This is the l"lAffidavit ofKim Rossmo in this case andwas made on the r{ltt¿sy s1October,2012.

Action No. 5112969Vancouver Registry

IN SUPREME COURT OF BRIT¡SH COLUMBIA

Between:

And:

Amanda Elizabeth Ladas

Plaintiff

Apple Inc,

Defendant

"Brought under the Class Proceedings Act, RSBC 1996, c. 50"

AFFIDAVIT

l, Kim Rossmo, Professor and Geographic Profiler, c/o Suite 302-1224 Hamilton

Street, in the City of Vancouver, Province of British Columbia, MAKE OATH AND SAY

THAT:

1. Attached hereto and marked as Exhibit "4" to this my affidavit is a true copy of

my expert report herein dated September 2012.

SWORN BEFORE ME at the Citv ofÈet:+.L, jn tre grff)éÌ'-f{. Kn< , this z$l- day ofOctober, 2012. tu

Kim Rossmo

MICHELE MUNIZNotary Public, State of Texas

i.XtS vy'commiásionExpires¿;i':lìs Morch 20,20]3

GenLiA9ST2laff#1 of Kim Rossmo

Introduction

This report was prepared by Dr. Kim Rossmo of Austin, Texas. My areas of expertise

include geographic profiling and investigations. A curriculum vitæ, outlining my qualifications,

employment, and education experience in my areas of expertise, is attached.

Instructions Provided and Nature of Opinion Sought

I was asked to prepare a report setting out possible uses, misuses and ramifications related to

and arising from the collection and storage of locational and other data on Apple smart devices,

as demonstrated by Francis Graf in connection with the Plaintiff s claims made in the Action.

This opinion relates to the issue of damages in this proceeding.

Opinion

My opinion and findings are laid out in the Consequences section below.

Reasons for Opinion

Assumptions

This report assumes that an Apple smart device (e.g., iPhone) running the iOS4x operating

system generates an unencrypted backup file containing location and date/time information for a

one-year period stored in a consolidated.db database file (re iOS4x Location Based Services

Analysis Report, June 6, 2012, by Francis Graf).

Methodologv

This report discusses possible misuses of the unencrypted backup file on Apple smart

devices running the iOS4x operating system, focusing on the loss of privacy implications for the

user. The likelihood of these misuses is not evaluated. The references used in the preparation of

this report are listed at the end.

Ädvice and Certification

I certifu that I afirawate of my duty to assist the court and not bo an advocate for any party,

that I have made this report in conformity with that duty; and that I will, if called on to give oral

or written testimony, give that testimony in conformity with that duty.

I am responsible for the contents of this report.

Respeetfu lly submitted,

D. Kim Rossmo, PhD

Introduction

Our daily routines, travels, and destinations say much about our lives. Many of our personal

activities can be inferred from where we go, when we travel, and how long we stay somewhere.

Just as we wish to keep our private conversations, financial status, and credit card purchases

private, we also do not want to be electronically "shadowed." Unfortunately, it appears that an

Apple smart device, such as the iPhone, which uses the iOS4x operating system, generates an

unencrypted backup file containing location and date/time information for a one-year period

stored in a consolidated.db database file (Graf, 2012).

The potential loss of privacy consequences to the user from this backup file depend upon

two factors: (1) the information that can be derived from the file's data (a function of

measurement precision, data comprehensiveness, and anal¡ic potential); and (2) from who can

access that data (exposure).

1. Information - The more information that can be derived from the data in the backup file,

the greater the loss of privacy. The information potential depends on the precision and

comprehensiveness of the data and on its analyic potential.

a. Precision - The more precisely an iPhone or similar Apple smart device determines

the position of a user, and the more precisely the time is recorded for when a user

was at a given position, the greater the loss of privacy.

b. Comprehensiveness - The higher the proportion of a user's movements recorded in

the backup file, the greater the privacy loss. Similarly, the longer the recording

period, the greater the privacy loss.

c. Analytic Potential - Location and time data can be mapped, measured, and analyzed

in a number of different ways, and can be used to generate derivative measures.

The greater the analytic potential of this information for inferring actions of the

user, the greater his or her privacy loss.

2. Exposure - The potential privacy loss consequences depend on who (i.e., individuals,

companies, and organizations) can access the user's Apple device backup file.

These factors are discussed in more detail below.

Information

Precision

The backup file contains the locations of cellular telephone towers and V/iFi sites that are

near the device when it is used, not the exact location of the device itself (Apple Press, 20ll).

This results in a loss of precision as there is almost always some distance between a device and

even the nearest cell tower or WiFi site. Furthermore, in an urban area, there are usually a

number of different cell towers and V/iFi sites within range of a device. Depending on how long

a device was operated in a given area, multiple locations - in different directions and varying

distances - will be recorded. The level of geographic accrüacy therefore depends on the density

of both cell phone towers and V/iFi locations in the surrounding atea, and on the street pattern or

highway network during travel.

Each location entry in the backup file includes the date and time the consolidated.db file was

updated; consequently, a large number of entries have the same date and time. The exact date

and time a position was recorded by the device is apparently not available from the f,rle (it is not

known if Apple has a way of accurately determining date/time information). Therefore,

temporal precision is low. Only a date-time interval can be determined, equal to the lag between

updates. The more often this happens, the narrower will be this range.

Comprehensiveness

The proportion of a user's movements recorded in the backup file appears to be related to

how often the Apple device is used and how it is used. An individual who frequently uses his or

her iPhone, especially while traveling, will have a greater proportion of his or her movements

recorded in the file.

The recording period for the backup file is one year. An individual engages in many

activities and much travel in a year, so consequently the file provides a great deal of personal

information about a user (Graf, 2012).

Anal)¡tic Potential

Even with the precision limitations discussed above, certain analyic techniques exist that

can improve geographic and temporal accuracy. For a stationary device, measures of geographic

central tendency such as the spatial mean, the spatial median, or the centre of minimum distance.

Figure 1 shows these measures for the WiFi sites from an Apple iPhone user's backup file (the

red circles are WiFi sites, the black triangle is the spatial mean, the white triangle is the spatial

median, and the yellow triangle is the centre of minimum distance). All three measures fall very

close to the user's offrce at 612 View Street, Victoria, British Columbia (marked with a blue

square), where she used her iPhone. Figure 2 shows the same measures for cell tower locations.

In this case, proximity to the user's office is lower, most likely because there were fewer towers

and their backcloth (i.e., their distribution in space) is less uniform. However, geographic

profiling, a more robust technique that is less sensitive to skewed spatial distributions, located

the user's office within a block (see Figures 3 and 4).

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Figure 1. Measures of geographic central tendency for WiFi sites.

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Figure 3. Geoprofìle of cell phone towers.

Figure 4. Geoprofile þeak 1%) of cell phone towers.

A moving device has only a couple of seconds to make a connection to a cell phone tower or

WiFi site. Consequently, there are fewer entries in a given arcaand it is much easier to discern

the user's movement, direction of travel, and often specific route (see Graf,2072).

Even though only the date and time the consolidated.db database file was updated is

recorded, it appears the locations are recorded in the file in chronological order. For example, all

the entries for an iPhone user's travel along British Columbia Highway 4 - from Port Albemi to

Parksville - show a date-time stamp of 11/18/1 I 6:25 pm (Graf, 2012). However, as can be seen

in Figure 5, moving from west to east the row number of the entry increases (e.g., 4685,4692,

4693, 4700,4709). Consequently, even though individual entries do not have an accurate time

10

stamp, they are listed in chronological order.

how the iPhone operates (Apple Press, 20lI).

This is consistent with the offrcial description of

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Figure 5. iPhone user's travel route on British Columbia Highway 4.

A location entry can therefore be both placed in chronological order in relationship to the

other location entries in the file, and bracketed by date and time (before or equal to its recorded

date-time and after the date-time of the prior update). This means that longer movements (i.e.,

greater than the median distance to nearby 'WiFi

sites, or approximately 100-200 meters in an

urban core) by the user can usually be detected from the consolidated.db update file. Finally,

logical inferences regarding starting times and speed allow for funher temporal accuracy. For

example, if a user traveled from his work site to abar, the arrival time can be estimated from

knowing when he usually left work, the distance between his work site and the bar, and the speed

limit.

11

It may be possible to use the location data in the consolidated.db update file to make several

inferences:

the location of the user's home - the location the user most commonly visited, at

daily intervals, and where the user typically spends the night

the location of the user's work - the location regularly visited during business hours,

on weekdays but not weekends, typically involving no movement for several hours

the locations where the user's relatives, relationships, and friends reside - residential

locations regularly visited, particularly during the evenings or on weekends

the location(s) of the user's significant relationships - residential locations regularly

visited, particularly during the evenings, on weekends, or ovemight

o the locations where the user engages in social activities - locations visited outside of

work hours, particularly during the evenings or on weekends

o other locations the user has visited

o travel and commuting routes.

The addresses and dates/times in the consolidated.db update file are not isolated data. The

file's total knowledge potential must be understood in the context of other geographic

information and existing spatial databases. Maplnfo (2004), a geographic information system

(GIS) company, claims that over 85%o of data has a geographic component. In other words, the

addresses in the consolidated.db update file are not isolated points. Rather, they are points that

can be placed on a map and seen within the context of such other geographic information as land

use, zoning, and nearby businesses, facilities, and residences. Additional knowledge can be

gained from any available ancillary information, such as telephone calls, websites visited, and

historical travel and behaviour patterns. Furthermore, patterns of movements and places visited

l2

over time reveal more about an individual than isolated locations. Such patterns extend over

both space and time. Under certain conditions, it is even possible to make future predictions of

behaviour from such data.

The lack of precision limits the accuracy of the inferences that can be made from the data in

the consolidated.db file. However, much can still be determined about a user, especially one

who often uses his Apple smart device, by employing various anal¡ic techniques. The length of

the backup file (one year) increases this anal¡ic potential.

An important issue emerges from the ambiguity of user movement caused by this lack of

precision. Situations will arise where erroneous information incorrectly suggests a user visited a

problematic location. If a user's backup file falls into the hands of individuals or agencies that

react on the basis of probabilities or suspicion, this could result in such negative consequences as

relationship strain, divorce, loss of employment or advancement opportunity, media allegations,

or unwarranted attention from law enforcement or govenìment intelligence agencies (see the

discussion in the Government subsection below).

Exposure

The nature and extent ofprivacy loss and consequent injury depends on who can gain access

to a uset's backup file. Access to the file can occur either physically or electronically. Physical

access could occur by a spouse, family member, friend, roommate, housekeeper, work colleague,

boss, secretary, subordinate, burglar, or thief. Electronic access could occur by Apple (assuming

Apple can access a user's backup file; see Smith, 2010, 2012) or by a hacker or network

eavesdropper (see Henry, 2012). Once an outsider has obtained a copy, the frle can be passed on

to anyone including advertisers, "trusted third parties," (i.e., Apple's partner companies), private

13

detectives, divorce lawyers, industrial espionage agents, debt collectors, police, goverrìment, and

intelligence agencies.

Some potential misuses are discussed below. These should be seen as possibilities, not

necessarily probabilities. However, given a large enough group of Apple users, it would not be

surprising to see many of these misuses eventually occur. Also, this is by no means a

comprehensive list.

Personal

Indiscriminate access to a user's backup file could have significant consequences for

familial, personal, and romantic relationships. It gives an individual the ability to track the

movements of his or her spouse in marital disputes, custody battles, and divorces. Visits to

certain locations (e.g., an ex-girlfriend) might cause strains in an engagement. A person could

use such information to undermine their siblings in an effort to influence the deliberations of

their parents regarding wills or inheritances.

Some families of certain cultures engage in comprehensive background checks of their

children's prospective husbands and wives. Apple smart device backup files could be used as

part of such a vetting.

V/ork

Some businesses have required job applicants to provide access to their Facebook accounts

(Maltais, 2012). "It's become standard practice for employers and schools to peruse potential

applicants' Facebook profiles. But in some cases, they are going even further: Some have

demanded applicants hand over their passwords so they can view individual's restricted profiles"

14

(Stem, 2012). Similarly, companies could ask prospective employees to provide the backup files

from their Apple smart devices. Software could easily evaluate the data for potential personnel

problems based on such warning signs as:

time away from work

frequent visits to problematic places (e.g., bars, nightclubs, racetracks, casinos, brothels,

vice districts, etc.).

In such situations, the onus would be on the job applicant to justify their behaviour.

A user who sometimes backs up his or her Apple device on an office computer exposes their

backup file to employers, supervisors, colleagues, employees, and administrative assistants.

Under certain conditions, loss of this information to the wrong person could jeopardize a

promotion, cause loss of employment, or even result in organizational blackmail.

Government

For obvious reasons, individuals engaged in criminal behavior do not want the backup files

of their Apple smart devices inspected by police. However, it is not just law breakers that might

have cause for concem. Intelligence and homeland security organizations operate on the basis of

possibilities and probabilities. If government agencies can gain access to a users' backup file

through Apple or an intermediate entity, an individual who was in - or even near - the wrong

place at the wrong time, could find themselves scrutinized by police or by an intelligence

service. Mere suspicion has been sufficient in the past for some people to be questioned, placed

on a watch list or do-not-fly registry, or refused entry into a country.

Governments have also used private data-mining companies to determine how public and

private records might be analyzed for certain security or military objectives. For example, a

15

marketing services business called Acxiom (http://www.acxiom.com/) sold demographic data on

a group of airline passengers to a U.S. Department of Defense contractor (U.S. should prosecute

JetBlue, 2003). Acxiom provided data on gender, home owner/renter status, years at residence,

income, number of children, Social Security numbers, occupation, and vehicle information

If Acxiom was an Apple "trusted third party,"l it could do much with the data in users'

backup files. Analysis and sale of such information is not restricted to person-based questions;

rather, it could just as easily be location or time based. For example, a request by a data

customer might be of the following nature:

1. Provide the identity of every Apple user within 100 meters of this particular address on

this particular date.

2. Filter that dataset by the following user characteristics (obtainable from individual

identifying information; see Smith,2010,2012): (1) gender; (2) age; (3) ethnicity; and

(4) occupation.

3. Cross-compare that result with the following govemment databases. . ..

Businesses

There are many ways that private businesses and companies could exploit the data in Apple

backup files, not all of them to the user's benefit. Targeted advertising is the most obvious one.

Marketing companies already use an individual's home address and the demographics of his or

her neighbourhood for delivery of direct ("junk") mail. Knowledge of a person's movements

and routine travels would open up a new world of invasive advertising possibilities.

I This phrase "trusted third party" raises the question, trusted by whom? A user might well have a very

different answer to this question than would Apple.

T6

More problematic is how insurance companies might use such information. Knowledge of a

user's movements could provide insight into an applicant's eating and drinking habits through

information on restaurants and bars frequented - which ones, how often, and for how long.

Automobile insurance companies may even be able to detect a user's risky driving behaviour

such as speeding.

The information in the Apple smart device backup files of key employees, managers, and

executives is valuable industrial espionage and could be exploited to advantage by business

competitors.

Criminals

Criminal access to a user's backup file, either through theft or by hacking, increases his or

her exposure to victimization. More sophisticated criminal groups could use this information to

determine when someone was likely to be present or away from certain locations such as their

home. Such knowledge could then be used to assist in the perpetration of fraud, identify theft, or

burglary. It would be disastrous if a user's backup file fell into the hands of a stalker. For

certain individuals, at risk of extortion, kidnapping, or terrorism because of their social, work, or

political position, the implications of a stolen file are even more sinister.

Other

The data in the backup hle of an Apple device owned by a movie celebrity, sports star,

politician, or other famous person would prove to be a bonanza of information and innuendo for

media outlets, tabloids, and scandal magazines. Similarly, the data could prove to be a potent

weapon in the hands of a rival candidate in any political election.

l7

Possible Misuses with Advanced Accuracy

The details of the exact data available to Apple (and through Apple, other businesses and

organizations) is not known. If Apple has methods for obtaining accurate location and time data

from the backup file, then the loss of user privacy is tremendous. With such information, it

would be possible to accurately generate what is c.alled a geospatial lifeline, defined as a

"continuous set of positions oceupied in space over some time period" (Mark, 1998, p. l2).

Figure 6 shows a typical example of an individual's one-month geospatial lifeline (Grengs,

W*g, & Kostyniuk, 2008).

18

Legend

Destlnatlon Vlslt Frequency22-4112-214-111-3

Route Visit Frequency

Figure 6. One-month geospatial lifeline.

Much can be derived from a person's lifeline. "Such individual lifelines presage a new era

of movement analysis ... in which scientists from various research fields previously hampered

by sparse and random movement observations can now be hard on the heels of their subjects as

they move in space and time" (Laube, Dennis, Forer, & 'Walker, 2007, p. a8\. Specialized

computer software, such as GeoTime developed by the Canadian company Oculus

l9

(nttp:¡¡www.geotime.c ), now exists for analyzing geospatial lifelines. Figure 7 shows an

example of a geospatial lifeline displayed in GeoTime.

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Figure 7. Geospatial lifeline displayed in GeoTime.

A geospatial lifeline obviously provides information on a user's position (location and time)

and movement (speed and direction). However, those who work in the field of Moving Object

Databases (MOD) have also developed complex models and query languages for analyzing

geospatial lifelines. For example, some of the existing context operators and standardization

techniques include location, interpolated locations, speed, acceleration, movement azimuth,

20

sinuosity, tortuosity, straightness, path entropy, navigational displacement, absolute and

standardized approaching rates, first derivatives, interval standard deviation, time series analysis,

path time and distance analyses, equal duration and track wrapping, spatial and temporal distance

analyses, bipolar analysis, and spatial variance analysis (Laube et al., 2007). Much can be

inferred from these measures.

A study on the geographic pattems of reoffending criminals illustrates the potential uses of

geospatial lifeline analysis. Parolees who reoffended while on an electronic monitoring (EM)

and global positioning system (GPS) program were identified and their movements for a period

of eight days prior to the new crime then mapped and analyzed (Rossmo, Lu, & Fang, 2011).

The objective was to study their spatial activity pattems prior to, during, and after offending in

order to distinguish routine travel from criminal movement. For example, the normal routine of

one particular parolee consisted of a single daily trip to a location northwest of his home.

However, three days before his re-offence he began to visit a commercial area to the northeast of

his home that was characteÅzed by restaurants, bars, motels, and parking lots. His movements

here exhibited hunting behaviour, as shown by the numerous stops and turns in this new part of

his geospatial lifeline. On his third trip to the commercial area he reoffended and sexually

assaulted a woman in a parking lot (see Figures 8 and 9).

2l

Legend

I ofiense location

I Home location

O GPS recorded poinls

Unban areas

V\fater areas

Trajectory 29th

Speed (mi/hr)

---- 0.00-500

----5.01 -15.00

¡rr¡ 15.01 -45.00

r r. r 45.0l - 95.16

Figure 8. Parolee's movements on offense day.

22

Legend

! offense location

I Home location

O GPS recorded points

Unban areas

Trajectory 29th

Speed (mi/hr)

---- 000-s.00

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ffMites0 01 02 04 06 08

Figure 9. Parolee's movements near crime

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site on offense day.

An analysis of this parolee's geospatial lifeline showed: (1) departure from nolmal routine;

(2) repeated visits to a new aïea; and. (3) high movement density2 (i.e., much travel back and

forth within a small region, indicative of search behaviour). These spatial aberrations,3

integrated with information on the area's land use and knowledge of the parolee's previous

2 Spatial activity patterns can also be categorized by such measures as total daily distance traveled, peak and

mean hourly velocity, momentum (changes in velocity over time), peak and mean density (travel within areal units),directional changes per hour, movement length between direction changes, and other indicators of search and huntbehavior as opposed to purposeful travel. Also important are type of area (e.g., land use, zoning, crime generatorsand attractors, etc.) traveled through and prior offender modus operandi factors.

3 A review of another EM program found the most common rule violation involved detours (Gibbs & King,2003). In contrast, if the routine movements of a pedophile intersects with locations frequented by children -schools, playgrounds, parks, daycare centers - he has a higher chance ofrecidivism (Ouimet & Proulx, I 994).

23

criminal behaviour, suggested a high probability of reoffending. The study concluded "It may be

possible to use electronic monitoring and global positioning system program data to assist in

offender risk evaluation during supervision. Differences in the movement patterns of offending

parolees could provide community supervision agents with an early warning tool to facilitate

timely interventions and help prevent new crimes" (Rossmo, Lu, &, Fang, 20ll,p.4l).

Multiple User and Social Network Analysis

Apple and its "trusted third parties" could have the ability to examine the intersection of

backup file data from multiple users, opening the door to powerful group analyses. Eagle and

Pentland (2006) demonstrated "the ability to use standard Bluetooth-enabled mobile telephones

to measure information access and use in different contexts, rccognize social patterns in daily

user activity, infer relationships, identiSr socially significant locations, and model organizational

rhythms.... The data these devices have returned to us is unprecedented in both magnitude and

depth. The applications we have presented include ethnographic studies of device usage,

relationship inference, individual behavior modeling, and group behavior analysis" (pp. 255,

267).

It is possible to determine existence and type of relationship from the intersection of

geospatial lifelines using such variables as context, proximity, time of day and day of week of

proximity, time length of proximity, and repetition of proximity. Models have been developed

that can accurately discern friends, acquaintances, and workplace colleagues on this basis (Eagle

& Pentland,2006; see Figure 10).

24

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Figure 10. Friendship and daily proximity networks.

Conclusion

Smart phones provide great functionality and utility. However, by the very use of this wide-

ranging functionality, an individual reveals much about their personal preferences, choices, and

behaviours. This information must be protected and a user's privacy maintained.

There is great value in this personal data for Apple and other businesses; however,

individuals are not paid for it and they do not realize they might be giving it away. No one

would want indiscriminate disclosure of their banking information or credit card purchase

history. Similarly, few who understand the full implications of sharing the information in their

backup file would willingly agree to do so.

The sensitivity to the loss of privacy regarding our personal movements can be seen in the

reactions to a study on individuals' movements which only used aggregated (i.e., not

individualized, like the data in an Apple backup file) location-tracking data from 100,000

cellphones in Europe (Gonzéùez, Hidalgo, & Barabási, 2008):

The use of cellphones to track people, even anonymously, has implications for privacy that

make this "a troubling study," said Marc Rotenberg, a founder of the Electronic Privacy

an

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25

Information Center in V/ashington. The study, Mr. Rotenberg said, "raises questions about

the protection of privacy in physical spaces, when devices make possible the capture of

locational data."

There are serious ethical issues as well, said Arthur Caplan, director of the Center for

Bioethics at the University of Pennsylvania. While researchers are generally free to observe

people in public places without getting permission from them or review from institutional

ethics boards, Mr. Caplan said, "your cellphone is not something I would consider a public

entity." (Schwartz, 2008)

In 1984, the world was introduced to the Apple Macintosh computer by a now famous Super

Bowl commercial which depicted a female heroine resisting the tyranny of Big Brother. In

George Orwell's dystopian novel, Big Brother was the omniscient head of a totalitarian

government. In 2012, we must be careful that Big Business does not take the place of Big

Brother.

26

References

Apple Press Info. (2017, April2T). Apple Q&A on location data. Retieved July 30,2012 from

the World V/ide Web:

Data.html.

Brantingham, P. J., & Brantingham, P. L. (Eds.). (1981). Environmental uiminology. Beverly

Hills: Sage.

Brantingham, P. J., & Brantingham, P. L. (1984). Patterns in crime. New York: Macmillan.

Clarke, R. V,, & Felson, M. (Eds.). (1993). Routine activity and rational choice. New

Brunswick, NJ: Transaction.

Cox, K. R., & Golledge, R. G. (Eds.). (1969). Behavioral problems in geography.Evansfon, IL:

Northwestem University Press.

Eagle, N., & Pentland, A. (2006). Reality mining: Sensing complex social systems. Journal of

P ers onal and Ubiquitous C omputing, I 0, 25 5 -268.

Fenton, W. (2011, April 22). How to see the secret tracking data in your iPhone. PC Magazine.

Retrieved July 30, 2012 from the Word Wide V/eb:

Gibbs, A., & Krg, D. (2003). The electronic ball and chain? The operation and impact of home

detention with electronic monitoring in New Zealand. The Australian and New Zealand

Journal of Criminolo g,t, 3 6, l -17 .

Golledge, R. G., & Stimson, R. J. (1987). Analytical behavioural geography. New York:

Routledge.

Gonzâlez, M. C., Hidalgo, C. ,A.., & Barabási, A.-L. (2008). Understanding individual human

mobility pattems. Nature, 45 3, 779-7 82.

27

Gould, P., & White, R. (1986). Mental maps (2"d ed.). London: Routledge.

Grat F. (2012). iOS4x location based services analysis report. Unpublished report. Vancouver,

BC.

Grengs, J., 'Wang, X., & Kostyniuk, L. (2003). Using GPS data to understand driving behavior.

Journal of Urban Technolo gy, I 5 (2), 33-53.

Henry, A. (2012, September 4). 1 million Apple device IDs leaked, 12 million total stolen.

Lifehacker. Retrieved September 5, 2012 from the V/orld Wide V/eb:

Jakle, J. 4., Brunn, S., & Roseman, C. C. (1976). Human spatial behavior: A social geography.

Prospect Heights, IL: 'Waveland Press.

Laube, P., Dennis, T., Forer, P., & Walker, M. (2007). Movement beyond the snapshot -

Dynamic analysis of geospatial lifelines. Computers, Environment and Urban Systems,3I,

481-s01 .

Maltais, M. (2012, March 20). Asking job applicants for Facebook password, fair or legal? Los

Angeles Times. Retrieved JuIy 25,2012 from the World V/ide Web:

facebook-20120320.

Maplnfo (2004). Technology Provider Opportunities with Maplnþ in Insurance. Retrieved July

25,2012 from the World Wide Web:

portunties.pdf.

Mark, D. M. (1998). Geospatial lifelines. Integrating spatial and temporal databases, Vol.

9847 L Dagstuhl Seminars.

28

Ouimet, M., & Proulx, J. (1994, November). Spatial and temporal behaviour of pedophiles:

Their clinical usefulness as to the relapse prevention model. Paper presented at the meeting

of the American Society of Criminology, Miami, FL.

Rossmo, D. K. (2000). Geographic profiling. Boca Raton, FL: CRC Press.

Rossmo, D. K., Lu, Y., &.Fang,T. (2011). Spatial-temporal crime paths. In M. A. Andresen & J.

B. Kinney (Eds.), Patterns, prevention, and geometry of crime (çry. 16-42). London:

Routledge.

Schmitz, P. M. U., Rossmo, D. K., de Jong, T., & Cooper, A. (2007, March). Determining

criminal activity space using mobile phone technology. Paper presented at the NIJ Mapping

and Public Safety Conference, Pittsburgh, PA.

Schwartz, J. (2008). Cellphone tracking study shows we're creatures of habit. The New York

Times. Retrieved August 22, 2012 from the World Wide Web:

Sistla, A. P., Wolfson, O., Chamberlain, S., & Dao, S. (1997). Modeling and querying moving

objects. Proceedings of the l3th International Conference on Data Engineering (ICDEI3)

(pp.422-432). Birmingham, UK: University of Birmingham.

Smith, E. (2010). iPhone applications & privacy issues: An analysis of application transmission

of iPhone Unique Device ldentifiers (UDIDs). Unpublished report. Lewisburg, PA.

Smith, E. (2012). iOS4x operating system privacy issues: An analysis of data transmitted from

an Apple device to the Apple Corporation. Unpublished report. Lewisburg, PA.

Stem, J. (2012, March 26). Demanding Facebook passwords may break law, say senators. IBC

World News. Retrieved August 24, 2012 from the World V/ide Web:

29

" t-

Taylor, P. J. (1977). Quantitative methods in geograp,hy. Prospect Heights, IL: Waveland Press.

UK National Statistics Online. (2003). The UK 2000 Time Use Survey. Retrieved July 25,20O4

from the World Wide V/eb:

U.S. should prosecute JetBlue, privacy group says. (September 22,2003). USA Today. Retrieved

August 24, 2012 from the World Wide Web:

Walmsley, D. J., & Lewis, G. J. (1984). Human geography: Behavioural approaches. London:

Longman.

Wolfson, O., & Mena, E. (2005). Applications of moving objects databases. In Y. Manolopoulos,

A. Papadopoulos, & M. Vassilakopoulos (Eds.), Spatial databases: technologies, techniques

and trends (pp. 186-203). Hershey, PA: Idea Group Publishing.

30

D. Kim RossmoCurriculum Vitæ

Summary of Professional BackgroundDr. Kim Rossmo is the University Endowed Chair in Criminology, and the Director of theCenter for Geospatial Intelligence and Investigation in the School of Criminal Justice at TexasState University. He has a PhD in criminology from Simon Fraser University, and has

researched and published in the areas of environmental criminology, the geography of crime, andcriminal investigations. Dr. Rossmo was formerly a management consultant with the Bureau ofAlcohol, Tobacco, Firearms and Explosives (ATF), and the Director of Research for the PoliceFoundation in Washington, DC. Before that, he was the Detective Inspector in charge of theVancouver Police Department's Geographic Profiling Section, which provided investigativesupport for the intemational law enforcement community. Dr. Rossmo is a member of theIntemational Association of Chiefs of Police (IACP) Advisory Committee for PoliceInvestigative Operations and is an Adjunct Professor at Simon Fraser University. He sits on theeditorial board for Homicide Studies and is a Full Fellow of the Intemational CriminalInvestigative Analysis Fellowship (ICIAF). Recently, Dr. Rossmo completed projects studyingthe geospatial structure of terrorist cells, geographic profiling applications in counter-insurgency,and patterns of illegal border crossings. He has also analyzed the spatial dynamics of animalforaging, including white shark predation and the origins of infectious diseases. He has

published books on geographic profiling and criminal investigative failures. In 2000, Dr.Rossmo was awarded the Governor General of Canada Police Exemplary Service Medal. Hewas appointed to the City of Austin Public Safety Commission in 2009.

EmploymentTexas State University

University Endowed Chair in Criminology, School of Criminal Justice (2007-present)Director, Center for Geospatial Intelligence and Investigation (2004-present)Research Professor, School of Criminal Justice (2003 - present)

Simon Fraser UniversityAssociate Scholar, Institute for Canadian Urban Research Studies (2004-present)Adjunct Professor, School of Criminology (1996-present)Sessional Instructor, School of Criminology (1988-1995)

Environmental Criminology Research Inc.Chief Scientist ( 1 996-present)

Bureau of Alcohol, Tobacco, Firearms and ExplosivesManagement Consultant (2003 -2005)

Police FoundationDirector of Research (2001-2003)

Vancouver Police DepartmentDetective Inspector, i/c Geographic Profiling Section (1995-2000)Constable, Patrol, Expo 86, Community Liaison, CLEU Intel, Crime Prevention (1980-1995)Communications Operator, Communications Centre ( 1 978-2000)

EducationDegreesPhD (Criminology, 1996), Simon Fraser University

Dissertation: Geographic Profiling: Target Patterns of Serial MurderersM.A. (Criminology, 1988), Simon Fraser University

Thesis: Fugitive Migration PatternsB.A. (Sociology, 1978), University of Saskatchewan

Certifi cates and CertificationsAdvanced Police Studies, General Police Studies; Canadian Police CollegePolice Advanced Certificate of Education, Police Studies Certificate Program; Justice Institute of

British ColumbiaPOST certified, CalifomiaTCLEOS certified, Texas

PublicationsBooksRossmo, D. K. (2000). Geographic profiling. Boca Raton, FL: CRC Press.Rossmo, D. K. (2002). Geographic profiling (S. Watanabe, K. 'Watanabe, M. Suzuki, & T.

Shimada, Trans.). Kyoto: Kitaohji Shobo. (Original work published 2000).Rossmo, D. K. (2007). Geographic profiling (M. Lee, Trans.). Beijing: Chinese Public Security

University Press. (Original work published 2000).Rossmo, D. K. (2009). Criminal investigative failures. Boca Raton, FL: Taylor & Francis.

Book ChaptersBeauregard,E., & Rossmo, D. K. (2007). Profilage géographique et analyse des tactiques de

chasse chez les agresseurs sexuels sériels. In M. St-Yves & M. Tanguay (Eds.), Psychologiede I'enquête criminelle: La recherche de la vérité (pp. 577-605). Cowansville, Québec: LesEditions Yvon Blais.

Beauregard,E., & Rossmo, D. K. (2008). Geographic profiling and analysis of the huntingprocess used by serial sex offenders. In M. St-Yves & M. Tanguay (Eds.), The psychology ofcriminal investigations: The searchfor the truth (çry. 529-55a) (J. Miller, Trans.). Toronto:Carswell. (Original work published 2007).

Beauregard, E., Rossmo, D. K., & Proulx, J. (2011). A descriptive model of the hunting process

of serial sex offenders: A rational choice approach. In M. Natarajan (Ed.), Crimeopportunity theories: Routine activity, rational choice qnd their variants. Surrey, UK:Ashgate.

Holmes, R. M., & Rossmo, D. K. (2002). Geography, profiling, and predatory criminals. In R.M. Holmes & S. T. Holmes, Profitüngviolent øimes; An investigative tool (3'd ed.) þp. 20S-

222). Thousand Oaks, CA: Sage.

Rossmo, D. K. (1995). Multivariate spatial profiles as a tool in crime investigation. In C. R.Block, M. Dabdoub, & S. Fregly (Eds.), Crime analysis through computer mapping (pp. 65-97). Washington, DC: Police Executive Research Forum.

Rossmo, D. K. (1995). Place, space, and police investigations: Hunting serial violent criminals.In J. E. Eck & D. L. Weisburd (Eds.), Crime and place: Crime prevention studies, Vol. 4(pp.2I7-235). Monsey, NY: Criminal Justice Press.

Rossmo, D. K. (1995). Strategic crime patteming: Problem-Oriented policing and displacement.In C. R. Block, M. Dabdoub, & S. Fregly (Eds.), Crime analysis through computer mapping

þp. 1-1a). Washington, DC: Police Executive Research Forum.Rossmo, D. K. (1996). Targeting victims: Serial killers and the urban environment. In T.

O'Reilly-Fleming (Ed.), Serial and mass murder: Theory, research and policy þp. 133-153). Toronto: Canadian Scholars' Press.

Rossmo, D. K. (1997). Geographic profiling. In J. L. Jackson & D. A. Bekerian (Eds.), Offenderprofiling: Theory, research and practice (pp. 159-175). Chichester: John Wiley & Sons.

Rossmo, D. K. (1997). Geographic prof,rling. In J. L. Jackson & D. A. Bekerian (Eds.), Offenderprofiling. Theory, research and practice (Japanese translation).

Rossmo, D.K. (1997). Place, space, and police investigations: Hunting serial violent criminals.In D. V. Canter &,L. J. Alison (Eds.), Criminal detection and the psychology of uime (pp.507 -525). Aldershot, Hants : Ashgate Publishing (reprint).

Rossmo, D. K. (2003). Maps, technology, and the search for treasure. In M. R. Leipnik & D. P.

Albert (Eds.), GIS in law enforcement: Implementation issues and case studies (pp.xii-xiv).London: Taylor & Francis.

Rossmo, D. K. (2004). Geographic profiling. In Q. C. Thurman &, J. Zhao (Eds.), Contemporarypolicing: Controversies, challenges, and solutions (pp.274-284). Los Angeles: RoxburyPublishing (reprint).

Rossmo, D. K. (2004). Geographic prof,rling as problem solving for serial crime. In Q. C.Thurman &, J.D. Jamieson (Eds.), Police problem solving þp. 121-131). Cincinnati:Anderson Publishing.

Rossmo, D. K. (2004). Geographic profiling update. In J. H. Campbell & D. DeNevi (Eds.),Profilers: Leading investigators take you inside the criminal mind (pp.29I-312). Amherst,NY: Prometheus Books.

Rossmo, D. K. (2005). The deadlier of the species. In H. Scott, The female serial murderer: Asociological study of homicide and the " gentler sex" (çry. i-iii). Lewiston, NY: EdwinMellen Press.

Rossmo, D. K. (2005). Geographical profiling. In M. Strano &,R.Bnnzone (Eds.),Psychological uiminal profiling: Manuale operativo (chap. 4). Florence: Societa EditriceEuropea.

Rossmo, D. K. (2006). Geographic profiling in cold case investigations. In R. Walton(Ed.), Coldcase homicides: Practical investigative techniques (pp. 537-560). Boca Raton, FL: CRCPress.

Rossmo, D. K. (2008). Geographic profiling. In M. Strano (Ed.), Manuale di investigazionecriminale (pp. a07-al7). Rome: International Crime Analysis Association.

Rossmo, D. K. (2008). Place, space, and police investigations: Hunting serial violent criminals.In D. V. Canter & D. Youngs (Eds.), Principles of geographical offender profiling (pp. A9-I 63). Aldershot, Hampshire : Ashgate Publishing.

Rossmo, D. K. (2009). Geographic profiling in serial rape investigations. In R. R. Hazelwood &A. W. Burgess (Eds.), Practical aspects of rape investigation: A multidisciplinary approach(4th ed.). Boca Raton, FL: CRC Press.

Rossmo, D. K., & Fisher, D. K. (2004). Problem solving prostitution in a problem neighborhood.In Q. C. Thurman & J. D. Jamieson (Eds.), Police problem solving (pp. 87-96). Cincinnati:Anderson Publishing.

Rossmo, D. K., Laverty, I., & Moore, B. (2005). Geographic profiling for serial crimeinvestigation. In F. Wang (Ed.), Geographic inþrmation systems and uime analysis (pp.102-117). Hershey, PA: Idea Group Publishing.

Rossmo, D. K., Lu, Y., &.Fang, T. (2011). Spatial-temporal crime paths. In M. A. Andresen & J.

B. Kinney (Eds.), Patterns, prevention, and geometry of crime (pp. 16-42). London:Routledge.

Rossmo, D. K., & Rombouts, S. (2008). Geographic profiling: An investigative application ofenvironmental criminology. In R. Wortley & L. Mazerolle, Environmental criminology andcrime analysis (pp. 136-1a9). Cullompton, Devon: Willan Publishing.

Rossmo, D. K., & Velarde, L. (2008). Geographic profiling analysis: Principles, methods, andapplications. In S. Chainey & L. Tompson (Eds.), Crime mapping case studies: Practice andresearch þp. 35-a3). Chichester: John V/iley & Sons.

Saville, G. J., & Rossmo, D. K. (1995). 'striking a balance': Lessons from problem-orientedpolicing in British Columbia. In K. M. Hazlehurst (Ed.), Perceptions ofjustice: Issues inindigenous and community empowerment (pp. 119-I4l). Aldershot, England: Avebury.

Refereed Journal ArticlesBeauregard, E., Proulx, J., Rossmo, D. K., Leclerc, 8., & Allaire, J.-F. (2007). Script analysis of

the hunting process of serial sex offenderc. Criminal Justice and Behavior, 34,1069-1084.Beauregard, E., Rebocho, M. F., & Rossmo, D. K, (2010). Target selection patterns in rape.

Journal of Investigative Psychology and Offender Profiling, 7, I37 -I52.Beauregard, E., Rossmo, D. K., & Proulx, J. (2007). A descriptive model of the hunting process

of serial sex offenders: A rational choice approach. Journal of Family Violence, 22, 449-463.

Blair, J.P., &, Rossmo, D. K. (2010). Evidence in context: Bayes' Theorem and investigations.Police Quarterly, I 3, 123-I35.

Le Comber, S. C., Nicholls, 8., Rossmo, D. K., & Racey, P. A. (2006). Geographic profiling andanimal foraging. Journal of The or etical Biolo gy, 2 4 0, 233 -240.

Le Comber, S. C., Rossmo, D. K., Hassan, A. N., Fuller, D. O., & Beier, J. C. (2011).Geographic profrling as a novel spatial tool for targeting infectious disease control.International Journal of Health Geographics, 10,35-42.

Martin, R. 4., Rossmo, D. K., & Hammerschlag, N. (2009). Hunting pattems and geographicprofiling of white shark predation. Journal of Zoolo gt, 2 7 9, 1 1 1 - 1 1 8.

Raine, N. E., Rossmo, D. K., & Le Comber, S. C. (2009). Geographic profiling applied to testingmodels of bumble-bee foraging. Journal of the Royal Society Interface,6,307-319.

Rossmo, D. K. (1993). Target patterns of serial murderers: A methodological model. AmericanJournal of Criminal Justice, 17(2),1-2I.

Rossmo, D. K. (1994). A primer on criminal geographic targeting. IALEIA Journal,9(l),l-12.Rossmo, D. K. (2005). Geographic heuristics or shortcuts to failure?: Response to Snook et al.

Applied Cognitive Psycholog,,, I 9, 651-654.

Rossmo, D. K. (2005). Geographical profiling. Forze civili: Dialogo cultura per la legalita

[Official Review of the Italian Police Offrcers Association], 3(1), 13-16.Rossmo, D. K. (2006). Criminal investigative failures: Avoiding the pitfalls. FBI Law

Enþrcement Bulletin, 7 5 (9), | -8.Rossmo, D. K. (2006). Criminal investigative failures: Avoiding the pitfalls (Part two). FBI Law

Enforcement Bulletin, 7 5 (10), 12-19.Rossmo, D. K. (2011). Evaluating geographic prof,rling. Crime Mapping: A Journal of Research

and Practice,3,42-65.Rossmo, D. K. (2011). A reality response to Bridges' "A structured geospatial analytic method

and pedagogy for the intelligence community." IALEIA Journal,20(l),91-106.Rossmo, D.K. (2012). Recent developments in geographic prohling. Policing: A Journal of

Policy and Practice, 6, 144-1 50.Rossmo, D. K., & Harries, K. D. (2011). The geospatial structure of terrorist cells. Justice

Quarterly, 28, 221 -248.Rossmo, D.K., & Routledge, R. (1990). Estimating the size of criminal populations. Journal of

Quantitative Criminolo g!, 6, 293 -3 14.Rossmo, D. K., & Saville, G. J. (1991). Policing Challenge 2000: Riding the winds of change.

Canadian Journal of Criminology, 33,543-549.Rossmo, D. K., Thurman, Q. C., Jamieson, J. D., & Egan, K. (2008). Geographic pattems and

profiling of illegal crossings of the southern U.S. border. Security Journal, 21,29-57 .

Schmitz, P., Cooper, 4., de Jong, T., & Rossmo, K. (submitted for publication). Mappingcriminal activity space using cellular (mobile) telephone data. Professional Geographer.

Stevenson, M. D., Rossmo, D. K., Knell, R. J., & Le Comber, S. C. (2012). Geographic profilingas a novel spatial tool for targeting the control of invasive species. Ecography, 35.

Taylor, 8., Brooks, J., Phanidis, J., & Rossmo, D. K. (1991). Services for Vancouver streetyouth: An integrated delivery model. Journal of Child and Youth Care,6(3),49-61.

Non-Referred ArticlesBoyd, N., & Rossmo, D. K. (1994, February). David Milgaard, the Supreme Court and Section

690: A wrongful conviction revisited. Canadian Lawyer,pp.28-29,32.Fleming, 2., & Rossmo, D. K. (1996). Optimizing patrol resources: Vancouver's 4lll íeam

model. RCMP Gazette, 5 8(6), 2-9.Rossmo, D. K. (1991). After the use of deadly force: What you should be aware of. Blue Line

Magazine, 3(4),19-20.Rossmo, D. K. (1999, March). Geographic profiling system helps catch criminals. GeoWorld,p.

41.Rossmo, D. K. (2009, October). Failures in criminal investigation. The Police Chief pp.54-66.Rossmo, D. K. (2010). Criminal investigative failures. RCMP Gazette, T2(l),30-31.Rossmo, D. K., & Davies, A. (2001). Stealth predator pattems. Crime Mapping News, 3(4),6-7.Rossmo, D. K., & Filer, S. (2005). Analysis versus guesswork: The case for professional

geographic profiling. Blue Line Magazine, l7(7),24-25.Rossmo, D. K., Filer, S., & Sesely, C. (2005). Geographic profiling debate - round four: The big

problem with Bennell, Snook and Taylor's research. Blue Line Magazine, 17(9),28-29.Rossmo, D. K., & Fisher, D. K. (1993). Problem-Oriented policing: A cooperative approach in

Mount Pleasant, Vancouver. RCMP Gazette, J5(1), 1-9.

ReportsBoyd, N., & Rossmo, D. K. (1992). Milgaardv. The Queen: Finding justice - Problems and

process. Burnaby, BC: Criminology Research Centre, Simon Fraser University.Brown, R. O., Rossmo, D. K., Sisak, T., Trahern, R., Jarret, J., & Hanson, J. (2005). Geographic

profiling military capabilities. Final report submitted to the Topographic EngineeringCenter, Department of the Army, Fort Belvoir, VA.

Hotel, C, & Rossmo, D. K. (1993). Creating a safer Vancouver: Safer City Task Forcequestionnaire results. In Safer City Task Force: Final report (pp.3a9476). Vancouver:Author.

Rossmo, D. K. (2005). Geographic Profilingfor Military Applications: Report on Sofh,vareEvaluation for the National Technology Alliance (NTA).

Rossmo, D. K. (2008). Geographic profilingfor military applications. Final report submitted tothe Topographic Engineering Center, Department of the Army, Fort Belvoir, VA.

Rossmo, D. K. (2009). Criminal hunting paths: An analysis of the spatial behavior of recidivists.Final report submitted to the Bureau of Justice Assistance, Office of Justice Programs.

Rossmo, D. K., Davies, A., & Patrick, M. (2004). Exploring the geo-demographic and distancerelationships between stranger rapists and their offinces (Special Interest Series: Paper 16).London: Research, Development and Statistics Directorate, Home Office.

Rossmo, D. K., Thurman, Q. C., & Jamieson, J. D. (2005). Geographic patterns and profiling ofillegal crossings of the southern U.S. border. Office of Science and Technology, NationalInstitute of Justice (NIJ).

Rossmo, D. K., &,Egan, K. (2007). Illegal U.S. land border crossings by American citizens.Bureau of Justice Assistance, Office of Justice Programs.

Book ReviewsRossmo, D. K. (1993). fReview of Violence and public anxiety: A Canadian casel. Culture,

I3(2),109-1 10.

Rossmo, D. K. (2006). fReview of Policing illegal drug markets: Geographic approaches tocrime reduction]. Canadian Journal of Criminologt and Criminal Justice,4S(6),943.

OtherRossmo, D. K. (1993). Strategic crime patteming: Problem-Oriented policing and displacement.

In C. R. Block & M. Dabdoub (Eds.), Worl<shop on crime analysis through computermapping; Proceedings: 1993 (pp. 5-20). Chicago: Illinois Criminal Justice InformationAuthority.

Rossmo, D. K. (1993). Multivariate spatial profiles as a tool in crime investigation. In C. R.Block & M. Dabdoub (Eds.), Workshop on uime analysis through computer mapping,'Proceedings: 1993 þp. 89-126). Chicago: Illinois Criminal Justice Information Authority.

Rossmo, D. K. (1993). Geographic profiling: Locating serial killers. In D. Zafun & P. F.

Cromwell (Eds.), Proceedings of the International Seminar on Environmental Criminologyand Crime Analysis (çry.1a-29). Coral Gables, FL: Florida Criminal Justice ExecutiveInstitute.

Rossmo, D. K. (1994, Fall). STAC tools: The Crime Site Probability Program. STAC News,pp.9, 14.

Rossmo, D. K. (2003). Geographic profiling. In E. W. Hickey (Ed.), Encyclopedia of murder andviolent uime (pp.205-209). Thousand Oaks, CA: Sage.

Rossmo, D. K. (2004). A day in the life: Geographic profiler. In C. H. Wecht, Crime scene

investigation: Crack the case with realJife experts. Pleasantville, NY: Reader's DigestAssociation.

Rossmo, D. K. (2005). An evaluation of NIJ's evaluation methodologtþr geographic profilingsoftware. Retrieved March 8,2007 from the World Wide Web:http ://www.ojp.usdoj. gov/niì/maps/gp.html.

Rossmo, D. K. (2005). Geographic profiling. InThe Serial Murder Symposium: CollectedReadings. Quantico, VA: National Center for the Analysis of Violent Crime: Quantico, VA.

Scholarl)¡ PresentationsBeauregard, E., Leclerc, 8., Rossmo, K., & Proulx, J. (2005, November). A script analysis of

patterns in the hunting process of serial sex offenders. Paper presented at the meeting of theAmerican Society of Criminology, Toronto, ON.

Beauregard, E., Proulx , J., & Rossmo, D. K. (2005, Decemb er). An investigation of scripts of thehunting process in serial sex offenders: Implications þr geographic profiling. Paperpresented at the meeting of the 8th Intemational Investigative Psychology Seminar, London,UK.

Beauregard, 8., Rossmo, D. K., & Proulx, J. (2005, October). A descriptive model of the huntingstrategies of serial sex offinders: A rational choice approach (Modèle descriptif destactiques de chasse des agresseurs sexuels sériels: Une approche de choixrationnel). Paperpresented at the 3'd International Francophone Meeting on Sexual Aggression, October,Hull, QC.

Boyd, N., & Rossmo, D. K. (1993, February). Interpreting homicide patterns. Paper presented atthe conference of the Vy'estem Society of Criminology, Berkeley, CA.

Boyd, N., & Rossmo, D. K. (2000, February). Awrongful murder conviction: The relevance ofgeographic profiling. Paper presented at the conference of the Western Society ofCriminology, Kona, HI.

Cooper, A. K., Schmitz, P. M. U., Byleveld, P., & Rossmo, D. K. (2000, December). Using GISand digital aerial photography to assist in the conviction of a serial killer. Paper presentedat the meeting of the Crime Mapping Research Center, San Diego, CA.

Fang, T., Lu, Y., Rossmo, D. K., Blair, P. (2010, April). Recidivism route analysis with GPSdata: A case study. Paper presented at the meeting of the Association of AmericanGeographers, Washinglon, DC.

Glackman, W., & Rossmo, D. K. (199i, November). Job perceptions in a policing organization.Paper presented at the meeting of the American Society of Criminology, San Francisco, CA.

Martin, R. 4., Rossmo, D. K., & Hammerschlag, N. (2006, July). Geographic profiling of whiteshark predation.Paper presented at the meeting of the American Elasmobranch Association,New Orleans, LA.

Moore, B. J., & Rossmo, D. K. (1999, November). Geographic profiling. Paper presented at themeeting of the American Society of Criminology, Toronto, ON.

Otín del Castillo, J. M., Rossmo, D. K., & Summers, L. (2011, November). Análisis de

vinculación y perfiles geográficos: Un estudio de caso sobre robos de domicilio seriales en

Zaragoza fCrime linknge and geographic profiling: A case study of serial residentialburglary in Saragossø]. Paper presented at the II Seminario Internacional de InvestigaciónCriminal, Valladolid, Spain.

Quinet, K., &. Rossmo, D. K. (2004,November). Estimating missing persons as serial murdervictims. Paper presented at the meeting of the American Society of Criminology, Atlanta,GA.

Rossmo, D. K. (1990). Thefuture of policing. Police: Challenge 2000 Conference, Vancouver,BC.

Rossmo, D. K. (1990, March). The impact of space on urban crime: Vancouver's Skid Row.

Paper presented at the meeting of the Canadian Association of Geographers, Vancouver,BC.

Rossmo, D. K. (1990, November). Fugitive migration patterns: An application of the

destination-specific gravity model. Paper presented at the meeting of the American Societyof Criminology, Baltimore, MD.

Rossmo, D. K. (199I). Geographic profiling in arson investigation.B.C. Fire InvestigationSeminar, Victoria, BC.

Rossmo, D. K. (1991). Privatization in policing.Westem Negotiators Conference, Vancouver,BC.

Rossmo, D. K. (1991, February). Police predatory range and uiminal migration.Paperpresented at the conference of the Western Society of Criminology, Berkeley, CA.

Rossmo, D. K. (1992, November). Chaos theory and criminologt. Paper presented at themeeting of the American Society of Criminology, New Orleans, LA.

Rossmo, D. K. (1992). Geographic profiles of serial murder.International Conference on Serialand Mass Murder, Windsor, ON.

Rossmo, D. K. (1992). Target patterns of serial murderers. American Society of Criminologymeeting, New Orleans, LA.

Rossmo, D. K. (1993, May). Geographic profiling: Locating serial killers. Paper presented at theIntemational Seminar on Environmental Criminology and Crime Analysis, Miami, FL.

Rossmo, D. K. (1993, August). Multivariate spatial profiles as a tool in crime investigation.Paper presented at the V/orkshop on Crime Analysis Through Computer Mapping, Chicago,IL.

Rossmo, D. K. (1993, August). Strategic crime patterning: Problem-Oriented policing anddisplacement.Paper presented at the V/orkshop on Crime Analysis Through ComputerMapping, Chicago, IL.

Rossmo, D. K. (1993, October). Beyond the crime scene tape: Analyzing geographic clues. Paper

presented at the meeting of the American Society of Criminology, Phoenix, AZ.Rossmo, D. K. (1994, March). Investigative geographic profiling: Validity, reliability, and

utility. Paper presented at the meeting of the Academy of Criminal Justice Sciences,Chicago, IL.

Rossmo, D. K. (1994, June). Geographic profiling. Paper presented at the International Seminaron Environmental Criminology and Crime Analysis, Newark, NJ.

Rossmo, D. K. (1994, September). Geographic profiling and investigative informationmanagement.Paper presented at the meeting of the Intemational lnvestigative PsychologySeminar, Liverpool, UK.

Rossmo, D. K. (1994, November). Cognitive maps and geographic fingerprints of serialcriminals. Paper presented at the meeting of the American Society of Criminology, Miami,FL.

Rossmo, D. K. (1995, February). Hunting patterns of serial violent offenders. Paper presented at

the conference of the'Westem Society of Criminology, San Diego, CA.

Rossmo, D. K. (1995, July). Human raptors; Criminql hunting behaviour and crime site choice.Paper presented at the International Seminar on Environmental Criminology and CrimeAnalysis, Cambridge, UK.

Rossmo, D. K. (1995, November). Raptors, stalkers, and trappers: Hunting styles of serialkillers. Paper presented at the meeting of the American Society of Criminology, Boston,MA.

Rossmo, D. K. (1996, February). Learning, displøcement, and the geography of serial murder.Paper presented at the conference of the Westem Society of Criminology, Sonoma, CA.

Rossmo, D. K. (1996, July). Probability surfaces and the geography profiling of serial killers.Paper presented at the Third International Conference on Forensic Statistics, Edinburgh,UK.

Rossmo, D. K. (1996, September). Geographic profiling. Paper presented at the meeting of the

International Investigative Psychology Seminar, Liverpool, UK.Rossmo, D. K. (1996, November). Spatial patterns ofjourneys to crime. Paper presented at the

meeting of the American Society of Criminology, Chicago, IL.Rossmo, D.K. (1997, February). Paper presented at the conference of the Westem Society of

Criminology, Honolulu, HI.Rossmo, D. K. (1997, June). GIS and police investigation: From data to lcnowledge. Paper

presented at the International Seminar on Environmental Criminology and Crime Analysis,Oslo, Norway.

Rossmo, D. K. (1997, October). Geographic profiling. Paper presented at the meeting of the

Crime Mapping Research Center, Denver, CO.Rossmo, D. K. (1997, November). "Murder Alley": The ecologt of dangerous places. Paper

presented at the meeting of the American Society of Criminology, San Diego, CA.Rossmo, D.K. (1997, November). Rigel: The new geographic profiling sofh,vare. Paper

presented at the meeting of the American Society of Criminology, San Diego, CA.Rossmo, D. K. (1998, February) . Criminal predcttors, victims, and mean streets. Paper presented

at the conference of the 'Western

Society of Criminology, Newport Beach, CA.Rossmo, D. K. (1998, June). Estimating criminal population sizes with cøpture-recapture

analysis. Paper presented at the Intemational Seminar on Environmental Criminology and

Crime Analysis, Barcelona, Spain.Rossmo, D. K. (1998, December). Case studies in geographic profiling. Paper presented at the

meeting of the Crime Mapping Research Center, Arlington, VA.Rossmo, D. K. (1999, February). Clues in crime maps: The Manhattan East Side Rapisl. Paper

presented at the conference of the Western Society of Criminology, Oakland, CA.Rossmo, D. K. (1999, June). Geographic profiling in cases of extended serial rape.Paper

presented at the International Seminar on Environmental Criminology and Crime Analysis,Pretoria, South Africa.

Rossmo, D. K. (1999, December). Environmental criminology: Criminal investigative praxis.Paper presented at the meeting of the Crime Mapping Research Center, Orlando, FL.

Rossmo, D. K. (2000, February). Charting a course through graduate school. Paper presented at

the conference of the Western Society of Criminology, Kona, HI.Rossmo, D. K. (2000, June). Geographic profiling and crime parsing. Paper presented at the

International Seminar on Environmental Criminology and Crime Analysis, Perth, Australia.

Rossmo, D. K. (2000, November). Routine activities andforaging theory: The influence ofmotivqtion on size of criminal hunting area.Paper presented at the meeting of the AmericanSociety of Criminology, San Francisco, CA.

Rossmo, D. K. (2001, February). Beyond "Round up the usual suspects": Geographic profiling,suspect prioritization, andforensic science. Paper presented at the meeting of the AmericanAcademy of Forensic Sciences, Seattle,'WA.

Rossmo, D. K. (2001, February). Geographic profiling, crime location sets, and child murder.Paper presented at the conference of the Westem Society of Criminology, Portland, OR.

Rossmo, D. K. (2001, June). An empirical evaluation of the geographic profiling program. Paperpresented at the International Seminar on Environmental Criminology and Crime Analysis,Liverpool, UK.

Rossmo, D. K. (2001, November). Evaluation of geographic profiling search strategies. Paperpresented at the meeting of the American Society of Criminology, Atlanta, GA.

Rossmo, D. K. (2002, November). Stranger rape and geo-demographics.Paper presented at themeeting of the American Society of Criminology, Chicago, IL.

Rossmo, D. K. (2002, December). Geographic profiling.Paper presented at the NationalConference of State Legislatures, Washington, DC.

Rossmo, D. K. (2003, February) . Stealth predator early warning methods updated: The PigFarm serial murder case.Paper presented at the conference of the Western Society ofCriminology, Vancouver, BC.

Rossmo, D. K. (2003, June). Some reflections on the journey to crime. Paper presented at theSeminar on Environmental Criminology and Crime Analysis, Cincinnati, OH.

Rossmo, D. K. (2003, August). Geographic profiling of predatory violent and sexual uime.Paper presented at the XIII World Congress of the Intemational Society for Criminology,Rio de Janerio, Brazil.

Rossmo, D. K. (2004, February). The who andwhere of stranger rape: Using geo-demographicsin offender profiling. Paper presented at the conference of the Western Society ofCriminology, Long Beach, CA.

Rossmo, D. K. (2004, March). The geo-demographics of stranger rape. Paper presented at themeeting of the Academy of Criminal Justice Sciences, Las Vegas, NV.

Rossmo, D. K. (2004, April). Criminal investigative failures. Paper presented at the NIJ CrimeMapping Research Conference, Boston, MA.

Rossmo, D. K. (2005, March). New developments in geographical profiling.Paper presented atThe Role of Psychology in Criminal Investigation - International Conference, Rome, Italy.

Rossmo, D. K. (2005, November). A journey-to-crime meta-analysis. Paper presented at themeeting of the American Society of Criminology, Toronto, ON.

Rossmo, D. K. (2006, February). Criminal investigative failures. Keynote luncheon speech,Western Society of Criminology, Seattle, WA.

Rossmo, D. K. (2006, February). Illegal border crossing population estimation. Paper presentedat the conference of the Westem Society of Criminology, Seattle, WA.

Rossmo, D. K. (2006, November). Geographic patterns and profiling of illegal uossings of thesouthern U.S. border. Paper presented at the meeting of the American Society ofCriminology, Los Angeles, CA.

Rossmo, D. K. (2007, February). A meta-analysis ofjourney-to-crime research. Paper presentedat the conference of the'Western Society of Criminology, Scottsdale, AZ.

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Rossmo, D. K. (2007, March). The error in error distance: Some conceptual and analyticproblems in crime mapping. Paper presented at the NIJ Crime Mapping ResearchConference, Pittsburgh, PA.

Rossmo, D. K. (2007, March). Illegal border crossings by American citizens. Paper presented atthe NIJ Crime Mapping Research Conference, Pittsburgh, PA.

Rossmo, D. K. (2007, April). Geographic patterns of illegal crossings of the southern U.S.

border. Paper presented at the Symposium on Illegal Immigration, Crime, and Public Policy,Phoenix, AZ.

Rossmo, D.K. (2007, May). Geographic profiling: Recent developments in property uimeinvestigation.Paper presented at UK National Crime Mapping Conference, London, UK.

Rossmo, D. K. (2007, June). Geographic profiling of stranger murder. Paper presented at theInternational Congress on Law and Mental Health, Padua, Italy.

Rossmo, D.K. (2007, July). Using geographic profilingþr volume crime detection. Paperpresented at the pre-ECCA Conference, London, UK.

Rossmo, D. K. (2008, October). Geospatial patterns of terrorist cells.Paper presented at themeeting of the Southwestem Association of Criminal Justice, Denver, CO.

Rossmo, D. K. (2008, November). Criminal investigative failures. Paper presented at themeeting of the American Society of Criminology, St. Louis, MO.

Rossmo, D. K. (2009, February). The geospatial structure of urban tercorist cells.Paperpresented at the conference of the Westem Society of Criminology, San Diego, CA.

Rossmo, D. K. (2009, March). Criminal investigative failures. Paper presented at the meeting ofthe Academy of Criminal Justice Sciences, Boston, MA.

Rossmo, D. K. (2009, July). Geographic profiling. Paper presented at the pre-ECCA Conference,Brasilia, Brazil.

Rossmo, D. K. (2009, July). Criminal hunting paths - An analysis of offender GPS track data.Paper presented at the Seminar on Environmental Criminology and Crime Analysis,Brasilia, Brazil.

Rossmo, D. K. (2009, November). Probability eruors in criminal investigative failures. Paperpresented at the meeting of the American Society of Criminology, Philadelphia, PA.

Rossmo, D. K. (2010, February). Geographic Profiling. Workshop presented at the meeting ofthe Academy of Criminal Justice Science, San Diego, CA.

Rossmo, D. K. (2010, June). The Chqndra Levy Case: Afailure in homicide investigation.Paperpresented at the meeting of the Homicide Research Working Group, Baltimore, MD.

Rossmo, D. K. (2010, July). Geographic profiling: Border security and countertenorism. Paperpresented at the post-ECCA Conference, Brisbane, Australia.

Rossmo, D. K. (2010, July). Military applications of environmental uiminology and crimeanalysis. Paper presented at the Seminar on Environmental Criminology and CrimeAnalysis, Brisbane, Australia.

Rossmo, D. K. (2010, October). Criminal investigative failures and the Missing Women / PigFarm serial murder case. Paper presented at the meeting of the Southwestern Association ofCriminal Justice, Little Rock, AR.

Rossmo, D. K. (2010, November). The deconstruction of a crime journey.Paper presented at themeeting of the American Society of Criminology, San Francisco, CA.

Rossmo, D. K. (2011, February). An Analysis of the øiminal investigative failure of the MissingIlomen/Pig Farm Serial Murder Case. Paper presented at the conference of the WesternSociety of Criminology, Vancouver, BC.

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Rossmo, D. K. (2011, March). Criminal investigative foilures in the Missing Women/Pig FarmSerial Murder Case. Paper presented at the meeting of the Academy of Criminal JusticeScience, Toronto, ON.

Rossmo, D. K. (2010, November). The deconstruction of a crime journey.Paper presented at themeeting of the American Society of Criminology, San Francisco, CA.

Rossmo, D. K., Allen, J., & Hom, P. (2011, October). The geography of terrorism and theMadrid Train Bombings. Paper presented at the NIJ Crime Mapping Research Conference,Miami, FL.

Rossmo, D.K., &Baeza, J. J. (1998, November). The Upper East Side Serial Rapist: A casestudy in geographic profiling. Paper presented at the meeting of the American Society ofCriminology, Washington, DC.

Rossmo, D. K., & Carreon, J . (2009, October). Geospatial patterns of reported cryptid sightingsin East Texas. Paper presented at the meeting of the Southwestem Association of CriminalJustice, Laredo, TX.

Rossmo, D. K., Davies, A., & Warraker, B. (2000, July). Beyond " Round up the usual suspects ":Behavioural science, physical evidence, and suspect prioritization in Operation Lynx.Paperpresented at the meeting of the Forensic Science Services, York, UK.

Rossmo, D.K., &.Filipuzzi, N. (2012, February). An environmental criminologt analysis of aprison halfway house location. Paper presented at the conference of the Western Society ofCriminology, Newport Beach, CA.

Rossmo, D. K., & Glackman, W. (1991, November). Police organizational surveys: Labour-Management diagnostic tools. Paper presented at the meeting of the American Society ofCriminology, San Francisco, CA.

Rossmo, D.K., Hammerschlag, N., & Martin, R. A. (2007, July). Environmental criminologyand optimal þraging models: Spatial analysis and geographic profiling of white sharkpredation. Paper presented at the Seminar on Environmental Criminology and CrimeAnalysis, London, UK.

Rossmo, D. K., & Harries, K. (2009, August). The geospatial structure of terrorist cells. Paperpresented at the NIJ Crime Mapping Research Conference, New Orleans, LA.

Rossmo, D. K., Hanies, K., &. Allen, J. (2011, November). The terror of place: Geoprofiling andthe Madrid Train Bombings. Paper presented at the meeting of the American Society ofCriminology,'Washington, DC.

Rossmo, D.K., Harries, K., Allen, J., & Stafford, M. (2011, July). The geography of tetorismand the Madrid Train Bombings. Paper presented at the Seminar on EnvironmentalCriminology and Crime Analysis, Durban, South Africa.

Rossmo, D. K., Harries, K., McGarrell, E., Teymur, S., & Thurman, Q. (2008, March). Thegeospatial structure of terrorist cells. Paper presented at the Seminar on EnvironmentalCriminology and Crime Analysis I,Izmir, Turkey.

Rossmo, D. K., Harries, K., McGarrell, E., & Thurman, Q. C. (2007, June). The geography ofterrorist qttaclrs in Turkey. Paper presented at the Conference on Democracy and GlobalSecurity, Istanbul, Turkey.

Rossmo, D.K., Harries, K., McGarrell, E., & Thurman, Q. (2008, July). The geospatial structureof teruorist cells.Paper presented at the Seminar on Environmental Criminology and CrimeAnalysis II, Anchorage, AK.

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Rossmo, D. K., Jamieson, J. D., & Thurman, Q. C. (2005, February). Geographic patterns andprofiling of illegal land border crossings. Paper presented at the conference of the WestemSociety of Criminology, Honolulu, HI.

Rossmo, D. K., & Kringen, A. L. (2012, June). Spatial and temporal patterns in serial crime.Paper presented at the Seminar on Environmental Criminology and Crime Analysis, Stavern,Norway.

Rossmo, D. K., &,Leahy, S. (2004, November). Using research to assist the police investigationof serious crime . Paper presented at the meeting of the American Society of Criminology,Atlanta, GA.

Rossmo, D. K., Lu, Y., &,Blair, J. P. (2009, August). An analysis of criminal search paths usingGPS track data. Paper presented at the NIJ Crime Mapping Research Conference, NewOrleans, LA.

Rossmo, D.K., &Pagaling-Hagan, S. (2008, February). The Zodiac Killer Case: Historicprofiling of an unsolved serial murder mystery. Paper presented at the meeting of the

Vy'estern Society of Criminology, Sacramento, CA.Rossmo, D. K., Pollock, J., & Blair, J. P. (2008, March). Criminal hunting paths: An analysis of

spatial behavior of recidivisls. Paper presented at the meeting of the Academy of CriminalJustice Sciences, Cincinnati, OH.

Rossmo, D. K., & Quinet, K. (2004,November). Spatial and temporal patterns of serial murderin the United States. Paper presented at the meeting of the American Society ofCriminology, Atlanta, GA.

Rossmo, D. K., & Thurman, Q. C. (2005, June). Geographic patterns and profiling of illegalland border crossings. Paper presented at the Conference on Democracy and GlobalSecurity, Istanbul, Turkey.

Rossmo, D. K., & Thurman, Q. C. (2005, September). Geographic patterns and profiling ofillegøl land border crossings. Paper presented at the Crime Mapping Research Conference,Savannah, GA.

Rossmo, D. K., & Thurman, Q. C. (2007, October). The geospatial structure of terrorism.Paperpresented at the meeting of the Southwestern Academy of Criminal Justice, Corpus Christi,TX.

Rossmo, D.K., Thurman, Q. C., & Jamison, J.D. (2004, October). Geographic patterns andprofiling of illegal uossings of the Texas border. Paper presented at the meeting of theSouthwestern Academy of Criminal Justice, Houston, TX.

Rossmo, D.K., Thurman, Q. C., & Jamison, J.D. (2005, July). Geographic patterns andprofiling of illegal land border uossings. Paper presented at the Seminar on EnvironmentalCriminology and Crime Analysis, Santiago, Chile.

Rossmo, D. K., Thurman, Q. C., & Jamison, J. D. (2006, July). Geographic profiling of illegalland border crossings; Final results. Paper presented at the Seminar on EnvironmentalCriminology and Crime Analysis, Vancouver, BC.

Rossmo, D. K., Thurman, Q. C., & Jamison, J. D. (2007, March). Border control policy:Population, permeability, and displacement.Paper presented at the meeting of the Academyof Criminal Justice Sciences, Seattle, WA.

Schmitz, P. M. U., Rossmo, D. K., de Jong, T., & Cooper, A. (2007, March). Determiningcriminal activity spqce using mobile phone technology.Paper presented at the NIJ CrimeMapping Research Conference, Pittsburgh, PA.

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Invited Presentations (Selected)Universidade Fernando Pessoa (Porto, Portugal: Iuly 2012)Austin Regional Intelligence Center (ARIC) (Austin, TX; September 2011)Austin/Travis County Health Department (Austin, TX; August2}Il)Kansas Bureau of Investigation (Topeka, KS; January 20ll)ESzu European Conference, with The Netherlands Ministry of Defence (Delft, The Netherlands;

September 2010)Colorado Association of Sex Crimes Investigators (Snowmass, CO; September 2010)California Police Offlrcers Association (Los Angeles, CA; May 2010)Danish National Police, Organized Crime Unit, and Danish Security and Intelligence Service

(Copenhagen, Denmark; April 20 1 0)Instituto Superior da Maia (Porto, Portugal; April2010)University of Texas-Austin, Geography Department (Austin, TX; April2010)Oklahoma State Bureau of Investigation (Edmond, OK; March 2010)The Netherlands Ministry of Defence (Epe, The Netherlands, March 2010)Vancouver Police Department, Major Crimes Section (Vancouver, BC; February 2010)Minneapolis Bureau of Criminal Apprehension (Minneapolis, MN; January 2010)Police Academy, Justice Institute of British Columbia (I.{ew Westminster, BC; October 2009,

November 2004)Simon Fraser University, School of Criminology (Burnaby, BC; October 2009)Wrongful Convictions Expert Panel, International Association of Chiefs of Police (IACP)

Annual Meeting (Denver, CO; October 2009)Association of State Criminal Investigative Agencies (Albuquerque, NM; September 2009)American Psychological Association (APA), invited plenary speaker (Toronto, ON; August

200e)University of Texas-Austin, Mathematics Department (Austin, TX; October 2008)International Crime Science Conference (London, UK; July 2008)National Summer Institute for Statistical & GIS Analysis of Crime & Justice Data, University of

Regina (Regina, SK; June 2008, June 2006, June 2005).Radford University (Radford, VA; March 2008).Califomia Association of Crime Laboratory Directors (Sacramento, CA; November 2007)International Association of Law Enforcement Intelligence Analysts (Vancouver, BC; April

2007)Georgia Bureau of Investigation (Forsyth, GA; March 2007)Los Angeles Police Department (Los Angeles, CA; December 2006)Chinese Ministry of State Security University (Beijing, Hangzhou, and Shanghai, China;

September 2006)International Association of Women Police (Saskatoon, SK; September 2006)Metropolitan Police Department (Washington, DC; March 2006)Texas State University, Anthropology Department, Body Recovery Conference (San Marcos,

TX; March 2006)Canadian Information Processing Society (CIPS) (Edmonton, AB; November 2005)Texas Rangers (Austin, TX; September 2005)Federal Bureau of Investigation, Serial Murder Symposium (San Antonio, TX; August 2005)Université de Montréal, École de criminologie (Montréal, QC; June 2005)Army Topographical Engineering Center (TEC) (Fort Belvoir, VA; March 2005)

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International Crime Analysis Association Investigative Psychology Conference (Rome, Italy;March 2005)

California Robbery Investigators Association Conference (Las Vegas, NV; February 2005)University of Virginia Psychology Department (Charlottesville, VA; October 2004)Forensics Department, British Columbia Institute of Technology (Vancouver, BC; June 2004)National Institute of JusticeÆederal Bureau of Investigation/American Psychology Association,

The Nature and Influence of Intuition in Law Enforcement (Arlington, VA; June 2004)National Technology Alliance, Pentagon J3DDIO, and National Geospatial-Intelligence Agency

(Arlington, VA; June 2004)University of Texas College of Engineering (Austin, TX; February 2004)FBI Major Crime Training Seminar (Baton Rouge, LA; December 2003)Alberta Crown Attorney's Association Meeting (Banff, AB; September 2003)Greater Austin Crime Commission (Austin, TX; August2003)

Joumal Editorial BoardsHomicide Studi es ( 1 997-present)International Journal of Police Strategies & Management (2011-present)Inv e s t i g at iv e P s y c h o I o 9,, and Offe n d e r P r ofi I in g (20 07 -20 I 0)

Professional MembershipsIACP Advisory Committee for Police Investigation Operations (1997-present)Canadian Association of Violent Crime Analysts, Vice-President (1997-2002)Westem Society of Criminology, Executive Counselor (1999-2002)American Society of CriminologyAcademy of Criminal Justice SciencesHomicide Research Working GroupInternational Association of Law Enforcement Intelligence AnalystsIntemational Association of Crime Analysts (1997-2010)International Criminal Investigative Analysis FellowshipSouth Carolina Research Authority Integrated Solutions Group Advisory Board (2004-2009)Canadian Police Association, Executive Vice-President and Chief Financial Ofhcer (1995-1997)Vancouver Police Union, Vice-President and Director (1988-1994)

LegalRecognized in the Superior Court of Ontario as an expert in "the geography of crime, the hunting

patterns ofserial offenders, and appropriate investigative strategies" (1997)Recognized by the British Columbia Missing'Women Commission of Inquiry as an expert in

"serial murder and criminal investigations" (2012)Testified at the Missing Women Commission of Inquiry (Vancouver, BC; January and May 2012)Testif,red at the Commission of Inquiry into the Wrongful Conviction of David Milgaard

(Saskatoon, SK;2006)

ConsultanciesSunalta/Scarboro Community Associations Halfway House Location Evaluation (2007)Zodiac Killer geographic profile, Phoenix Pictures (2007)Policing in British Columbia Commission of Inquiry community policing research project (1994)

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David Milgaard murder conviction independent review (1992)Japan-Canada comparative community policing research proj ect ( 1 99 1 )

Community ServiceCommissioner and Vice Chairman, Austin Public Safety Commission, and Chair, Police

Subcommittee (2009-present)Geographic profiling assistance for major crime investigations provided to international and

national police agenciesCold case review of the 1975 Sheryl Norris homicide for the San Marcos Police DepartmentCase review of the John Jerome V/hite wrongful conviction for the Georgia Bureau of

InvestigationCase review of the Benjamin LaGuer conviction for State Representative, Commonwealth of

Massachusetts

Media Interviews (Selected)ABC20120, NightlineAl JazeeraAssociated PressAustin American- StatesmanBBCBlue Line MagazineCanadian PressCBCCKNWCNNCTV V/5Dallas Morning NewsDateline NBCDe Limburger (The Netherlands)Der Spiegel (German)Financial PostGeoV/orldGlobe and MailIl Tempo (Italy;Journal de MontréalLondon Times (UK)Maclean'sNational PostNew Zealand RadioPopular ScienceReader's DigestRegina Leader-PostSan Antonio Express-NewsUSA TodayVancouver SunWashington Post

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