Download CV - ITTC - The University of Kansas

CURRICULUM VITAE
Jun (Luke) Huan, Ph.D.
Professor
Department of Electrical Engineering and Computer Science
University of Kansas
Lawrence, KS 66047, USA
Phone: 1-785-864-2375
Fax: 1-785-864-3226
E-mail: [email protected]
http://ittc.ku.edu/~jhuan
RESEARCH INTEREST
Machine Learning and Data Mining: model selection, approximate inference, Bayesian nonparametrics,
kernel machines, deep learning
Big Data Analytics: big graph analytics, safe data analytics
Bio, Biomedical and Health Informatics: computational chemical biology, pharmacogenomics, mobile
health
EDUCATION
Ph.D., Computer Science, University of North Carolina at Chapel Hill, 2006
Graduate Certificate, Bioinformatics and Computational Biology, UNC-CH, 2003
M.S., Computer Science, Oklahoma State University, 2000
WORK EXPERIENCE
2016 – Present
2016 – Present
2014 – Present
2013 - 2013
2012 – Present
2012 – Present
2008 – 2014
2011 – 2014
2006 – 2011
2004
2001-2006
2000-2001
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, Partnership for International Research and Education (PIRE).
Director, Computational Chemical Biology Core, KU COBRE Center on
Chemical Biology of Infectious Disease
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
Visiting Professor, Computational Chemistry Group, GlaxoSmithKline plc.
(sabbatical leave)
Director, Data Science and Computational Life Sciences Laboratory,
Information and Telecommunication Technology Center, University of Kansas
Director, the Bioinformatics Track, Bioengineering Program, University of
Kansas
Director, Cheminformatics Core, KU NIH Specialized Chemistry Center
Associate Professor, Department of Electrical Engineering and Computer
Science, Associate Professor (by courtesy), Bioengineering Program,
Bioinformatics Program
Assistant Professor, Department of Electrical Engineering and Computer
Science, Assistant Professor (by courtesy), Bioengineering Program,
Bioinformatics Program
Intern, GlaxoSmithKline plc. Research Triangle Park, NC
Research Assistant, Computer Science Department, University of North
Carolina, Chapel Hill, NC
Software Designer, Nortel Networks, Richardson, TX
1
1999
Summer Intern, Mathematics and Computer Science Division, Argonne National
Laboratory, Argonne, IL
HONORS & AWARDS
•
•
•
•
•
•
•
Miller Scholar, University of Kansas School of Engineering, 2016
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
SELECTED 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, IEEE International Conference on Bioinformatics and Biomedicine, December 2016
•
Jun Huan, “Demystifying the Black Box: Towards Transparent and Interpretable Data Analytics”,
Invited Talk (Representing US NSF), US-Japan Joint Big Data PI Meeting/Symposium, Tokyo,
Japan, November 2016
•
Jun Huan, “Factor Analysis in Multi-X Learning”, Invited talk, University of Kentucky,
Lexington, KY, October 2016
•
Jun Huan, “Factor Analysis in Multi-X Learning”, Invited talk, Virginia Polytechnic Institute and
State University, Arlington, VA, September 2016
•
Jun Huan, “Factor Analysis in Multi-X Learning”, Invited talk, Baidu Research, San Jose, CA,
August 2016
•
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, 15th International Workshop on Data Mining in Bioinformatics (BIOKDD'16), in
conjunction with ACM SIGKDD International Conference on Knowledge Discovery and Data
Mining (SIGKDD '16), San Francisco, CA, August 2016
•
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), AAAI 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
2
•
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
•
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
3
•
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 Principal Investigator (total support >6M)
1
2
3
4
Intergovernmental
Personnel Act
Assignment
1/16-1/18
$454,865
NSF IIS
1513324
Identification of
Subpopulations for the
Intervention and
Prevention of Largescale Ebola Virus
Spreading
1/15-12/16
$189,000
NSF CNS
1337899
MRI: Acquisition of
Computing Equipment
for Supporting Dataintensive Bioinformatics
Research at the
University of Kansas
9/13-8/16
$714,000
6/13-5/15
$282,000
08/09 – 06/14
$500,000
NSF 1624071
University of
Kansas
Establishing a MultiDisciplinary Data
Science Research Team
at the University of
Kansas
5
NSF CAREER
Award IIS:
0845951
CAREER: Mining
Genome-wide ChemicalStructure Activity
Relationships in
Emergent Chemical
Genomics Databases
6
NIH
G20 RR031125
KU Bioinformatics
Computing Facility Core
Renovation and
Improvement*
07/10 – 07/12
$4,658,000
7
NIH,
Subcontract from
Protein
Structure/Function
09/06 – 09/10
$51,000
4
R01 GM868665
Specific Packing Motifs
8
US Department
of Transportation
Development of Freight
Analysis Framework for
the Sustainable
Economic Growth
07/07 – 07/08
$50,000
9
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
06/10 –06/11
06/08 – 06/09
Data Mining in
Predicting Function of
Biomolecules
$9,600
$8,000
As Co-Principal Investigator or Co-Investigator (total support >$55M)
11
NIH
OD023118
12
NIH
NR015743
13
NIH
GM113117-01
14
NSF IIS
1550320
15
NSF SMA
1547464
16
NSF CNS
1422206
Comprehensive Analysis of
Human Adaptive Immune
Receptors to Elucidate
Correlates of Epstein-Barr
virus Disease Suppression
09/16-06/21
$1,800,000
PI: Brandon
Dekosky
TEEN Connections for
Support from
Multidisciplinary
Professional & Peers
09/16-06/19
$1,500,000
PI: Carol Smith
05/16-04/21
$12,000,000
PI: Thomas
Prisinzano
09/15-09/18
$1,500,000
PI: Edward
Seidel (UIUC)
Collaborative Research:
EAGER: Automating
HERD Reporting Using
Machine Learning and
Administrative Data
09/15-08/17
$200,000
PI: Rodolfo
Torres
Privacy Protection in
Social Networks:
Bridging the Gap
Between User Perception
09/14-08/17
$220,000
PI: Bo Luo
COBRE: Chemical Biology
of Infectious Disease. My
role: Leader of the Core C:
Computational Chemical
Biology.
BD Hubs: MIDWEST:
SEEDCorn: Sustainable
Enabling Environment for
Data Collaboration (My
role: senior personnel and
Steer Committee Member)
5
and Privacy Enforcement
17
NIH
P20 GM103638
18
NSF OIA
1028098
19
NIH
U54 HG005031
20
NSF
CNS 0821625
21
Kansas
Department of
Transportation
22
23
08/12-07/17
$12,000,000
PI: Susan
Lunte
CDI-Type II:
Computational Methods
to Enable an Invertebrate
Paleontology
Knowledgebase
08/10 – 07/14
$1,500,000
PI: Xuewen
Chen
Kansas Special
Chemistry Center
07/08 – 07/14
$21,200,000
PI: Jeff Aubé
07/08 – 07/11
$300,000
PI: Joseph
Evans
07/08 – 12/09
$60,000
PI: Bai Yong
07/08 – 06/09
$30,000
PI: Bai Yong
06/07 – 06/10
$1,217,000
PI: Joseph
Evans
KU COBRE Center on
Molecular Analysis of
Disease Pathways
MRI: Acquisition of an
Advanced Computational
Infrastructure for
Modeling Biological
Systems
Development of an
Interactive E-Training
Program for Work
Smart Zone
Iowa Department Deployment Initiative:
Transportation Development of a Work
Zone training program
Office of Naval
Research
N00014-07-11042
SensorNet - Rail Sensor
Testbed - Active Agents
in Containers for
Transport Chain Security
NIH, through
KU Center for
$100,000
Chemical
Strategic chemical
PI:
Gerald
24
Methodology
synthesis guidance via
02/07 – 02/09
Lushington
and Library
data mining
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
Post Doctoral Research Associate Supervised
1. Koutsoukas Alexios, 2014-2016
Graduate Students in Progress:
2. Sai Nivedita Chandrasekaran (Ph.D. student since 2012)
3. Chao Lan (Ph.D. student since 2011)
4. Xiaoli Li (Ph.D. student since 2013)
5. Joseph St. Amand (Ph.D. student since 2011)
6. Bahl Pranav Shekhar (M.S. student since 2015)
Graduated Ph.D. Students:
7. Aaron Smalter, Ph.D. in Computer Science, “Genome-Wide Protein-Chemical Interaction
6
Prediction”, the University of Kansas, July 2011
8. Xiaotong Lin, Ph.D. in Computer Science, “Bayesian Network Learning and Applications in
Bioinformatics”, the University of Kansas, July 2012
9. Jintao Zhang, Ph.D. in Bioinformatics, “Drug Adverse Reaction Prediction with Multi-view
Learning”, the University of Kansas, August 2012
10. 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
11. Hongliang Fei, Ph.D. in Computer Science, “Learning with Structured Data: a Regularization
Based Approach”, the University of Kansas, October 2012
12. Yi Jia, Ph.D. in Computer Science, “Online Spectral Clustering on Network Streams”, the
University of Kansas, December 2012
13. Meenakshi Mishra, PH. D., “Task Relationship Modeling in Lifelong Multitask Learning”,
The University of Kansas, August 2015
Graduated M.S. Students:
14. 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
15. Fei Seak Lei, M.S. in Computer Science, “Toward Efficient Active-Site Based Protein
Functional Annotation”, Master Thesis, the University of Kansas, May 2008
16. 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
17. 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
18. 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
19. Yuanliang Meng, M.S. in Computer Science, “Building an Intelligent Knowledgebase of
Brachiopod Paleontology”, Master Thesis, the University of Kansas, August 2012, coadvised with Brian Potetz
20. 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
21. Sreenivas Kumar Vekapu, M.S. in Computer Science, “Chemocaffe: A platform providing
Deep Learning as a service to cheminformatics researchers”, Master Project, the University
of Kansas, June 2016
Ph.D. Dissertation Committee Memberships:
22. Sandhya Beldona, Ph.D. in Computer Science, 2008
23. 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
24. 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
25. Alexander Senf, Ph.D. in Computer Science, “A Machine Learning Approach to Query TimeSeries Microarray Data Sets for Functionally Related Genes Using Hidden Markov Models”,
the University of Kansas, January 2011
26. 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
27. Jong Cheol Jeong, Ph.D. in Bioengineering, “New Methodology for Measuring Semantic
Functional Similarity Based on Bidirectional Integration”, the University of Kansas, April
7
2013
28. Martin Kuehnhausen, Ph.D. in Computer Science, “A Framework for Knowledge Derivation
Incorporating Trust and Quality of Data”, the University of Kansas, August 2013
29. Meeyoung Park, Ph.D. in Computer Science, “HealthTrust: Assessing the Trustworthiness of
Healthcare Information on the Internet”, the University of Kansas, October 2013
30. Brock Charles Roughton, Ph.D. in Chemical Engineering, “Development of Computer-Aided
Molecular Design Methods for Bioengineering Applications”, the University of Kansas,
December 2013
31. Ashwin Shikaripur Nadig, Ph.D. in Computer Science, “Statistical Approaches to Inferring
Object Shape From Single Images”, the University of Kansas, May 2014
32. Yuhao Yang, Ph.D. in Computer Science, “Protecting attributes and contents in online social
networks”, the University of Kansas, August 2014
33. 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
34. Guannan Hu, Ph.D. in Mathematics, “Fractional diffusion in Gaussian noisy environment”,
the University of Kansas, August 2015
M.S. Thesis/Project Committee Memberships:
35. Vandana Samala, M.S. in Computer Science, 2007
36. Theertham Bhargav, M.S. in Computer Science, 2007
37. Kannan Chandrasekaran, M.S. in Computer Science, 2007
38. Supriya Vasudevan, M.S. in Computer Science, 2008
39. Wasikowski (KU EECS) 2009
40. Ashwini Shikaripur Nadig, M.S. in Computer Science, 2010
41. 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
42. David Tai, M.S. in Computer Science, "Software for Supporting Large Scale Data Processing
for High Throughput Screening", the University of Kansas, December 2011
43. Kriti Chakdar, M.S. in Computer Science, “Cancer Detection For Low Grade Squamous
intraepithelial lesion”, Master Thesis, the University of Kansas, August 2012
44. Hyuntaek Oh, M.S. in Bioengineering, “Bayesian Ensemble Learning for Medical Image
Denoising”, Master Thesis, the University of Kansas, August 2012
45. Manogna Thimma, M.S. in Computer Science, “Hybrid approach for XML access control
(HyXAC)”, Master Thesis, the University of Kansas, July 2012
46. Gianpierre Villagomez Saldana, M.S. in Computer Science, “Exploration of Large Data Sets
in Mobile Devices”, Master Project, the University of Kansas, May 2012
47. Yingying Ma, M.S. in Computer Science, “A Comparison of Two Discretization Options of
the MLEM2 algorithm”, Master Thesis, May 2014
48. Rama Subramanian Krishnamoorthy, M.S. in Computer Science, “Adding Collision
Detection to Functional Active Programming”, Master Project, January 2015
49. Venu Gopal Reddy Bommu, M. S. in Computer Science, “Performance analysis of various
implementations of machine learning algorithms”, Master Project, May 2015
50. 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
51. 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
52. Anirudh Narasimman, M. S. in Computer Science, “Arcana: Private Tweets on a Public
Microblog Platform”, M. S. in Computer Science, Master Thesis, May 2016
8
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, 2013-2016
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
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
9
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
Federal Government:
29. Committee Member and Subcommittee Chair (Data Science Research), Working Group on
Harnessing Data for 21st Century Science and Engineering, National Science Foundation, 20162017
30. Committee Member, Graduate Education Implementation Group, National Science Foundation,
2016
PROFESSIONAL ACTIVITIES
Panelist:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Panelist, NIH, March 2016
Panelist, NIH, October 2015
Panelist, NSF, Division of Information and Intelligent Systems, May 2015
Panelist, Biotechnology and Biological Sciences Research Councile, UK
Panelist, NASA Advanced Information Systems Technology (AIST, ROSES-14), San Diego,
CA, October 2014
Panelist, NSF Division of Information and Intelligent Systems, July 2014
Panelist, NIH, July 2014
Panelist, NSF Division of Information and Intelligent Systems, March 2014
Panelist, NIH, April 2014
Panelist, NSF Division of Biological Infrastructure, October 2013
Panelist, NASA Advanced Information Systems Technology (AIST, ROSES-11), San Diego,
CA, October 2011
Panelist, NSF Division of Information and Intelligent Systems, Washington DC, October 2011
Reviewer, NSF Division of Computing and Communication Foundations , 2009
Panelist, NASA Advanced Information Systems Technology (AIST, ROSES-08), College
Station, MD, October 2008
International Journals
15. Associate Editor, the Liebert Big Data Journal, 2014- present
16. Founding Associate Editor, the AIMS International Journal of Big Data and Information
Analytics, 2014 - present
17. Associate Editor, OA Bioinformatics, OA Publishing London, 2013- present
18. Editorial Board Member, PeerJ Computer Science, 2015-present
19. Editorial Board Member, Elsevier Journal of Big Data Research, 2014 – present
20. Editorial Board Member, Springer Journal of Big Data, 2013 – present
21. Editorial Board Member, International Journal of Data Mining and Bioinformatics (IJDMB),
2011 – present
22. Executive Editorial Board Member (North America), Journal of Pharmacogenomics &
Pharmacoproteomics, 2011 – present
23. Contributing Editor, American Journal of Bioinformatics, 2011 - present
24. Advisory Board Member, Journal of Combinatorial Chemistry and High Throughput Screening,
2009 – present
25. Guest Editor, Special Issue of IEEE/ACM Transactions on Computational Biology and
Bioinformatics for IEEE International Conference on Bioinformatics & Biomedicine, 2010
10
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
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
11
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
Management , Qingdao, China, June 2015
Program Committee Member, thePacific-Asia Conference on Knowledge Discovery and Data
Mining , Ho Chi Minh, Vietnam, May 2015
Program Committee Member, the 2015 SIAM International Conference on Data Mining
(SDM15) , Vancouver, Canada, March 2015
Program Committee Member, the IEEE International Conference on Tools with Artificial
Intelligence (ICTAI'14) , Limassol, Cyprus, November 2014
Program Committee Member, the ACM International Conference on Information and
Knowledge Management (CIKM'14) , Shanghai, China, November 2014
Program Committee Member, the IEEE International Conference on Data Science and
Advanced Analytics (DSAA'14) , Shanghai, China, October 2014
Program Committee Member, the IEEE 14th International Conference on BioInformatics and
BioEngineering (BIBE'14) , Boca Raton, USA, November 2014
Program Committee Member, the 2014 IEEE International Conference on Bioinformatics and
Biomedicine (BIBM'14) , Belfast, UK, November 2014
Program Committee Member, the 5th ACM Conference on Bioinformatics, Computational
Biology and Health Informatics (ACM BCB) , Newport Beach, CA, September 2014
Program Committee Member, the 3rd IEEE International Conference on Big Data Science and
Engineering (BDSE'14) , Beijing, China, September 2014
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
Program Committee Member, the 20th ACM International Conference on Knowledge Discovery
and Data Mining (KDD'14) , New York City, August 2014
Program Committee Member, the 3rd IEEE International Congress on Big Data , Anchorage,
Alaska, June 2014
Program Committee Member, the 15th International conference on Web-Age Information
Management , Macau, China, June 2014
Program Committee Member, the International Conference on Machine Learning (ICML 2014) ,
Beijing, China, June 2014
Program Committee Member, the Pacific-Asia Conference on Knowledge Discovery and Data
Mining (PAKDD 14) , May 2014
Program Committee Member, the Second ASE International Conference on Big Data Science
and Computing , Stanford, CA, May 2014
Program Committee Member, the SIAM International Conference on Data Mining (SDM) ,
Philadelphia, PE, April 2014
Program Committee Member, the Twelfth Asia Pacific Bioinformatics Conference (APBC'14) ,
Shanghai, China, January 2014
Program Committee Member, the IEEE International Conference on Bioinformatics and
Biomedicine (BIBM'13), Shanghai, China, December 2013
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
Program Committee Member, the 2013 IEEE International Conference on Big Data Science and
Engineering, Sydney, Australia, December 2013
Program Committee Member, the 2013 IEEE International Conference on Data Mining
(ICDM'13), Dallas, Texas, December 2013
Program Committee Member, the 22nd ACM International Conference on Information and
Knowledge Management (CIKM 2013) , San Francisco, CA, October 2013
Program Committee Member, the 2013 ASE International Conference on BigData , Washington,
12
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
DC, September 2013
Program Committee Member, the 19th ACM International Conference on Knowledge Discovery
and Data Mining (KDD'13) , Chicago, IL, August 2013
Program Committee Member, the 30th International Conference on Machine Learning
(ICML'13), Atlanta, GA, June 2013
Program Committee Member, the 14th International Conference on Web-Age Information
Management, Beidaihe, China, June 2013
Program Committee Member, the 13th SIAM International Conference on Data Mining
(SDM'13), Austin, TX, USA, May 2013
Program Committee Member, the 17th Pacific-Asia Conference on Knowledge Discovery and
Data Mining (PAKDD'13) , Gold Coast, Australia, April 2013
Program Committee Member, the Eleventh Asia Pacific Bioinformatics Conference (APBC'13) ,
Vancouver, BC, Canada, January 2013
Program Committee Member, the 12th IEEE International Conference on Data Mining
(ICDM'12) , Brussels, Belgium, December 2012
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
Program Committee Member, the 24th IEEE International Conference on Tools with Artificial
Intelligence (ICTAI’12), Athens, Greece, November 2012
Program Committee Member, the IEEE International Conference on Bioinformatics &
Biomedicine (BIBM'12) , Philadelphia, PE, October 2012
Program Committee Member, the 21st ACM Conference on Information and Knowledge
Management (CIKM'12) , Maui, Hawaii, October 2012
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
Program Committee Member, the ACM Conference on Bioinformatics, Computational Biology
and Biomedicine (ACM BCB'12) , Orlando, Florida, October 2012
Program Committee Member, the First International Conference on Global Health Challenges,
Venice, Italy, October 2012
Program Committee Member, The First International Conference on Data Analytics (DATA
ANALYTICS 2012), Barcelona, Spain, September 2012
Program Committee Member, the 18th ACM International Conference on Knowledge Discovery
and Data Mining (KDD'12), Beijing, China, August 2012
Program Committee Member, the ACM International Workshop on Knowledge Discovery from
Sensor Data (Sensor-KDD'12), Beijing, China, August 2012
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
Program Committee Member, the 2012 SIAM International Conference on Data Mining
(SDM'12) , Anaheim, CA, April 2012
Program Committee Member, the 10th Asia Pacific Bioinformatics Conference (APBC'12) ,
Melbourne, Australia, January 2012
Program Committee Member, the 11th IEEE International Conference on Data Mining
(ICDM'11), Vancouver, Canada, December 2011
Program Committee Member, the Tenth IEEE International Conference on Machine Learning
and Applications (ICMLA'11), Honolulu, Hawaii, December 2011
Program Committee Member, the IEEE International Conference on Bioinformatics and
Biomedicine (BIBM'11), Atlanta, Georgia, November 2011
13
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
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
14
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.
2.
3.
4.
Qiang Yu, Hongwei Huo, Ruixing Zhao, Dazheng Feng, Jeffery Vitter, Jun Huan, RefSelect:
a reference sequence selection algorithm for planted (l, d) motif search, BMC bioinformatics,
Vol. 17, No. 9, S37, 2016
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, The Non-Coding RNA Ontology (NCRO): A comprehensive
resource for the unification of non-coding RNA biology, Journal of Biomedical Semantics,
Vol. 7, No. 24, 2016
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, Vol. 15, No. 3, pp. 214-232, 2016
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, Volume 395, pp. 186–193, 2016
15
5.
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.
6.
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
7.
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
8.
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
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.
10.
11.
12.
Jintao Zhang, Jun Huan*, Predicting Drug-Induced QT Prolongation Effects Using MultiView Learning, IEEE Transactions on NanoBioscience , Vol. 12, No. 3, pp. 206-213, 2013
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)
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
13.
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)
14.
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
Jintao Zhang, Genald Lushington, Jun Huan*, The BioAssay Network and Its Implications to
Future Therapeutic Discovery, BMC Bioinformatics, Vol. 12, Suppl 5:S1, 2011
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
15.
16.
17.
18.
19.
20.
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
Meenakshi Mishra, Hongliang Fei, and Jun Huan*, Computational Prediction of Toxicity,
International Journal of Data Mining and Bioinformatics, 2011
Yong Bai, Jun Huan, Seonghoon Kim, Measuring Bridge Construction Efficiency Using the
Wireless Real-time Video Monitoring System, Journal of Management in Engineering, 2011
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
16
21.
Yi Jia, Jun Huan*, Constructing Non-Stationary Dynamic Bayesian Networks with a Flexible
Lag Choosing Mechanism, BMC Bioinformatics, Vol. 11 (Suppl 6):S27, 2010
22.
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
23.
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
24.
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
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.
26.
Deepak Bandyopadhyay, Jun Huan, Jan Prins, Jack Snoeyink, Wei Wang, Alexander
Tropsha,Identification of Family-Specific Residue Packing Motifs and their use for StructureBased Protein Function Prediction, I. Method Development, Journal of Computer-Aided
Molecular Design, Vol. 23, Iss. 11, pp. 773-784, 2009
27.
Deepak Bandyopadhyay, Jun Huan, Jan Prins, Jack Snoeyink, Wei Wang, Alexander
Tropsha, Identification of Family-Specific Residue Packing Motifs and their use for StructureBased Protein Function Prediction: II. Case Studies and Applications, Journal of ComputerAided Molecular Design, Vol. 23, Iss. 11, pp. 785–797, 2009
Aaron Smalter, Jun Huan*, Gerald Lushington, Graph Wavelet Alignment Kernels for Drug
Virtual Screening, Journal of Bioinformatics and Computational Biology, Vol. 7 (3), pp. 473497, 2009
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
28.
29.
30.
31.
32.
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
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
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:
33.
34.
35.
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
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
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
17
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
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
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
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
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
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
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
Jun Huan, Jake Chen, Mohammed Zaki, Proceeding of the 9th International Workshop on
Data Mining in Bioinformatics, BIOKDD 2010, Washington DC, July, 2010
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
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)
Jun Huan, Frequent Subgraph Mining, Encyclopedia of Database Systems, pp. 1170-1175,
Liu & Özsu Eds., Springer, New York, 2009
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:
47.
48.
49.
50.
51.
52.
Chao Lan, Jun Huan, Learning with Positive and Unknown Features, IEEE International
Conference on Bioinformatics and Biomedicine (BIBM’16), Shenzhen China, December
2016, acceptance rate 19% (361 submissions)
Sai Nivedita Chandrasekaran, Jun Huan, Weighted Multi-view Learning for Predicting DrugDisease Associations, IEEE International Conference on Bioinformatics and Biomedicine
(BIBM’16), Shenzhen China, December 2016
Chao Lan, Sai Nivedita Chandrasekaran, Jun Huan, A Distributed and Privatized Framework
for Drug-Target Interaction Prediction, IEEE International Conference on Bioinformatics and
Biomedicine (BIBM’16), Shenzhen China, December 2016
Chao Lan, Xiaoli Li, Yujie Deng, Joseph St. Amand, Jun Huan, A PAC Bound for Joint
Matrix Completion via Partially Collective Matrix Factorization, 23rd International
Conference on Pattern Recognition (ICPR’16), Cancun, Mexico, December 2016
Yujie Deng, Chao Lan, Jun Huan, Co-Regularized Collective Matrix Factorization for Joint
Matrix Completion, 23rd International Conference on Pattern Recognition (ICPR’16),
Cancun, Mexico, December 2016
Xiaoli Li, Jun Huan, aptMTVL: Nailing Interactions in Multi-Task Multi-View Multi-Label
Learning using Adaptive-basis Multilinear Factor Analyzers, ACM International Conference
18
on Information and Knowledge Management (CIKM’16), acceptance rate 165/935=17.6%,
pp. 1171-1180
53.
54.
55.
56.
57.
58.
59.
60.
61.
Joseph St.Amand, Jun Huan, Discriminative View Learning for Single View Co-Training,
ACM International Conference on Information and Knowledge Management (CIKM’16),
Indianapolis, IN, November 2016, pp. 2221-2226
Sai Nivedita Chandrasekaran, Alexios Koutsoukas and Jun Huan, Investigating Multiview
and Multitask Learning Frameworks for Predicting Drug-Disease Associations, The 7th ACM
Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB’16),
Seattle, WA, October 2016, pp. 138-145
Gowtham Kumar, Jun Huan, Jordan Carlson, Developing Novel Machine Learning
Algorithms to Improve Sedentary Assessment for Youth Health Enhancement, IEEE
International Conference on Healthcare Informatics (ICHI’16), Chicago, IL, October 2016,
pp. 375-379
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 (IJCNN’16), Vancouver, Canada, July 2016, pp. 342-347
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 (IJCNN’16), Vancouver, Canada, July 2016, pp. 4082-4088
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’16), New York City, NY, June 2016, acceptance rate 85/275=31%
Hongwei Huo, S Li, Z Sun, Jeffrey Scott Vitter, Xinkun Wang, Qiang Yu, Jun Huan, CS2A:
a compressed suffix array based method for short read alignment, Proceedings of the 2016
IEEE Data Compression Conference (DCC’16), Snowbird, UT, pp. 271-278
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%
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%
62.
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 (SIGKDD’15), Sydney, Australia, August 2015, acceptance rate:
159/869= 18%
63.
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%
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
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
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
64.
65.
66.
19
the IEEE International Conference on Bioinformatics and Biomedicine (BIBM’13), Shanghai,
China, December 2013, pp. 473-476
67.
68.
69.
70.
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
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. 12731282, acceptance rate 146/1088=13%
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%
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 (SIGKDD'12) , Beijing, China, August 2012, pp. 543-551
71.
Jintao Zhang and Jun Huan*, Multi-target protein-chemical interaction prediction using taskregularized and boosted multi-task learning, ACM Conference on Bioinformatics,
Computational Biology and Biomedicine (BCB'12), Orlando, FL, October 2012, pp. 60-67,
acceptance rate 33/159=20%
72.
Jintao Zhang and Jun Huan*, Drug-induced QT Prolongation Prediction Using Coregularized 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%
Xin Huang, Hong Cheng, Jiong Yang, Jeffrey Xu Yu, Hongliang Fei, and Jun Huan, SemiSupervised 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%
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)
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%
73.
74.
75.
76.
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%
77.
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%
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 (BCB'11), Chicago, IL, August
2011, regular paper, acceptance rate 29/153 = 19%
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
78.
79.
20
Data Engineernig (ICDE'11), Hannover, Germany, April 2011, pp. 769-779, regular paper,
acceptance rate 98/494 = 19.8%
80.
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%
81.
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
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%
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
82.
83.
84.
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%
85.
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%
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)
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%
86.
87.
88.
89.
90.
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%
Yi Jia, Jun Huan*, The Analysis of Arabidopsis Thaliana Circadian Network Based on Nonstationary 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%
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
91.
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), SaintPetersburg, Russia, March 2009, pp. 472-480, acceptance rate 92/283 = 32%
92.
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
21
International Conference on Bioinformatics and Biomedicine (BIBM'08), Philadelphia, PA,
December 2008, pp. 199-206, acceptance rate 38/156 = 24%
93.
94.
95.
96.
97.
98.
99.
100.
101.
102.
103.
104.
105.
106.
107.
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%
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
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
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%
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
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
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
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
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
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
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
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 (SIGKDD’04), Seattle, Washington, August 2004, pp. 581-586
J. Huan, W. Wang, D. Bandyopadhyay, J. Snoeyink, J. Prins, A. Tropsha, Mining Familyspecific 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
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
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
22
Parallel Applications on Cluster Architectures, Language and Compilers for Parallel
Computing (LCPC’03), Springer-Verlag, College Station, Texas, October 2003, pp. 194-208
108.
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:
109.
110.
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
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
111.
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
112.
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
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
113.
114.
115.
116.
117.
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
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
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
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
118.
119.
120.
J. Huan, Graph Based Pattern Discovery in Protein Structures, Ph.D. Dissertation, Computer
Science Department, University of North Carolina, 2006
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
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
23
121.
J. Huan, A Localized Clustering Algorithm and Its Application in DNA Sequence Analysis,
Master’s thesis, Computer Science Department, Oklahoma State University, 2000
122.
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
24