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CURRICULUM VITAE Jun (Luke) Huan, Ph.D.

Professor Phone: 1-785-864-2375 Department of Electrical Engineering and Computer Science Fax: 1-785-864-3226 University of Kansas E-mail: jhuan@ku.edu Lawrence, KS 66047, USA http://ittc.ku.edu/~jhuan

RESEARCH INTEREST Machine Learning and Data Mining: model selection, geometric and algebraic approaches in statistical inference, approximate inference, Bayesian nonparametrics, kernel machines, deep learning Big Data Analytics: GPGPU computing, big graph analytics Bio, Biomedical and Health Informatics: computational chemical biology, pharmacogenomics, mobile health, population genetics and human genetics

EDUCATION Ph.D., Computer Science, University of North Carolina at Chapel Hill Graduate Certificate, Bioinformatics and Computational Biology, UNC-CH M.S., Computer Science, Oklahoma State University

WORK EXPERIENCE 2016 – Present Program Director, Division of Information and Intelligent Systems, Directorate

for Computer and Information Science and Engineering, US National Science Foundation (started as an Expert of CISE/IIS in 2015). Managing programs: IIS core, Big Data, PIRE.

2016 – Present Director, Computational Chemical Biology Core, KU COBRE Center on Chemical Biology of Infectious Disease

2014 – Present Professor (with tenure), Department of Electrical Engineering and Computer Science Professor (by courtesy), Bioengineering Program Professor (by courtesy), Computational Biology Program Professor (by courtesy), KU Surveillance Studies Research Center Investigator, Department of Veterans Affairs Eastern Kansas Health Care System Visiting Professor, Big Data and Machine Learning Research Center, Peking University

2013 - 2013 Visiting Professor, Computational Chemistry Group, GlaxoSmithKline plc. (sabbatical leave)

2012 – Present Director, Data Science and Computational Life Sciences Laboratory, Information and Telecommunication Technology Center, University of Kansas

2012 – Present Director, the Bioinformatics Track, Bioengineering Program, University of Kansas

2008 – 2014 Director, Cheminformatics Core, KU NIH Specialized Chemistry Center

2011 – 2014 Associate Professor, Department of Electrical Engineering and Computer Science, Associate Professor (by courtesy), Bioengineering Program, Bioinformatics Program

2006 – 2011 Assistant Professor, Department of Electrical Engineering and Computer Science, Assistant Professor (by courtesy), Bioengineering Program, Bioinformatics Program

2004 Intern, GlaxoSmithKline plc. Research Triangle Park, NC

2001-2006 Research Assistant, Computer Science Department, University of North Carolina, Chapel Hill, NC

2000-2001 Software Designer, Nortel Networks, Richardson, TX

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1999 Summer Intern, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL

HONORS & AWARDS • Miller Scholar, University of Kansas School of Engineering, 2014 • Best Student Paper Award, the IEEE International Conference on Data Mining, Vancouver,

Canada, December 2011, with the graduate student Hongliang Fei • Bellows Scholar, University of Kansas School of Engineering, 2011 • Miller Scholar, University of Kansas School of Engineering, 2010 • Best Paper Award (Runner-up), the 18th ACM Conference on Information and Knowledge

Management, Hong Kong, China, November 2009 • Faculty Early Career Development (CAREER) Award, National Science Foundation, 2009

INVITED TALKS

• Jun Huan, “Deep-Learning: Investigating feed-forward Deep Neural Networks hyper-parameters and Comparison of Performance to Shallow Methods for Modeling Bioactivity Data”, Invited talk, National Center for Advancing Translational Sciences (NCATS), NIH, June 2016

• Jun Huan, “Large-scale Predictive Analytics, insights from Structuralism”, Keynote Speech, the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Open House, Phoenix, AZ, February 2016

• Jun Huan, “Large-scale Predictive Analytics”, Invited Talk, International Conference in Big Data and Information Analytics, Xi’An, China, October 2015

• Jun Huan, “Big Data Research at the University of Kansas”, Invited Talk and Panelist, Big Data Summit III, the Great Plains Network, Kansas City, May 2015

• Jun Huan, “Large-scale Heterogeneous Learning in Big Data Analytics”, Invited Talk, University of Arkansas, Fayetteville, AR, April 2015

• Jun Huan, “Large-scale Heterogeneous Learning in Big Data Analytics”, Invited Talk, University of Missouri, Kansas City, Missouri, March 2015

• Jun Huan, “Large-scale Heterogeneous Learning in Big Data Analytics”, Tutorial, IEEE International Conference on Big Data, Washington DC, October 2014

• Jun Huan, “Large-scale Multi-task learning”, Keynote speech, Heterogeneous Machine Learning Workshop, in conjunction with the SIAM International Conference on Data Mining, Philadelphia, PA, April 2014

• Jun Huan, “Mining and Learning with Big Graph Data”, Invited talk, the Electrical and Computer Engineering Department, Iowa State University, Iowa, February 2014

• Jun Huan, “Big Data Analytics in Computational Chemical Biology and Drug Discovery”, invited talk, 2013 IEEE International Conference on Bioinformatics and Biomedicine, Shanghai, China, December 2013

• Jun Huan, “Mining and Learning with Graph Data and Their Applications in Bioinformatics”, tutorial, 2013 IEEE International Conference on Bioinformatics and Biomedicine, Shanghai, China, December 2013

• Jun Huan, “Machine Learning in Big Graph Data”, invited talk, School of Computer Science, Fudan University, Shanghai, China, July 2013

• Jun Huan, “Big Data Analytics in Computational Chemical Biology”, invited talk, College of Life Science, Peking University, Beijing, China, June 2013

• Jun Huan, “Machine Learning in Big Graph Data”, invited talk, Computer and Information Sciences Department, Temple University, Philadelphia, PE, April 2013

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• Jun Huan, “Characterizing the Diversity and Biological Relevance of the MLPCN Assay Manifold and Screening Set”, Division of Chemical Information, the 245th ACS National Meeting, New Orleans, LA, April 2013.

• Jun Huan, “Machine Learning in Big Chemical Biology Data” invited talk, GlaxoSmithKline plc, Collegeville, Philadelphia, PE, March 2013

• Jun Huan, “Machine Learning in Big Graph Data”, invited talk, College of Information Science, Drexel University, Philadelphia, PE, March 2013

• Jun Huan, “Big Data in Drug Discovery: Opportunities and Challenges”, Tutorial, the 2012 IEEE International Conference on Bioinformatics and Biomedicine, (BIBM), Philadelphia, PE, October 2012

• Jun Huan, “PubChem Mining - From Small Molecule to Structures and Bioactivity”, Short Course, Cambridge Health Institute Structured-based Drug Design conference, Cambridge, MA, June 2012

• Jun Huan, “Knowledge Discovery in Academic-Based Drug Design: New Opportunities and Challenges”, Tutorial, The 2nd ACM International Conference on Bioinformatics and Computational Biology (SIGBCB), Chicago, IL, August 2011

• Jun Huan, “Knowledge Discovery in Academic-Based Drug Design: New Opportunities and Challenges”, Tutorial, The 10th IEEE International Conference on Data Mining, Sydney, Australia, December 2010

• Jun Huan, “Chemical Genomics and Systems Biology”, College of Life Science, Sichuan University, Chengdu, China, November 2009

• Jun Huan, “Learning from Multiple Data Sources and Its Applications in Chemical Toxicity Prediction”, The First ToxCastTM Data Analysis Summit, Hosted by National Center for Computational Toxicology, Environmental Protection Agency (EPA), Research Triangle Park, NC, May 2009

• Jun Huan and Deepak Bandyopadhyay, “Geometric Pattern Mining and Its Applications in Protein Structure and Function Analysis”, Tutorial, IEEE international Conference on Bioinformatics and Biomedicine (BIBM'08), Philadelphia, PA, November 2008

• Jun Huan, “Protein Function Prediction: the Data Mining Approach”, Department of Molecular and Integrative Physiology, the University of Kansas Medical Center, March 2008

• Jun Huan, “Graph Kernel Function for Microarray Analysis”, The MicroArray Quality Control (MAQC) Project: An FDA-led Effort Toward Personalized Medicine, Federal Food and Drug Administration (FDA), Washing DC, March 2008

• Jun Huan, “Analyzing Biomolecules with Data Mining Approaches”, Department of Electronic Engineering and Computer Science, Case Western Reserve University, April 2007

• Jun Huan, “Discovering Patterns in Families of Protein Structures”, School of Computer Science, University of Waterloo, April 2006

• Jun Huan, “Mining Family-Specific Residue-Packing Patterns from Protein Structure Graphs”, Department of Computer Science, Duke University, November 2004

RESEARCH SUPPORTS Agency Title Dates Total Award

As Principe Investigator (total support ~6M)

1 NSF 1624071 Intergovernmental Personnel Act Assignment 1/16-1/17 $223,000

2 NSF IIS 1513324

Subpopulations for the Intervention and

1/15-12/16 $189,000

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Prevention of Large-scale Ebola Virus Spreading

3 NSF CNS 1337899

MRI: Acquisition of Computing Equipment for Supporting Data-intensive Bioinformatics Research at the University of Kansas

9/13-8/16 $714,000

4 University of Kansas

Establishing a Multi-Disciplinary Data Science Research Team at the University of Kansas

6/13-5/15 $282,000

5 NSF CAREER

Award IIS: 0845951

CAREER: Mining Genome-wide Chemical-Structure Activity Relationships in Emergent Chemical Genomics Databases

08/09 – 06/14 $500,000

6 NIH

G20 RR031125

KU Bioinformatics Computing Facility Core Renovation and Improvement*

07/10 – 07/12 $4,658,000

7 NIH,

Subcontract from R01 GM868665

Protein Structure/Function Specific Packing Motifs

09/06 – 09/10 $51,000

8 US Department of Transportation

Development of Freight Analysis Framework for the Sustainable Economic Growth

07/07 – 07/08 $50,000

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NIH, through Kansas IDeA Network of Biomedical Research

Excellence P20 RR016475

Cellular Pathogen Gene Identification via Graph Database Mining

04/07 – 04/08 $44,000

10 University of Kansas

Data-Driven Metabolic Network Study for the Next Generation Bioenergy

Data Mining in Predicting Function of Biomolecules

06/10 –06/11

06/08 – 06/09

$9,600

$8,000

As Co-Principle Investigator or Co-Investigator (total support ~$50M)

11 NIH

1P20GM113117- COBRE: Chemical Biology 09/16-08/21 $12,000,000 PI: Thomas

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of Infectious Disease. My role: Leader of the Core C: Computational Chemical Biology.

Prisinzano

12 NSF IIS 1550320

BD Hubs: MIDWEST: SEEDCorn: Sustainable Enabling Environment for Data Collaboration (My role: senior personnel and Steer Committee Member)

09/15-09/18 $1,500,000 PI: Edward

Seidel (UIUC)

13 NSF SMA 1547464

Collaborative Research: EAGER: Automating HERD Reporting Using Machine Learning and Administrative Data

09/15-08/17 $200,000

PI: Rodolfo Torres

14 NSF CNS 1422206

Privacy Protection in Social Networks: Bridging the Gap Between User Perception and Privacy Enforcement

09/14-08/17 $220,000

PI: Bo Luo

15 NIH

P20 GM103638 KU COBRE Center on Molecular Analysis of Disease Pathways

08/12-07/17 $12,000,000

PI: Susan Lunte

16 NSF OIA 1028098

CDI-Type II: Computational Methods to Enable an Invertebrate Paleontology Knowledgebase

08/10 – 07/14 $1,500,000

PI: Xuewen Chen

17 NIH

U54 HG005031 Kansas Special Chemistry Center 07/08 – 07/14

$21,200,000 PI: Jeff Aubé

18 NSF

CNS 0821625

MRI: Acquisition of an Advanced Computational Infrastructure for Modeling Biological Systems

07/08 – 07/11 $300,000

PI: Joseph Evans

19 Kansas

Department of Transportation

Development of an Interactive E-Training Program for Work

07/08 – 12/09 $60,000

PI: Bai Yong

20 Iowa Department

Transportation

Smart Zone Deployment Initiative: Development of a Work Zone training program

07/08 – 06/09 $30,000

PI: Bai Yong

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Office of Naval Research

N00014-07-1-1042

SensorNet - Rail Sensor Testbed - Active Agents in Containers for Transport Chain Security

06/07 – 06/10 $1,217,000 PI: Joseph

Evans

22 NIH, through KU Center for

Chemical

Strategic chemical synthesis guidance via data mining

02/07 – 02/09 $100,000

PI: Gerald Lushington

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Methodology and Library

Development P50 GM069663

*Steven Warren, KU vice chancellor for research and graduate studies, was the nominal PI on the grant. I served as the leading co-PI and led a team of over 12 scientists and IT professionals across the KU campus to secure the G20 grant.

STUDENTS SUPERVISION Ph.D. Students in progress:

1. Sai Nivedita Chandrasekaran 2. Chao Lan 3. Xiaoli Li 4. Joseph St. Amand

Graduated Ph.D. Students: 5. Aaron Smalter, Ph.D. in Computer Science, “Genome-Wide Protein-Chemical Interaction

Prediction”, the University of Kansas, July 2011 6. Xiaotong Lin, Ph.D. in Computer Science, “Bayesian Network Learning and Applications in

Bioinformatics”, the University of Kansas, July 2012 7. Jintao Zhang, Ph.D. in Bioinformatics, “Drug Adverse Reaction Prediction with Multi-view

Learning”, the University of Kansas, August 2012 8. Brian Quanz (NSF Graduate Research Fellow, 2009-2012), Ph.D. in Computer Science,

“Learning with Low-Quality Data: Multi-View Semi-Supervised Learning with Missing Views”, the University of Kansas, August 2012

9. Hongliang Fei, Ph.D. in Computer Science, “Learning with Structured Data: a Regularization Based Approach”, the University of Kansas, October 2012

10. Yi Jia, Ph.D. in Computer Science, “Online Spectral Clustering on Network Streams”, the University of Kansas, December 2012

11. Meenakshi Mishra, PH. D., “Task Relationship Modeling in Lifelong Multitask Learning”, The University of Kansas, August 2015

Graduated M.S. Students: 1. Abhinav Peddi, M.S. in Computer Science, “Development of Human Pose Analyzing

Algorithms for the Determination of Construction Productivity in Real-time”, Master Thesis, the University of Kansas, May 2008

2. Fei Seak Lei, M.S. in Computer Science, “Toward Efficient Active-Site Based Protein Functional Annotation”, Master Thesis, the University of Kansas, May 2008

3. Xiaohong Wang, M.S. in Computer Science, “G-hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases”, Master Thesis, the University of Kansas, May 2009

4. Avindra Fernando, M.S. in Computer Science, “Identification of Transposable Elements of the Giant Panda (Ailuropoda Melanoleuca) Genome”, Master Project, the University of Kansas, May 2012

5. Ruoyi Jiang, M.S. in Computer Science, “A Family of Joint Sparse PCA Algorithms for Anomaly Localization in Network Data Streams”, Master Thesis, the University of Kansas, April 2012

6. Yuanliang Meng, M.S. in Computer Science, “Building an Intelligent Knowledgebase of Brachiopod Paleontology”, Master Thesis, the University of Kansas, August 2012, co-advised with Brian Potetz

7. Gowtham Kumar Golla, M.S. in Computer Science, “Developing Novel Machine Learning Algorithms to Improve Sedentary Assessment for Youth Health Enhancement”, Master Project, the University of Kansas, May 2016

8. Sreenivas Kumar Vekapu, M.S. in Computer Science, “Chemocaffe: A platform providing

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Deep Learning as a service to cheminformatics researchers”, Master Project, the University of Kansas, June 2016

Ph.D. Dissertation Committee Memberships: 9. Sandhya Beldona, Ph.D. in Computer Science, 2008 10. Mei Liu, Ph.D. in Computer Science, “Knowledge-guided Inference of Domain-Domain

Interactions from Incomplete Protein-protein Interaction Networks”, the University of Kansas, May 2009

11. Bing Han, Ph.D. in Computer Science, “Detecting Cancer-Related Genes and Gene-Gene Interactions by Machine Learning Methods”, the University of Kansas, December 2011

12. Alexander Senf, Ph.D. in Computer Science, “A Machine Learning Approach to Query Time-Series Microarray Data Sets for Functionally Related Genes Using Hidden Markov Models”, the University of Kansas, January 2011

13. Said Bleik, Ph.D. in Computer Science, “Concept Graphs: Applications to Biomedical Text Categorization and Concept Extraction”, the New Jersey Institute of Technology, March 2013

14. Jong Cheol Jeong, Ph.D. in Bioengineering, “New Methodology for Measuring Semantic Functional Similarity Based on Bidirectional Integration”, the University of Kansas, April 2013

15. Martin Kuehnhausen, Ph.D. in Computer Science, “A Framework for Knowledge Derivation Incorporating Trust and Quality of Data”, the University of Kansas, August 2013

16. Meeyoung Park, Ph.D. in Computer Science, “HealthTrust: Assessing the Trustworthiness of Healthcare Information on the Internet”, the University of Kansas, October 2013

17. Brock Charles Roughton, Ph.D. in Chemical Engineering, “Development of Computer-Aided Molecular Design Methods for Bioengineering Applications”, the University of Kansas, December 2013

18. Ashwin Shikaripur Nadig, Ph.D. in Computer Science, “Statistical Approaches to Inferring Object Shape From Single Images”, the University of Kansas, May 2014

19. Yuhao Yang, Ph.D. in Computer Science, “Protecting attributes and contents in online social networks”, the University of Kansas, August 2014

20. Justin Metcalf, Ph.D. in Electrical Engineering, “Signal Processing for Non-Gaussian Statistics: Clutter Distribution Identification and Adaptive Threshold Estimation”, the University of Kansas, March 2015

21. Guannan Hu, Ph.D. in Mathematics, “Fractional diffusion in Gaussian noisy environment”, the University of Kansas, August 2015

M.S. Thesis/Project Committee Memberships: 22. Vandana Samala, M.S. in Computer Science, 2007 23. Theertham Bhargav, M.S. in Computer Science, 2007 24. Kannan Chandrasekaran, M.S. in Computer Science, 2007 25. Supriya Vasudevan, M.S. in Computer Science, 2008 26. Wasikowski (KU EECS) 2009 27. Ashwini Shikaripur Nadig, M.S. in Computer Science, 2010 28. Jong Cheol Jeong, M.S. in Computer Science, “A New Methodology for Identifying Interface

Residues Involved in Binding Protein Complexes”, Master Thesis, the University of Kansas, December 2011

29. David Tai, M.S. in Computer Science, "Software for Supporting Large Scale Data Processing for High Throughput Screening", the University of Kansas, December 2011

30. Kriti Chakdar, M.S. in Computer Science, “Cancer Detection For Low Grade Squamous intraepithelial lesion”, Master Thesis, the University of Kansas, August 2012

31. Hyuntaek Oh, M.S. in Bioengineering, “Bayesian Ensemble Learning for Medical Image Denoising”, Master Thesis, the University of Kansas, August 2012

32. Manogna Thimma, M.S. in Computer Science, “Hybrid approach for XML access control (HyXAC)”, Master Thesis, the University of Kansas, July 2012

33. Gianpierre Villagomez Saldana, M.S. in Computer Science, “Exploration of Large Data Sets

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in Mobile Devices”, Master Project, the University of Kansas, May 2012 34. Yingying Ma, M.S. in Computer Science, “A Comparison of Two Discretization Options of

the MLEM2 algorithm”, Master Thesis, May 2014 35. Rama Subramanian Krishnamoorthy, M.S. in Computer Science, “Adding Collision

Detection to Functional Active Programming”, Master Project, January 2015 36. Venu Gopal Reddy Bommu, M. S. in Computer Science, “Performance analysis of various

implementations of machine learning algorithms”, Master Project, May 2015 37. Satya Shanmuka Srinivas Kundeti, M. S. in Computer Science, “A comparison of two

decision tree generating algorithms: C4.5 and CART based on numerical data”, M.S. in Computer Science, Master Project, February 2016

38. Caitlin McCollister, M. S. in Computer Science, “Predicting Author Traits Through Topic Modeling of Multilingual Social Media Text”, M. S. in Computer Science, Master Thesis, May 2016

39. Anirudh Narasimman, M. S. in Computer Science, “Arcana: Private Tweets on a Public Microblog Platform”, M. S. in Computer Science, Master Thesis, May 2016

COURSES TAUGHT Theoretic Foundation of Data Science (KU EECS 940, graduate course) Introduction to Systems Biology (KU EECS 831, graduate course) Pattern Discovery from Data (KU EECS 800, graduate seminar) Mining Biological Data (KU EECS 800, graduate seminar) Machine Learning (KU EECS 738, graduate course) Introduction to Bioinformatics (KU EECS 730, graduate course) Introduction to Database Systems (KU EECS 647, undergraduate course) Data Structures (KU EECS 560, undergraduate course) Programming II (KU EECS 268, undergraduate course) Programming I (KU EECS 168, undergraduate course) Introduction to Programming (UNC COMP 14, undergraduate course)

SELECTED UNIVERSITY SERVICES Department: 1. Chair, EECS Bioinformatics Faculty Search Committee, 2012-2016 2. Chair, EECS Data Science Faculty Search Committee, 2016 3. Committee Member, ITTC Strategic Plan Committee, 2010-2011 4. Chair, ITTC Data Science Seminar, 2007-present 5. Committee Member, EECS Department Ph.D. Qualifying Exam Committee, 2012-2015 6. Committee Member, EECS Department Graduate Study Committee, 2010-2014 7. Committee Member, EECS Department Faculty Awards Committee, 2010-2012 8. Committee Member, EECS Department Student Awards Committee, 2009-2010 9. Committee Member, EECS Department Library Committee, 2008-2010 10. Committee Member, EECS Bioinformatics Faculty Search Committee, 2007-2008 11. Committee Member, EECS Department Equipment Committee, 2006-2008 School: 12. Director, the Bioinformatics Track and core faculty member, Bioengineering Graduate Program,

2012- present 13. Committee Member, Bioengineering Graduate Program, 2011- 2014 14. Committee Member, School of Engineering Strategic Plan Committee, 2010-2011 15. Committee Member, KU Bioengineering Program Qualifying Examination Planning Committee,

2008

University: 16. Mentor, KU Biotechnology Predoctoral Training Program, 2010-present

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17. Committee Member, KU Technology Infrastructure Planning Group, 2012 18. Committee Member, KU Bioinformatics Computation Facility Renovation User Committee, 2010

– 2012 19. Committee Member, KUCR Drug Discovery Task Force Committee, 2011 - 2012 20. Committee Member, KU ITTC Bioinformatics Computation Facility Renovation User

Committee, 2010 - 2012 21. Committee Member, KU Bioinformatics Computing Core Renovation Building Committee, 2010 22. Committee Member, KU Special Chemistry Center System Specialist Search Committee, 2010 23. Affiliated Faculty, Center for Biostatistics and Advanced Informatics, University of Kansas

School of Medicine, 2007- 2010 24. Committee Member, KU Molecular Graphics and Modeling Laboratory Research Associate

Search Committee, 2009 25. Committee Member, KU Special Chemistry Center Information Technology Senior Research

Assistant Search Committee, 2009 26. Committee Member, KU Special Chemistry Center Cheminformatics Specialist Search

Committee, 2008 – 2009 27. Committee Member, KU Bioinformatics Core Bioinformatics Specialist Search Committee, 2008 28. Fellow, Best Practices Institute, Center for Teaching Excellence, 2007-2008

PROFESSIONAL ACTIVITIES Panelist:

1. Panelist, NIH, October 2015 2. Panelist, NSF, Division of Information and Intelligent Systems, May 2015 3. Panelist, Biotechnology and Biological Sciences Research Councile,UK 4. Panelist, NASA Advanced Information Systems Technology (AIST, ROSES-14), San Diego,

CA, October 2014 5. Panelist, NSF Division of Information and Intelligent Systems, July 2014 6. Panelist, NIH, July 2014 7. Panelist, NSF Division of Information and Intelligent Systems, March 2014 8. Panelist, NIH, April 2014 9. Panelist, NSF Division of Biological Infrastructure, October 2013 10. Panelist, NASA Advanced Information Systems Technology (AIST, ROSES-11), San Diego,

CA, October 2011 11. Panelist, NSF Division of Information and Intelligent Systems, Washington DC, October 2011 12. Reviewer, NSF Division of Computing and Communication Foundations , 2009 13. Panelist, NASA Advanced Information Systems Technology (AIST, ROSES-08), College

Station, MD, October 2008

International Journals 14. Associate Editor, the Liebert Big Data Journal, 2014- present 15. Founding Associate Editor, the AIMS International Journal of Big Data and Information

Analytics, 2014 - present 16. Associate Editor, OA Bioinformatics, OA Publishing London, 2013- present 17. Editorial Board Member, PeerJ Computer Science, 2015-present 18. Editorial Board Member, Elsevier Journal of Big Data Research, 2014 – present 19. Editorial Board Member, Springer Journal of Big Data, 2013 – present 20. Editorial Board Member, International Journal of Data Mining and Bioinformatics (IJDMB),

2011 – present

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21. Executive Editorial Board Member (North America), Journal of Pharmacogenomics & Pharmacoproteomics, 2011 – present

22. Contributing Editor, American Journal of Bioinformatics, 2011 - present 23. Advisory Board Member, Journal of Combinatorial Chemistry and High Throughput Screening,

2009 – present 24. Guest Editor, Special Issue of IEEE/ACM Transactions on Computational Biology and

Bioinformatics for IEEE International Conference on Bioinformatics & Biomedicine, 2010

Program Co-Chair: 1. Program Co-Chair, the IEEE International Conference on Bioinformatics and Biomedical

Informatics (BIBM 2015), 2015 2. Workshop co-chair, the 2014 IEEE International Conference on Big Data (BigData 2014),

Washington DC, 2014 3. Workshop co-chair, the 2013 IEEE International Conference on Big Data (BigData 2013),

Silicon Valley, CA, 2013 4. Program Co-Chair, the 5th International Conference on BioMedical Engineering and Informatics

(BMEI 2012), Chongqing, China, October 2012 5. Demo & Poster Co-Chair and Program Committee Member, the 2nd ACM SIG International

Health Informatics Symposium (HIT'12), Miami, Florida, January 2012 6. Poster Session Co-Chair, IEEE International Conference on BioInformation and BioMedicine

(BIBM 2010), Hong Kong, China, December, 2010 7. Program Co-Chair, the 9th ACM International Workshop on Data Mining in Bioinformatics

(BIOKDD 2010), in conjunction with the 16th ACM International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington DC, July, 2010

8. Program Co-Chair, the 3rd ACM International Workshop on Data and Text Mining in Bioinformatics (DTMBIO'09), in conjunction with the 18th ACM International Conference on Information and Knowledge Management (CIKM'09), Hong Kong, November, 2009

9. Special Session Chair, Machine Learning and Data Mining in Bioinformatics, in conjunction with the 7th International Conference on Machine Learning and Applications (ICMLA'08), San Diego, California, December, 2008

10. Award Committee Co-Chair, IEEE International Conference on BioInformation and BioMedicine (BIBM 2008), Philadelphia, PA, USA, November 2008

11. Program Co-chair, The 2nd International Workshop on Data and Text Mining in Bioinformatics (DTMbio 2008), in Conjunction with the 17th ACM Conference on Information and Knowledge Management, Napa Valley, California, October, 2008

12. Program Co-chair, IEEE Workshop on Mining and Management of Biological Data (MMBD 2008), in conjunction with the 7th IEEE International Conference on Data Mining, Omaha, NE, USA, October, 2007

Program Committee Member: 13. Senior Program Committee Member, IEEE International Conference on Data Mining, 2016 14. Program Committee Member, the 22th ACM SIGKDD Conference on Knowledge Discovery

and Data Mining (KDD'16), San Francisco, CA, August 2016 15. Program Committee Member the 17th International Conference on Web-Age Information

Management , Nanchang, China, June 2016 16. Program Committee Member the Sixteenth SIAM International Conference on Data Mining,

Miami, FL, May 2016 17. Program Committee Member the The 20th Pacific Asia Conference on Knowledge Discovery

and Data Mining (PAKDD) 2016 , Auckland, New Zealand, April 2016 18. Program Committee Member, the 2015 IEEE International Conference on Big Data , Santa

Clara, CA, November 2015

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19. Program Committee Member, the International Conference of Tools with Artificial Intelligence (ICTAI 2015) , Vietri sul Mare, Italy, November 2015

20. Program Committee Member, the 2015 ACM International Conference on Information and Knowledge Management (CIKM) , Melbourne, Australia, October 2015

21. Program Committee Member, the 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'15) , Sydney, Australia, August 2015

22. Program Committee Member, the The 16th International Conference on Web-Age Information Management , Qingdao, China, June 2015

23. Program Committee Member, thePacific-Asia Conference on Knowledge Discovery and Data Mining , Ho Chi Minh, Vietnam, May 2015

24. Program Committee Member, the 2015 SIAM International Conference on Data Mining (SDM15) , Vancouver, Canada, March 2015

25. Program Committee Member, the IEEE International Conference on Tools with Artificial Intelligence (ICTAI'14) , Limassol, Cyprus, November 2014

26. Program Committee Member, the ACM International Conference on Information and Knowledge Management (CIKM'14) , Shanghai, China, November 2014

27. Program Committee Member, the IEEE International Conference on Data Science and Advanced Analytics (DSAA'14) , Shanghai, China, October 2014

28. Program Committee Member, the IEEE 14th International Conference on BioInformatics and BioEngineering (BIBE'14) , Boca Raton, USA, November 2014

29. Program Committee Member, the 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM'14) , Belfast, UK, November 2014

30. Program Committee Member, the 5th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB) , Newport Beach, CA, September 2014

31. Program Committee Member, the 3rd IEEE International Conference on Big Data Science and Engineering (BDSE'14) , Beijing, China, September 2014

32. Program Committee Member, the 13th International Workshop on Data Mining in Bioinformatics (BIOKDD'14) , in conjunction with the 20th ACM International Conference on Knowledge Discovery and Data Mining (KDD'14) , New York City, August 2014

33. Program Committee Member, the 20th ACM International Conference on Knowledge Discovery and Data Mining (KDD'14) , New York City, August 2014

34. Program Committee Member, the 3rd IEEE International Congress on Big Data , Anchorage, Alaska, June 2014

35. Program Committee Member, the 15th International conference on Web-Age Information Management , Macau, China, June 2014

36. Program Committee Member, the International Conference on Machine Learning (ICML 2014) , Beijing, China, June 2014

37. Program Committee Member, the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 14) , May 2014

38. Program Committee Member, the Second ASE International Conference on Big Data Science and Computing , Stanford, CA, May 2014

39. Program Committee Member, the SIAM International Conference on Data Mining (SDM) , Philadelphia, PE, April 2014

40. Program Committee Member, the Twelfth Asia Pacific Bioinformatics Conference (APBC'14) , Shanghai, China, January 2014

41. Program Committee Member, the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'13), Shanghai, China, December 2013

42. Program Committee Member, the International Workshop on Big Data Computing (BDC-2013), in conjunction with the International Conference on Algorithms and Applications for Parallel Processing (IC3APP-2013), Sorrento Peninsula, Italy, December 2013

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43. Program Committee Member, the 2013 IEEE International Conference on Big Data Science and Engineering, Sydney, Australia, December 2013

44. Program Committee Member, the 2013 IEEE International Conference on Data Mining (ICDM'13), Dallas, Texas, December 2013

45. Program Committee Member, the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013) , San Francisco, CA, October 2013

46. Program Committee Member, the 2013 ASE International Conference on BigData , Washington, DC, September 2013

47. Program Committee Member, the 19th ACM International Conference on Knowledge Discovery and Data Mining (KDD'13) , Chicago, IL, August 2013

48. Program Committee Member, the 30th International Conference on Machine Learning (ICML'13), Atlanta, GA, June 2013

49. Program Committee Member, the 14th International Conference on Web-Age Information Management, Beidaihe, China, June 2013

50. Program Committee Member, the 13th SIAM International Conference on Data Mining (SDM'13), Austin, TX, USA, May 2013

51. Program Committee Member, the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'13) , Gold Coast, Australia, April 2013

52. Program Committee Member, the Eleventh Asia Pacific Bioinformatics Conference (APBC'13) , Vancouver, BC, Canada, January 2013

53. Program Committee Member, the 12th IEEE International Conference on Data Mining (ICDM'12) , Brussels, Belgium, December 2012

54. Program Committee Member, The IEEE International Workshop on Biological Data Mining and its Applications in Healthcare, in conjunction with the 12th IEEE International Conference on Data Mining (ICDM'12), Brussels, Belgium, December 2012

55. Program Committee Member, the 24th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’12), Athens, Greece, November 2012

56. Program Committee Member, the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'12) , Philadelphia, PE, October 2012

57. Program Committee Member, the 21st ACM Conference on Information and Knowledge Management (CIKM'12) , Maui, Hawaii, October 2012

58. Program Committee Member, the 6th ACM International Workshop on Data and Text Mining in Biomedical informatics, in conjunction with the ACM Conference on Information and Knowledge Management (CIKM'12) , Maui, Hawaii, October 2012

59. Program Committee Member, the ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB'12) , Orlando, Florida, October 2012

60. Program Committee Member, the First International Conference on Global Health Challenges, Venice, Italy, October 2012

61. Program Committee Member, The First International Conference on Data Analytics (DATA ANALYTICS 2012), Barcelona, Spain, September 2012

62. Program Committee Member, the 18th ACM International Conference on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, August 2012

63. Program Committee Member, the ACM International Workshop on Knowledge Discovery from Sensor Data (Sensor-KDD'12), Beijing, China, August 2012

64. Program Committee Member, the Fifth International Workshop on Intelligent Informatics in Biology and Medicine (IIBM’12), in conjunction with Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2012), Palermo, Italy, July 2012

65. Program Committee Member, the 2012 SIAM International Conference on Data Mining (SDM'12) , Anaheim, CA, April 2012

66. Program Committee Member, the 10th Asia Pacific Bioinformatics Conference (APBC'12) ,

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Melbourne, Australia, January 2012 67. Program Committee Member, the 11th IEEE International Conference on Data Mining

(ICDM'11), Vancouver, Canada, December 2011 68. Program Committee Member, the Tenth IEEE International Conference on Machine Learning

and Applications (ICMLA'11), Honolulu, Hawaii, December 2011 69. Program Committee Member, the IEEE International Conference on Bioinformatics and

Biomedicine (BIBM'11), Atlanta, Georgia, November 2011 70. Program Committee Member, the 23rd IEEE International Conference on Tools with Artificial

Intelligence (ICTAI’11), Boca Raton, Florida, November 2011 71. Program Committee Member, the 20th ACM Conference on Information and Knowledge

Management (CIKM'11), Glasgow, Scotland, UK, October 2011 72. Program Committee Member, ACM International Workshop on Data and Text Mining in

Bioinformatics (DTMBio’11), in conjunction with the 20th ACM Conference on Information and Knowledge Management (CIKM'11), Glasgow, Scotland, UK, October 2011

73. Program Committee Member, Workshop on Knowledge Discovery in Health Care and Medicine (KD-HCM), In conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Athens, Greece, September 2011

74. Program Committee Member, the IEEE International Conference on Healthcare Informatics, Imaging, and Systems Biology (HISB'11) , San Jose, California, July 2011

75. Program Committee Member, the 9th Asia Pacific Bioinformatics Conference (APBC'11), Incheon, Korea, Jan 2011

76. Program Committee Member, the 10th IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia, December 2010

77. Program Committee Member, the IEEE International Conference on Bioinformatics & Biomedicine (BIBM 2010), Hong Kong, China, December 2010

78. Program Committee Member, the 1st ACM International Health Informatics Symposium (SIGHIT 2010), Washington DC, November 2010

79. Program Committee Member, the 9th IEEE International Conference on Data Mining (ICDM 2009), Miami, Florida, December 2009

80. Program Committee Member, the IEEE International Conference on Bioinformatics & Biomedicine (BIBM 2009), Washington DC, November 2009

81. Program Committee Member, the 18th ACM International Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, November 2009

82. Program Committee Member, the 15th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD 2009), Paris, France, June 2009

83. Program Committee Member, the 3rd International Workshop on Knowledge Discovery from Sensor Data (SensorKDD 2009), in conjunction with the 15th ACM International Conference on Knowledge Discovery and Data Mining, Paris, France, June 2009

84. Program Committee Member, the 25th IEEE International Conference on Data Engineering (ICDE 2009), Shanghai, China, April 2009

85. Program Committee Member, the first International Workshop on Data Mining in Drug Discovery (RxDM 2009), in conjunction with SIAM Data Mining, Sparks, Nevada, May 2009

86. Program Committee Member, the Second International Workshop on Intelligent Informatics in Biology and Medicine (IIBM 2009), in Conjunction with the International Conference on Complex, Intelligent and Software Intensive Systems, Fukuoka, Japan, March 2009

87. Program Committee Member, the Demonstration Track of the 8th IEEE International Conference on Data Mining, (ICDM 2008), Pisa, Italy, December 2008

88. Program Committee Member, the Seventh International Conference on Machine Learning and Applications (ICMLA'08), San Diego, CA, USA, December 2008

89. Program Committee Member, IEEE International Conference on BioInformation and

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BioMedicine (BIBM 2008), Philadelphia, PA, USA, November 2008 90. Program Committee Member, the International workshop on Biomedical and Health

Informatics, in conjunction with the IEEE International Conference on BioInformation and BioMedicine (BIBM 2008), Philadelphia, PA, USA, November 2008

91. Program Committee Member, the 1st International Workshop on Data Mining in Functional Genomics, in conjunction with the IEEE International Conference on BioInformation and BioMedicine (BIBM 2008), Philadelphia, PA, USA, November 2008

92. Program Committee Member, the 8th International Workshop on Data Mining in Bioinformatics (BIOKDD 2008) in Conjunction with the 14th ACM SIGKDD, Las Vegas, NV, August 2008

93. Program Committee Member, the IADIS European Conference on Data Mining (ECDM 2008), Amsterdam, Netherlands, July 2008

94. Program Committee Member, SIAM International Conference on Data Mining (SDM'08), Atlanta, George, April 2008

95. Program Committee Member, International Workshop on Intelligent Informatics in Biology and Medicine (IIMB), in Conjunction with the International Conference on Complex, Intelligent and Software Intensive Systems, Barcelona, Spain, March 2008

96. Program Committee Member, the 6th International Conference on Machine Learning and Applications (ICMLA'07), Cincinnati, Ohio, USA, December 2007

97. Program Committee Member, International Workshop on Machine Learning in Biomedicine and Bioinformatics, in Conjunction with the 6th International Conference on Machine Learning and Applications (ICMLA'07), Cincinnati, Ohio, USA, December 2007

98. Program Committee Member, IEEE International Conference on Bioinformatics and Biomedicine (BIBM'07), Silicon Valley, USA, November 2007

99. Program Committee Member, International Workshop on Knowledge Discovery and Management in Health Informatics, in Conjunction with the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'07), Silicon Valley, USA, November 2007

100. Program Committee Member, the 2nd VLDB Workshop on Data Mining in Bioinformatics in Conjunction with the 33rd International Conference on Very Large Data Bases, University of Vienna, Austria, September 2007

101. Program Committee Member, the 7th International Workshop on Data Mining in Bioinformatics (BIOKDD'07) in Conjunction with the 13th ACM SIGKDD, San Jose, CA, USA, August 2007

102. Program Committee Member, the 1st European Data Mining Conference (ECDM'07), Lisbon, Portugal, July 2007

103. Program Committee Member, the 5th International Conference on Machine Learning and Applications (ICMLA'06), Orlando, Florida, USA, December 2006

PUBLICATIONS *: Corresponding Author Journal Papers:

1. Jingshan Huang, Karen Eilbeck, Barry Smith, Judith A. Blake, Dejing Dou, Weili Huang, Darren A. Natale, Alan Ruttenberg, Jun Huan, Michael T. Zimmermann, Guoqian Jiang, Yu Lin, Bin Wu, Harrison J. Strachan, Yongqun He, Shaojie Zhang, Xiaowei Wang, Zixing Liu, Glen Borchert, Ming Tan, Journal of Biomedical SemanticsThe Non-Coding RNA Ontology (NCRO): A comprehensive resource for the unification of non-coding RNA biology, Journal of Biomedical Semantics, 2016

2. Jingshan Huang, Karen Eilbeck, Barry Smith, Judith A. Blake, Dejing Dou, Weili Huang, Darren A. Natale, Alan Ruttenberg, Jun Huan, Michael T. Zimmermann, Guoqian Jiang, Yu Lin, Bin Wu, Harrison Strachan, Nisansa de Silva, Mohan Vamsi Kasukurthi, Vikash Kumar Jha, Yongqun He, Shaojie Zhang, Xiaowei Wang, Zixing Liu, Glen Borchert, Ming Tan, The Development of Non-Coding RNA Ontology, International Journal of Data Mining and Bioinformatics, 2016

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3. Xiaoqing Peng, Jianxin Wang, Jun Huan, Fang-Xiang Wu Double-layer clustering method to predict protein complexes based on power-law distribution and protein sublocalization, Journal of theoretical biology, 2016

4. Alexios Koutsoukas, Joseph St. Amand, Meenakshi Mishra, Jun Huan Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine, Frontiers in Environmental Science, section Environmental Informatics, March 2016, http://dx.doi.org/10.3389/fenvs.2016.00011. This article is part of the topic: Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs where several of our models are ranked top 10 in the international competition.

5. Qiang Yu, Hongwei Huo, Jeffrey Scott Vitter, Jun Huan, and Yakov Nekrich, An Efficient Exact Algorithm for the Motif Stem Search Problem over Large Alphabets, IEEE/ACM Transactions on Bioinformatics and Computational Biology, Vol. 12, No. 2, pp. 384-397, 2015

6. Hongliang Fei and Jun Huan*, Structured Sparse Boosting for Graph Classification, ACM Transactions on Knowledge Discovery from Data, Vol. 9 No. 1, Article No. 4, 2014

7. Said Bleik, Meenakshi Mishra, Jun Huan, Min Song, Text Categorization of Biomedical Data Sets using Graph Kernels and a Controlled Vocabulary, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Nov, 10, No. 5, pp. 1211-1217, 2013

8. Ruoyi Jiang, Hongliang Fei, Jun Huan*, A Family of Joint Sparse PCA Algorithms for Anomaly Localization in Network Data Streams, IEEE Transactions on Knowledge and Data Engineering, Vol. 25, No. 11, pp. 2421-243, 2013

9. Jintao Zhang, Jun Huan*, Predicting Drug-Induced QT Prolongation Effects Using Multi-View Learning, IEEE Transactions on NanoBioscience , Vol. 12, No. 3, pp. 206-213, 2013

10. Hongliang Fei and Jun Huan*, Structured Feature Selection and Task Relationship Inference for Multi-Task Learning, Knowledge and Information Systems, Vol. 35, No. 2, pp. 345-364, 2013 (invited to the KAIS special issue of selected papers from ICDM'11)

11. Meenakshi Mishra, Hongliang Fei and Jun Huan*, Computational prediction of toxicity, Int. J. Data Mining and Bioinformatics, Vol. 8, No. 3, pp. 338-348, 2013

12. Brian Quanz, Jun Huan*, and Meenakshi Mishra, Knowledge Transfer with Low-Quality Data: a Feature Extraction Issue, IEEE Transactions on Knowledge and Data Engineering, Vol. 24, No. 10, pp. 1789-1802, 2012 (invited to the TKDE special issue of selected papers from ICDE'11)

13. J. Huang, D. Dou, J. Dang, J.H. Pardue, X. Qin, J. Huan*, W.T. Gerthoffer, and M. Tan, Knowledge Acquisition, Semantic Text Mining, and Security Risks in Health and Biomedical Informatics , World Journal of Biological Chemistry, Vol. 3, No. 2, 2012

14. Jintao Zhang, Genald Lushington, Jun Huan*, The BioAssay Network and Its Implications to Future Therapeutic Discovery, BMC Bioinformatics, Vol. 12, Suppl 5:S1, 2011

15. Yi Jia, Jintao Zhang, and Jun Huan*, An efficient graph-mining method for complicated and noisy data with real-world applications, Knowledge and Information Systems, Vol. 28, No. 4, 423-447, 2011

16. Jintao Zhang, Gerald Lushington, and Jun Huan*, Characterizing the Diversity and Biological Relevance of the MLPCN Assay Manifold and Screening Set, Journal of Chemical Information and Modeling, Vol. 51, No. 6, pp. 1205-1215, 2011

17. Meenakshi Mishra, Hongliang Fei, and Jun Huan*, Computational Prediction of Toxicity, International Journal of Data Mining and Bioinformatics, 2011

18. Yong Bai, Jun Huan, Seonghoon Kim, Measuring Bridge Construction Efficiency Using the Wireless Real-time Video Monitoring System, Journal of Management in Engineering, 2011

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19. The MicroArray Quality Control (MAQC) Consortium, The MAQC-II Project: A Comprehensive Study of Common Practices for the Development and Validation of Microarray-based Predictive Models, Nature Biotechnology, Vol. 28, pp. 827-838, 2010

20. Yi Jia, Jun Huan*, Constructing Non-Stationary Dynamic Bayesian Networks with a Flexible Lag Choosing Mechanism, BMC Bioinformatics, Vol. 11 (Suppl 6):S27, 2010

21. Deepak Bandyopadhyay, Jun Huan, Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, and Alexander Tropsha, Functional Neighbors: Relationships between Non-homologous Protein Families Inferred Using Family-Specific Fingerprints, IEEE Transaction on Information Technology in Biomedicine, Vol. 14, No. 5, pp. 1137-1143, 2010

22. Seak Fei Lei and Jun Huan*, Towards Site-based Protein Functional Annotations, International Journal of Data Mining in Bioinformatics, Vol. 4, No.4, pp. 452 – 470, 2010

23. Aaron Smalter, Jun Huan*, Jia Yi, and Gerald Lushington, GPD: A Graph Pattern Diffusion Kernel for Accurate Graph Classification with Applications in Cheminformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 7, No. 2, pp. 197-207, 2010

24. Xiaohong Wang, Jun Huan*, Aaron Smalter, Gerald Lushington, Application of Kernel Functions for Accurate Similarity Search in Large Chemical Databases, BMC Bioinformatics, Vol. 11 (Suppl 3):S8, 2010

25. Deepak Bandyopadhyay, Jun Huan, Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha,Identification of Family-Specific Residue Packing Motifs and their use for Structure-Based Protein Function Prediction, I. Method Development, Journal of Computer-Aided Molecular Design, Vol. 23, Iss. 11, pp. 773-784, 2009

26. Deepak Bandyopadhyay, Jun Huan, Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha, Identification of Family-Specific Residue Packing Motifs and their use for Structure-Based Protein Function Prediction: II. Case Studies and Applications, Journal of Computer-Aided Molecular Design, Vol. 23, Iss. 11, pp. 785–797, 2009

27. Aaron Smalter, Jun Huan*, Gerald Lushington, Graph Wavelet Alignment Kernels for Drug Virtual Screening, Journal of Bioinformatics and Computational Biology, Vol. 7 (3), pp. 473-497, 2009

28. Yi Jia, Jun Huan, Vincent Buhr, Jintao Zhang, and Leonidas N. Carayannopoulos, Towards Comprehensive Structural Motif Mining for Better Fold Annotation in the “Twilight Zone” of Sequence Dissimilarity, BMC Bioinformatics, Vol. 10 (Suppl 1):S46, 2009

29. Deepak Bandyopadhyay, Jun Huan, Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha, Structure-based Function Inference Using Protein Family-specific Fingerprints, Protein Science, Vol. 15, No. 6, pp. 1537-43, 2006

30. Jun Huan, D. Bandyopadhyay, W. Wang, J. Snoeyink, J. Prins, and A. Tropsha, Comparing Graph Representations of Protein Structure for Mining Family-Specific Residue-Based Packing Motifs, Journal of Computational Biology, Vol. 12, No. 6, pp. 657-671, 2005

31. Jingmei Liu, Yuan Yuan, Jun Huan, and Zhiyuan Shen. Inhibition of Breast and Brain Cancer Cell Growth by BCCIP, an Evolutionarily Conserved Nuclear Protein that Interacts with BRCA2, Oncogene, Vol. 20, No. 3, pp. 336-345, 2001

Book Chapters, Volumes Edited, and Tutorials: 32. Xiang Chen, Jun Huan, On-line Graph Partitioning with An Affine Message Combing Cost

Function, Big Data Analytics: Methods and Applications, S. Pyne, B. L. S. Rao, S. B. Rao (eds.), Springer, 2016

33. Jun Huan, Satoru Miyano, Amarda Shehu, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Vijay K. Gombar, Matthieu-P. Schapranow, Illhoi Yoo, Jiayu Zhou, Brian Chen, Vinay Pai, Brian G. Pierce, 2015 IEEE International Conference on Bioinformatics and Biomedicine, Washington, DC, USA, November 9-12, 2015

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34. Jimmy Lin, Jian Pei, Xiaohua Hu, Wo Chang, Raghunath Nambiar, Charu Aggarwal, Nick Cercone, Vasant Honavar, Jun Huan, Bamshad Mobasher, Saumyadipta Pyne: 2014 IEEE International Conference on Big Data, Big Data 2014, Washington, DC, USA, October 27-30, 2014

35. Meenakshi Mishra, Jun Huan, Brian Potetz, Predicting Chemical Toxicity with Bayesian Approaches, Medical Applications of Artificial Intelligence, Chapter 9, edited by Arvin Agah, Taylor & Francis Group, 2014

36. Mohammad Al Hasan, Jun Huan, Jake Yue Chen, Mohammed J. Zaki: Biological knowledge discovery and data mining, Scientific Programming, Nov. 20, No. 1, pp. 1-2, 2012

37. Jun Huan, Jake Chen, and Mohammed Zaki, Guest Editorial: Selected Articles from the 9th International Workshop on Data Mining in Bioinformatics (BIOKDD), BMC Bioinformatics, Vol. 12, Suppl 12, 2011

38. Fang-Xiang Wu and Jun Huan, Guest Editorial: Special Focus on Bioinformatics and Systems Biology, IEEE/ACM Transaction on Computational Biology and Bioinformatics, Vol. 8, No. 2, pp. 292-293, 2011

39. Xiaohong Wang, Jun Huan, Aaron Smalter, Gerald H. Lushington, G-hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases, Graph Data Management: Techniques and Applications, Sherif Sakr and Eric Pardede edt, IGI Global, 2011

40. Jun Huan, Knowledge Discovery in Academic Drug Discovery Programs: Opportunities and Challenges, Tutorial, In Proceedings of the IEEE International Conference on Data Mining, Sydney, Australia, 2010, pp. 1218

41. Jun Huan, Jake Chen, Mohammed Zaki, Proceeding of the 9th International Workshop on Data Mining in Bioinformatics, BIOKDD 2010, Washington DC, July, 2010

42. Doheon Lee, Russ B. Altman, Min Song, and Jun Huan, Proceeding of the 3rd International Workshop on Data and Text Mining in Bioinformatics, DTMBIO 2009, Hong Kong, China, November, 2009

43. Aaron Smalter and Jun Huan, Kernel Function Applications in Cheminformatics, Computational Intelligence and Pattern Analysis in Biological Informatics, U. Maulik, S. Bandyopadhyay and J. T. L. Wang (Eds.), Wiley, 2009 (invited)

44. Jun Huan, Frequent Subgraph Mining, Encyclopedia of Database Systems, pp. 1170-1175, Liu & Özsu Eds., Springer, New York, 2009

45. Jun Huan, Wei Wang, and Jan Prins, Protein Local Structure Comparison: Methods and Future Directions, Advances in Computers, Chau-Wen Tseng (eds.), Elsevier, pp. 180-255, 2006

Refereed Conference Papers: 46. Chao Lan, Jianxing Wang, and Jun Huan, Towards a Theoretical Understanding of Negative

Transfer in Collective Matrix Factorization, the Conference on Uncertainty in Artificial Intelligence (UAI), New York City, NY, June 2016, acceptance rate 85/275=31%.

47. Chao Lan, Yujie Deng, Xiaoli Li, and Jun Huan, Co-Regularized Least Square Regression for Multi-View Multi-Class Classification, the International Joint Conference on Neural Networks, Vancouver, Canada, July 2016

48. Chao Lan, Yujie Deng, and Jun Huan, A Provably Correct Disagreement based Active Matrix Completion Method, Oral Presentation, the International Joint Conference on Neural Networks, Vancouver, Canada, July 2016

49. Qiang Yu, Hongwei Huo, Ruixing Zhao, Dazheng Feng, Jeffrey Scott Vitter, Jun Huan, Reference sequence selection for motif searches, In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM’15), Washington DC, December 2015, pp. 569-574, acceptance rate: 68/345= 19%

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50. Meenakshi Mishra and Jun Huan, Learning Task Grouping using Supervised Task Space Partitioning in Lifelong Multitask Learning, in proceedings of the ACM Conference on Information and Knowledge Management (CIKM'15), Melbourne, Australia, October 2015, acceptance rate: 87/484=18%

51. Chao Lan and Jun Huan, Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning, in proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’15), Sydney, Australia, August 2015, acceptance rate: 159/869= 18%

52. Qiang Yu, Hongwei Huo, Xiaoyang Chen, Haitao Guo, Jeffrey Scott Vitter, and Jun Huan, An Efficient Motif Finding Algorithm for Large DNA Data Sets, in Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM'14), Belfast, UK, November 2014, acceptance rate: 56/286= 19%

53. Yuhao Yang, Chao Lan, Xiaoli Li, Bo Luo, and Jun Huan, Automatic Social Circle Detection Using Multi-View Clustering, in Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM’14), Shanghai, China, November 2014

54. Meenakshi Mishra and Jun Huan*, Multitask Learning with Feature Selection for Groups of Related Tasks, in Proceedings of EEE International Conference on Data Mining (ICDM'13), Dallas, TX, December 2013, pp. 1157-1162

55. Qiang Yu, Hongwei Huo, Jeffrey Scott Vitter, Jun Huan, and Yakov Nekrich, StemFinder: An Efficient Algorithm for Searching Motif Stems over Large Alphabets, in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM’13), Shanghai, China, December 2013, pp. 473-476

56. Jingshan Huang, Jun Huan, Alexander Tropsha, Jiangbo Dang, Min Xiong, and Weijian Jiang, Semantics-Driven Frequent Data Pattern Mining on Electronic Health Records for Effective Adverse Drug Event Monitoring, in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM’13) , industry track, Shanghai, China, December 2013, pp. 608-611

57. Brian Quanz and Jun Huan*, CoNet: Feature Generation for Multi-View Semi-Supervised Learning with Partially Observed Views, in Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM'12), Maui, Hawaii, October 2012, pp. 1273-1282, acceptance rate 146/1088=13%

58. Jia Yi, Wenrong Zeng and Jun Huan*, Non-stationary bayesian networks based on perfect simulation, the 21st ACM Conference on Information and Knowledge Management (CIKM'12) , Maui, Hawaii, October 2012, pp. 1095-1104, acceptance rate 146/1088=13%

59. Jintao Zhang and Jun Huan*, Inductive Multi-Task Learning with Multiple View Data, in Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12) , Beijing, China, August 2012, pp. 543-551

60. Jintao Zhang and Jun Huan*, Multi-target protein-chemical interaction prediction using task-regularized and boosted multi-task learning, ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB'12), Orlando, FL, October 2012, pp. 60-67, acceptance rate 33/159=20%

61. Jintao Zhang and Jun Huan*, Drug-induced QT Prolongation Prediction Using Co-regularized Multi-view Learning, The IEEE International Conference on Bioinformatics and Biomedicine (BIBM'12) , Philadelphia, Pennsylvania, October 2012, pp. 1-6, acceptance rate 59/299=20%

62. Xin Huang, Hong Cheng, Jiong Yang, Jeffrey Xu Yu, Hongliang Fei, and Jun Huan, Semi-Supervised Clustering of Graph Objects: A Subgraph Mining Approach, in Proceedings of the 17th International Conference on Database Systems for Advanced Applications (DASFAA'12), Busan, South Korea, April 2012, pp. 197-212, acceptance rate 44/159=27.6%

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63. Hongliang Fei and Jun Huan*, Structured Feature Selection and Task Relationship Inference for Multi-Task Learning, in Proceedings of the IEEE International Conference on Data Mining (ICDM'11), Vancouver, Canada, December 2011, acceptance rate 12%, Best Student Paper (1/101 accepted full papers)

64. Meenakshi Mishra, Brian Potetz, and Jun Huan*, Bayesian Classifier for Chemical Toxicity Prediction, in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'11), Atlanta, GA, November 2011, short paper, acceptance rate 40%

65. Hongliang Fei, Ruoyi Jiang, Yuhao Yang, Bo Luo, Jun Huan*, Content based Social Behavior Prediction: A Multi-task Learning Approach, in Proceedings of the 20th ACM International Conference on Information and Knowledge Management (CIKM'11), Glasgow, UK, October 2011, acceptance rate 35%

66. Ruoyi Jiang, Hongliang Fei, and Jun Huan*, Anomaly Localization for Network Data Streams with Graph Joint Sparse PCA, in Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD'11), San Diego, CA, August 2011, acceptance rate 125/714 = 17.5%

67. Aaron Smalter, Jun Huan*, Gerry Lushington, Similarity Boosting for Label Noise Tolerance in Protein-Chemical Interaction Prediction, in Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB'11), Chicago, IL, August 2011, regular paper, acceptance rate 29/153 = 19%

68. Brian Quanz, Jun Huan* and Meenakshi Mishra, Knowledge Transfer with Low-Quality Data: a Feature Extraction Issue, in Proceedings of the IEEE International Conference on Data Engineernig (ICDE'11), Hannover, Germany, April 2011, pp. 769-779, regular paper, acceptance rate 98/494 = 19.8%

69. Meenakshi Mishra, Hongliang Fei, and Jun Huan*, Computational Prediction of Toxicity, in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'10), Hong Kong, China, December 2010, pp. 686-691, regular paper, acceptance rate 61/355 = 17%

70. Jintao Zhang, Gerald Lushington, and Jun Huan*, Exploratory Analysis of the BioAssay Network with Implications to Therapeutic Discovery, in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'10), Hong Kong, China, December 2010, pp. 569-572, short paper

71. Hongliang Fei, Brian Quanz, and Jun Huan*, Regularization and Feature Selection for Networked Features, in Proceedings of the 19th ACM Conference on Information and Knowledge Management (CIKM'10), Toronto, Canada, October 2010, pp. 1893-1896, acceptance rate 296/945 = 31%

72. Jintao Zhang and Jun Huan*, Novel Biological Network Feature Discovery for In Silico Identification of Drug Targets, in Proceedings of the 1st ACM International Health Informatics Symposium (IHI'10), Arlington, VA, November 2010, pp. 144-152

73. Hongliang Fei and Jun Huan*, Boosting with Structure Information in the Functional Space: an Application to Graph Classification, in Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD'10), Washington DC, July 2010, pp. 643-652, acceptance rate 101/578 = 17%

74. Aaron Smalter, Jun Huan*, Gerald Lushington, Feature Selection in the Feature Tensor Product Space, in Proceedings of the 9th IEEE International Conference on Data Mining (ICDM'09), Miami, FL, December 2009, pp. 1004-1009, acceptance rate 140/786 = 18%

75. Hongliang Fei, Jun Huan*, L2 Norm Regularized Feature Kernel Regression For Graph Data, in Proceedings of the ACM 18th Conference on Information and Knowledge Management (CIKM’09), Hong Kong, China, October 2009, pp. 593-600, acceptance rate 123/847=15%, Best Paper Award Runner-up (6/123 accepted papers)

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76. Brian Quanz, Jun Huan*, Large Margin Transductive Transfer Learning, in Proceedings of the ACM 18th Conference on Information and Knowledge Management (CIKM’09), Hong Kong, China, October 2009, pp. 1327-1336, acceptance rate 123/847=15%

77. Xiaohong Wang, Jun Huan*, Aaron Smalter, Gerald Lushington, Application of Kernel Functions for Accurate Similarity Search in Large Chemical Databases, in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'09), Washington DC, November 2009, pp. 356-361, acceptance rate 44/233 = 19%

78. Yi Jia, Jun Huan*, The Analysis of Arabidopsis Thaliana Circadian Network Based on Non-stationary DBNs Approach with Flexible Time Lag Choosing Mechanism, in Proceedings of the IEEE International Conference on Bioinformatics & Biomedicine (BIBM'09), Washington DC, November 2009, pp. 356-361, acceptance rate 81/233= 35%

79. Brian Quanz and Jun Huan*, Aligned Graph Classification with Laplacian Regularized Logistic Regression, in Proceedings of the SIAM Data Mining (SDM'09), Sparks, NV, April 2009, pp. 353-364

80. Xiaohong Wang, Aaron Smalter, Jun Huan*, and Gerald Lushington, G-Hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases, to appear in Proceedings of the 12th International Conference on Extending Database Technology (EDBT'09), Saint-Petersburg, Russia, March 2009, pp. 472-480, acceptance rate 92/283 = 32%

81. Deepak Bandyopadhyay, Jun Huan, Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, and Alexander Tropsha, Functional Neighbors: Relationships between Non-homologous Protein Families Inferred Using Family-Specific Fingerprints, in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'08), Philadelphia, PA, December 2008, pp. 199-206, acceptance rate 38/156 = 24%

82. Seak Fei Lei, Jun Huan, Towards Site-based Function Annotations for Protein Structures, in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM'08), Philadelphia, PA, December 2008, pp. 193-198, acceptance rate 38/156 = 24%

83. Aaron Smalter, Jun Huan*, and Gerald Lushington. A Graph Pattern Diffusion Kernel for Chemical Compound Classification. in Proceedings of the 8th IEEE International Conference on Bioinformatics and BioEngineering (BIBE'08), Athens, Greece, October 2008

84. Hongliang Fei, Jun Huan*, Structure Feature Selection for Chemical Compound Classification, in Proceedings of the 8th IEEE International Conference on Bioinformatics and BioEngineering (BIBE'08), Athens, Greece, October 2008

85. Hongliang Fei, Jun Huan*, Structure Feature Selection for Graph Classification, to appear in Proceedings of the ACM 17th Conference on Information and Knowledge Management (CIKM’08), Napa Valley, CA, October 2008, pp. 991-1000, acceptance rate 132/772=17%

86. Aaron Smalter, Jun Huan*, Gerald Lushington, Graph Wavelet Alignment Kernels for Drug Virtual Screening, in Proceedings of the 7th Annual International Conference on Computational Systems Bioinformatics (CSB’08), Stanford, CA, July 2008, pp. 327-338

87. Aaron Smalter, Jun Huan*, Gerald Lushington, Structure-based Pattern Mining For Chemical Compound Classification, in Proceedings of the 6th Asia Pacific Bioinformatics Conference (APBC’08), Beijing, China, January 2008, pp. 39-48

88. X. Wang, J. Huan, J. Snoeyink, W. Wang, Mining RNA Tertiary Motifs with Structure Graphs, in proceedings of the 19th International Conference on Scientific and Statistical Database Management (SSDBM’07), Banff, Canada, July 2007, pp. 31-39

89. X. Zhang, W. Wang, J. Huan, On demand Phenotype Ranking through Subspace Clustering, to appear in Proceedings of SIAM International Conference on Data Mining (SDM’07), Minneapolis, MN, April 2007, pp. 623-628

90. D. Williams, J. Huan, W. Wang, Graph Database Indexing Using Structured Graph Decomposition, in Proceedings of the 23rd IEEE International Conference on Data Engineering (ICDE’07), Istanbul, Turkey, April 2007, pp. 976-985

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91. J. Huan, D. Bandyopadhyay, J. Snoeyink, J. Prins, A. Tropsha, W. Wang, Distance-based Identification of Spatial Motifs in Proteins Using Constrained Frequent Subgraph Mining, in Proceedings of the IEEE Computational Systems Bioinformatics (CSB’06), Stanford, CA, August 2006

92. S. Olivier, J. Huan, J. Liu, J. Prins, J. Dinan, P. Sadayappan and C. Tseng. UTS: An Unbalanced Tree Search Benchmark, in Proceedings of the 19th Intl. Workshop on Languages and Compilers for Parallel Computing (LCPC’06), New Orleans, Louisiana, November 2006, pp. 235-250

93. J. Huan, W. Wang, J. Prins, J. Yang, SPIN: Mining Maximal Frequent Subgraphs from Graph Databases, in Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD’04), Seattle, Washington, August 2004, pp. 581-586

94. J. Huan, W. Wang, D. Bandyopadhyay, J. Snoeyink, J. Prins, A. Tropsha, Mining Family-specific Residue-Packing Patterns from Protein Structure Graphs, in Proceedings of the Eighth Annual International Conferences on Research in Computational Molecular Biology (RECOMB’04), San Diego, California, March 2004, pp. 308-315

95. J. Huan, W. Wang, A. Washington, J. Prins, R. Shah, A. Tropsha, Accurate Classification of Protein Families based on Coherent Subgraph Mining, in Proceedings of the Tenth Pacific Symposium on Biocomputing (PSB’04), Big Island, Hawaii, January 2004, pp. 411-422

96. K. Berlin, J. Huan, M. Jacob, G. Kochhar, J. Prins, B. Pugh, P. Sadayappan, J. Spacco, C. Tseng, Evaluating the impact of Programming Language Features on the Performance of Parallel Applications on Cluster Architectures, Language and Compilers for Parallel Computing (LCPC’03), Springer-Verlag, College Station, Texas, October 2003, pp. 194-208

97. J. Huan, W. Wang, J. Prins, Efficient Mining of Frequent Subgraphs in the Presence of Isomorphisms, in Proceedings of the 3nd IEEE International Conference of Data Mining (ICDM’03), Melbourne, Florida, November 2003, pp. 549 -552

Refereed Workshop or Poster Papers: 98. Aaron Smalter Hall, and Jun Huan, KUChemBio: A repository of computational chemical

biology data sets, In Proceedings of the IEEE International Conference on Big Data, Santa Clara, CA, October 2013, pp. 37-42, poster

99. Peng Hao, Jintao Zhang, and Jun Huan, A New On-line Chemical Biology Data Visualization System, In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops, Shanghai, China, December 2013, pp. 35-37, poster

100. Avindra Fernando, Jun Huan, Justin P. Blumenstiel, Jin Li, Xue-wen Chen, Bo Luo: Identification of transposable elements of the giant panda (Ailuropoda melanoleuca) genome. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops, Philadelphia, PA, October 2012, pp. 674-681

101. Brian Quanz, Hongliang Fei, Jun Huan, Joseph Evans, Victor Frost, Gary Minden, Daniel Deavours, Leon Searl, Daniel DePardo, Martin Kuehnhausen, Daniel Fokum, Matt Zeets, Angela Oguna, Anomaly Detection with Sensor Data for Distributed Security, in Proceedings of the International Workshop on Sensor Networks, in conjunctions with the 18th International Conference on Computer Communications and Networks (ICCCN’09), San Francisco, CA, August 2009

102. Aaron Smalter, Jun Huan, and Gerald Lushington. GPD: A Graph Pattern Diffusion Kernel for Accurate Graph Classification. in Proceedings of the 8th International Workshop of Data Mining in Bioinformatics (BIOKDD'08), Las Vegas, NV, August 2008

103. J. Huan, D. Bandyopadhyay, J. Liu, J. Prins, J. Snoeyink, A. Tropsha, and W. Wang, Rapid Determination of Local Structural Features Common to a Set of Proteins, Intelligent Systems for Molecular Biology (ISMB’05) demo, Detroit, Michigan, June 2005

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104. D. Bandyopadhyay, J. Huan, J. Liu, J. Prins, J. Snoeyink, A. Tropsha, and W. Wang, Function Inference Using Family-Specific Subgraph Fingerprints Mined from Protein Families, Intelligent Systems for Molecular Biology (ISMB’05), poster, Detroit, Michigan, June 2005

105. R. Shah, J. Huan, A. Tropsha, W. Wang, Structure Based Identification of Protein Family Signatures for Function Annotation, in Proceeding of the Ninth Annual International Conferences on Research in Computational Molecular Biology (RECOMB’05), poster, Cambridge, MA, May 2005

106. J. Huan, J. Prins, T. Vision, W. Wang, Reconstruction of Ancestral Gene Order after Segmental Duplication and Gene Loss, IEEE Computer Science Society Bioinformatics Conference (CSB’03), poster, Stanford University, August 2003, pp. 484-485

Technical Reports & Thesis 107. J. Huan, Graph Based Pattern Discovery in Protein Structures, Ph.D. Dissertation, Computer

Science Department, University of North Carolina, 2006 108. D. Bandyopadhyay, J. Huan, J. Liu, J. Prins, J. Snoeyink, A. Tropsha, and W. Wang, Protein

Functional Family Identification by Fast Subgraph Isomorphism Using Structure-Based Fingerprints Mined from SCOP Families, UNC-CS Technical Report TR04-031, 2004. Poster presented at Triangle Biophysics Symposium, Nov. 2004, Durham, NC

109. J. Prins, J. Huan, B. Pugh, C. Tseng, P. Sadayappan, UPC Implementation of an Unbalanced Tree Search Benchmark, UNC-CS Technical Report TR03-034, 2003

110. J. Huan, A Localized Clustering Algorithm and Its Application in DNA Sequence Analysis, Master’s thesis, Computer Science Department, Oklahoma State University, 2000

111. M. G. D'Souza, J. Huan, S. Sutton, M. Romine, and N. Maltsev, PUMA2 -- An Environment for Comparative Analysis of Metabolic Subsystems and Automated Reconstruction of Metabolism of Microbial Consortia and Individual Organisms from Sequence Data, Argonne National Laboratory Technical Memorandum ANL/MCS-TM-240, 1999