Jim C. Huang, Ph.D.


huangjim at amazon dot com


About me

I'm currently a Research Scientist at Amazon, working on applications of machine learning to large-scale behavioral data.

Previously, I co-founded two start-ups and I was a Post-doctoral Researcher in the eScience group at Microsoft Research. I obtained my doctoral degree in 2009 at the University of Toronto.
In 2006, 2008 and 2009, I was a research intern in the Machine Learning & Perception and eScience groups at Microsoft Research in Cambridge, UK and Redmond, WA. My doctoral thesis presents a class of graphical models for joint cumulative distribution functions, called cumulative distribution networks (CDNs), with properties distinct from those of standard graphical modelling frameworks. I have also developed several message-passing algorithms for inference and learning in such graphical models. For more info, take a look below at my papers or at research projects I've worked on.


Projects


Cumulative distribution networks: Graphical models for cumulative distribution functions



Applications of cumulative distribution networks






Using expression profiling data to identify human microRNA targets

Joint work with the Gallie lab (Ontario Cancer Institute/Princess Margaret Hospital),
Blencowe, Hughes and Morris labs (Banting and Best Department of Medical Research, University of Toronto)




Integrating functional genomics data with genetics to help understand human disease

Joint work with John Winn, Anitha Kannan (Microsoft Research Cambridge)
and Richard Durbin, Manolis Dermitzakis (Wellcome Trust Sanger Institute)






Ph.D. thesis

J.C. Huang (2009). Cumulative distribution networks: Inference, estimation and applications of graphical models for cumulative distribution functions.
Department of Electrical and Computer Engineering, University of Toronto.

Papers

J.C. Huang, C. Meek, C. Kadie and D. Heckerman (2011). Conditional random fields for fast, large-scale genome-wide association studies.
PLoS ONE 6(7): e21591. doi:10.1371/journal.pone.0021591

J.C. Huang and N. Jojic (2011). Variable selection by correlation sifting.
Lecture Notes in Bioinformatics, Springer-Verlag 6577: 106-123.
Fifteenth Annual International Conference on Research in Computational Molecular Biology (RECOMB).

J.C. Huang and B. J. Frey (2011). Cumulative distribution networks and the derivative-sum-product algorithm: Models and inference for cumulative distribution functions on graphs.
Journal of Machine Learning Research (JMLR) 12 : 301-348.

J.C. Huang, N. Jojic and C. Meek (2010). Exact inference and learning for cumulative distribution functions on loopy graphs.
Advances in Neural Information Processing Systems (NIPS) 23: 874-882. Supplemental File

T. Hertz, D. Nolan, I. James, M. John, S. Gaudieri, E. Phillips, J.C. Huang, G. Riadi, S. Mallal and N. Jojic (2010). Mapping the landscape of host-pathogen co-evolution: HLA class I-peptide interactions correlate with conservation in human and viral proteins.
Journal of Virology (JVI). doi:10.1128/JVI.01966-10

J.C. Huang and N. Jojic (2010). Modelling Major Histocompatibility Complex binding by nonparametric averaging of multiple predictors and sequence encodings.
Journal of Immunological Methods (JIM). doi:10.1016/j.jim.2010.10.001

J.C. Huang and N. Jojic (2010). Maximum-likelihood learning of cumulative distribution functions on graphs.
Journal of Machine Learning Research (JMLR) W&CP Series 9: 342-349
Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS)
.

J.C. Huang and B.J. Frey (2009). Cumulative distribution networks: Graphical models for cumulative distribution functions.
The Learning Workshop (LEARNING 2009).

N. Jojic, T. Hertz and J.C. Huang (2009). HLA viral targeting.
UCSD Information Theory and Applications Workshop (ITA).

J.C. Huang and B.J. Frey (2009). STORMSeq: A method for ranking regulatory sequences by integrating experimental datasets with diverse computational predictions.
Handbook of Computational Statistics: Statistical Bioinformatics, Springer, eds. Henry Lu, Bernhard Scholkopf and Hongyu Zhao.

J.C. Huang and B.J. Frey (2009). Structured ranking learning using cumulative distribution networks.
Advances in Neural Information Processing Systems (NIPS) 21: 697-704. Supplemental File

J.C. Huang and B.J. Frey (2008). Cumulative distribution networks and the derivative-sum-product algorithm.
Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI), AUAI Press: 290-297.
(Best Student Paper Runner-Up Award)

J.C. Huang, B.J. Frey and Q.D. Morris (2008). Comparing sequence and expression for predicting microRNA targets using GenMiR3.
Pacific Symposium for Biocomputing (PSB) 13: 52-63.

J.C. Huang*, T. Babak*, T.W. Corson, G. Chua, S. Khan, B.L. Gallie, T.R. Hughes, B.J. Blencowe, B.J. Frey and Q.D. Morris (2007).
Using expression profiling data to identify human microRNA targets.
Nature Methods 4: 1045-1049. (*Joint first authors)

J.C. Huang, A. Kannan and J. Winn (2007). Bayesian association of haplotypes and non-genetic factors to regulatory and phenotypic variation in human populations.
Bioinformatics 23: i212-221
Fifteenth Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) &
Sixth European Conference on Computational Biology (ECCB)

J.C. Huang, Q.D. Morris and B.J. Frey (2007). Bayesian inference of microRNA targets from sequence and expression data.
Journal of Computational Biology 14: 550-563.

J.C. Huang, Q.D. Morris and B.J. Frey (2006). Computational discovery of microRNA regulatory networks in retinoblastoma from sequence and expression data.
Sixth Cold Spring Harbor Laboratory/Wellcome Trust (CSHL/WT) Conference on Genome Informatics.

J.C. Huang, Q.D. Morris and B.J. Frey (2006). Detecting microRNA targets by linking sequence, microRNA and gene expression data.
Lecture Notes in Computer Science, Springer-Verlag 3909: 114-129.
Tenth Annual International Conference on Research in Computational Molecular Biology (RECOMB).

J.C. Huang, Q.D. Morris, T.R. Hughes and B.J. Frey (2005). GenXHC: A probabilistic generative model for cross-hybridization compensation in high-density, genome-wide microarray data.
Bioinformatics 21: i222-i231.
Thirteenth Annual International Conference on Intelligent Systems for Molecular Biology (ISMB).

D. Dueck*, J.C. Huang*, Q.D. Morris and B.J. Frey (2004). Iterative analysis of microarray data.
Forty-Second Annual Allerton Conference on Communication, Control and Computing. (*Joint first authors)


Talks and Posters

J.C. Huang, N. Jojic and C. Meek (2010). Exact inference and learning for cumulative distribution functions on loopy graphs.
Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS),
Vancouver, BC, Canada, December 6-9, 2010.

J.C. Huang and N. Jojic (2010). Maximum-likelihood learning of cumulative distribution functions on graphs.
Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS),

Sardinia, Italy, May 12-15 2010.

J.C. Huang and B.J. Frey (2009). Cumulative distribution networks: Graphical models for cumulative distribution functions.
The Learning Workshop (LEARNING 2009),
Clearwater, FL, USA, April 13-16, 2009.

N. Jojic, T. Hertz and J.C. Huang (2009). HLA viral targeting.
UCSD Information Theory and Applications Workshop (ITA),
La Jolla, CA, USA, February 9-13, 2009.

J.C. Huang and B.J. Frey (2008). Structured ranking learning using cumulative distribution networks.
Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS),
Vancouver, BC, Canada, December 8-13, 2008.

J.C. Huang and B.J. Frey (2008). Cumulative distribution networks and the derivative-sum-product algorithm.
Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI),
Helsinki, Finland, July 9-12, 2008.

J.C. Huang, B.J. Frey and Q.D. Morris (2008). Comparing sequence and expression for predicting microRNA targets using GenMiR3.
Pacific Symposium for Biocomputing (PSB),
Big Island, HI, USA, January 4-8, 2008.

J.C. Huang, A. Kannan and J. Winn (2007). Bayesian association of haplotypes and non-genetic factors to regulatory and phenotypic variation in human populations.
Fifteenth Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) & Sixth European Conference on Computational Biology (ECCB),
Vienna, Austria, July 21-25, 2007.

J.C. Huang, Q.D. Morris and B.J. Frey (2006). Computational discovery of microRNA regulatory networks in retinoblastoma from sequence and expression data.
Sixth Cold Spring Harbor Laboratory/Wellcome Trust (CSHL/WT) Conference on Genome Informatics,
Hinxton, Cambridge, UK, September 13-17, 2006.

J.C. Huang, Q.D. Morris and B.J. Frey (2006). Detecting microRNA targets by linking sequence, microRNA and gene expression data.
Tenth Annual International Conference on Research in Computational Molecular Biology (RECOMB),
Venice, Italy, April 2-5, 2006.

J.C. Huang, Q.D. Morris, T.R. Hughes and B.J. Frey (2005). GenXHC: A probabilistic generative model for cross-hybridization compensation in high-density, genome-wide microarray data.
Thirteenth Annual International Conference on Intelligent Systems for Molecular Biology (ISMB),
Detroit, MI, USA, June 25-29, 2005.

J.C. Huang, Q.D. Morris, T.R. Hughes and B.J. Frey (2004). Detection and compensation of cross-hybridization in DNA microarray data.
Third Annual Information Processing Workshop,
Toronto, ON, Canada, August 8, 2004.