I am a fifth-year Ph.D. student in Computer Science at the University of Maryland, College Park. I work in the Computational Linguistics and Information Processing lab with my advisors Hal Daumé III and Jordan Boyd-Graber. My interests are at the interface between machine learning and natural language processing. I develop machine learning algorithms that can dynamically acquire information and do inference incrementally, with an emphasis on structured prediction problems in natural language processing.

Before joining UMD, I received my B.Eng in Electronic and Information Engineering with a minor in Applied Mathematics at the Hong Kong Polytechnic University, where I worked with Wan-Chi Siu on image super-resolution. In 2010, I spent one semester at the University of Waterloo as an exchange student.




Active Information Acquisition.
He He, Paul Mineiro and Nikos Karampatziakis.
NIPS Workshop on Interactive Machine Learning, 2015
[abstract] [bib] [poster]

Syntax-based Rewriting for Simultaneous Machine Translation.
He He, Alvin Grissom II, John Morgan, Jordan Boyd-Graber and Hal Daumé III.
Empirical Methods in Natural Language Processing (EMNLP), 2015
[abstract] [bib] [slides]

Learning to Search for Dependencies.
Kai-Wei Chang, He He, Hal Daumé III and John Langford.
Arxiv 1503.05615 (preprint), 2015
[abstract] [bib]

Crowdsourcing with Multi-Dimensional Trust. (2nd runner-up for the Tammy L. Blair Award)
Xiangyang Liu, He He and John Baras.
International Conference on Information Fusion (Fusion), 2015
[abstract] [bib]

Trust-Aware Optimal Crowdsourcing With Budget Constraint.
Xiangyang Liu, He He and John Baras.
IEEE International Conference on Communications (ICC), 2015
[abstract] [bib]

Temporal Supervised Learning for Inferring a Dialog Policy from Example Conversations.
Lihong Li, He He and Jason D. Williams.
Spoken Lanugage Technology Workshop (SLT), 2014
[abstract] [bib]

Learning to Search in Branch and Bound Algorithms.
He He Hal Daumé III and Jason Eisner.
Neural Information Processing Systems (NIPS), 2014
[abstract] [bib] [poster]

Don't Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation.
Alvin Grissom II, He He, Jordan Boyd-Graber, John Morgan and Hal Daumé III.
Empirical Methods in Natural Language Processing (EMNLP), 2014
[abstract] [bib]

Dynamic Feature Selection for Dependency Parsing.
He He, Hal Daumé III and Jason Eisner.
Empirical Methods in Natural Language Processing (EMNLP), 2013
[abstract] [bib] [slides] [screencast]

Imitation Learning by Coaching.
He He, Hal Daumé III and Jason Eisner.
Neural Information Processing Systems (NIPS), 2012
[abstract] [bib] [poster]

Besting the Quiz Master: Crowdsourcing Incremental Classification Games.
Jordan Boyd-Graber, Brianna Satinoff, He He and Hal Daumé III.
Empirical Methods in Natural Language Processing (EMNLP), 2012
[abstract] [bib]

Cost-sensitive dynamic feature selection.
He He, Hal Daumé III and Jason Eisner.
ICML Workshop on Inferning, 2012
[abstract] [bib] [slides] [poster]

Single Image Super-resolution using Gaussian Process Regression.
He He and Wan-Chi Siu.
Computer Vision and Pattern Recognition (CVPR), 2011
[abstract] [bib] [slides] [poster]

Rare Class classification with SVM.
He He and Ali Ghodsi.
International Conference on Pattern Recognition (ICPR), 2010
[abstract] [bib] [code]




Co-organizer

NAACL 2015 Tutorial: Hands-on Learning to Search for Structured Prediction.
DARPA Program: Probabilistic Programming for Advancing Machine Learning (Challenge Problem #5: Natural Language Processing)
Mid-Atlantic Student Colloquium on Speech, Language and Learning, 2015

Reviewer

2016: NAACL, ICML
2015: EMNLP, NIPS
2014: NIPS