Rory  Smith,  Ph.D.

California  Institute  of  Technology  •  1200  E.  California  Blvd  •  Pasadena,  CA•  91125  •  MC  100-­‐36    •  747-­‐238-­‐8603    e-­‐mail  roryjesmith@gmail.com    •  linkedin  https://www.linkedin.com/in/roryjsmith  

 SKILLS   Signal  Processing     Data  Analysis     Bayesian  Inference    

Data  Compression     Stochastic  Sampling   Mathematical  Modeling      Approximation  Theory     Parallel  Computing   Multi-­‐parameter  Interpolation  Python       C/C++       Scalable  Algorithms      LaTeX       (non)linear  regression     Scientific/Technical  Writing    

  EDUCATION   Ph.D.  Physics  (2013)     University  of  Birmingham,  U.K.     MSci.  (Hons)  Theoretical  Physics,  Class  1  (2009)     University  of  Birmingham,  U.K.  

 EXPERIENCE    

California  Institute  of  Technology  Senior  postdoctoral  researcher  in  physics  (Current)  and  postdoctoral  researcher  in  physics  (2013-­‐2016)    

! I  am  a  member  of  the  data  science  group  in  the  LIGO  laboratory  at  Caltech.  My  research  is  at  the  interface  of  mathematical  modeling,  the  development  of  low-­‐latency  and  scalable  Bayesian  inference  algorithms,  signal  processing  and  machine  learning.  For  example,  I  am:    • Leading  an  effort  within  the  international  collaboration  LIGO  to  design  and  implement  

scalable,  low-­‐latency  matched  filtering  and  Monte-­‐Carlo  inference  algorithms  to  extract  astronomical  information  from  noisy  time-­‐series  data.  My  work  has  improved  the  efficiency  of  Monte  Carlo  sampling  algorithms  for  inference  by  several  orders  of  magnitude,  increasing  the  feasibility  of  making  astronomical  measurements  using  LIGO  data.  [http://journals.aps.org/prd/abstract/10.1103/PhysRevD.94.044031]    

 • Designing  and  implementing  algorithms  to  improve  the  quality  of  LIGO  data  –  and  

astronomical  measurements  using  LIGO  data  –  through  linear  and  non-­‐linear  regression  of  noise  sources.      

• Producing  tools  to  simulate  realistic  interferometers  in  near  real-­‐time  for  experimental  design  and  commissioning.  [http://iopscience.iop.org/article/10.1088/2040-­‐8978/18/2/025604]  

   

! The  links  between  these  areas  are  a  set  of  techniques  known  collectively  as  “reduced  order  modeling”.  These  techniques  include,  but  are  not  limited  to,  finding  highly  compressed  expressions  for  likelihood  functions  that  arise  in  Bayesian  inference,  which  utilize  multi-­‐parameter  interpolation  with  sparse  and  scattered  data.  

 ! I  am  a  contributor  to  two  software  libraries  used  by  the  LIGO  Scientific  Collaboration:  The  

inference  libraries  in  LIGO’s  data  analysis  software  suite  (LALsuite),  and  the  open  source  interferometer  simulation  software  Finesse.  These  libraries  are  routinely  used  by  a  collaboration  of  several  hundred  people.  

       FASTech  LLC  Co-­‐founder  and  consultant  in  data  science  (2014-­‐2015)  

 • I  co-­‐founded  FASTech  (Fast  Analysis  and  Simulation  Technologies)  LLC,  a  startup  based  in  San  

Diego,  to  explore  commercial  applications  of  reduced  order  modeling  and  signal  processing/inference  techniques  that  I  developed  as  a  postdoc  at  Caltech.  Such  applications  include  data  compression,  efficient  inference  on  large  data  sets,  and  simulations  of  stochastic  physical  processes.  As  a  consultant,  I  help  draft  a  SBIR  (Small  Business  Innovation  Research)  grant  proposals  for  to  develop  simulations  of  jet  flows  using  reduced  order  modeling.  In  addition,  we  also  explored  and  formed  strategic  partnerships  with  DAC  (Decisive  Analytics  Corporation)  and  FiskeTech,  two  companies  specializing  in  predictive  analytics  for  defense.  

 University  of  Birmingham  Ph.D.  in  physics  (2009-­‐2013)  

 ! My  thesis  focused  on  efficient  methods  to  detect  astronomical  signals  and  perform  inference  on  

those  signals  in  data  from  the  LIGO  experiment.  My  thesis  received  an  honorable  mention  in  a  PhD  thesis  award  from  an  international  committee  of  physicists  and  astronomers.  [https://gwic.ligo.org/thesisprize/2013/]  

! I  was  also  the  recipient  of  a  (competitive)  Canadian  visiting  graduate  fellowship  award  at  Perimeter  Institute  for  Theoretical  Physics  (2012)  where  I  spent  six  months  working  in  the  gravitational  physics  group  on  data  analysis  techniques  for  the  LIGO  experiment.  

 

Publications  and  Presentations    

An  up-­‐to-­‐date  list  of  my  publications  can  be  found  on  Google  Scholar:  https://scholar.google.co.uk/citations?user=db687GsAAAAJ&hl=en&oi=ao    

 

Caltech  •  1200  E.  California  Blvd  •  Pasadena,  CA  •  91125  •  MC  100-­‐36    •  e-­‐mail  roryjesmith@gmail.com