Xiaodong He

Xiaodong He

Affiliate Professor

Box 352500

Department of Electrical Engineering

University of Washington

Seattle, WA 98195

E-mail: xiaohe@washington.edu

Link to my latest publications and research.


Xiaodong He is an Affiliate Professor in the Department of Electrical Engineering at the University of Washington, Seattle, WA. He is also a Principal Researcher at Microsoft Research, Redmond, WA. He received the B.S. degree from Tsinghua University (Beijing) in 1996, M.S. degree from Chinese Academy of Sciences (Beijing) in 1999, and the Ph.D. degree from the University of Missouri - Columbia in 2003.

His research interests lie in the area of artificial intelligence, including deep learning, speech, natural language, computer vision, information retrieval, and knowledge representation & management. He has authored/co-authored more than 100 papers and one book, and has published in ACL, CVPR, SIGIR, WWW, CIKM, NIPS, ICLR, IEEE TASLP, Proc. IEEE, IEEE SPM and other venues. He and colleagues developed the MSR-NRC-SRI entry and the MSR entry that won No. 1 in the 2008 NIST Machine Translation Evaluation and the 2011 IWSLT Evaluation (Chinese-to-English), respectively, and the MSR image captioning system that won the 1st Prize in the MS COCO Captioning Challenge 2015.

He has held editorial positions on several IEEE Journals, served as an area chair for NAACL-HLT 2015, and served in the organizing committee/program committe of major speech and language processing conferences. He is an elected member of the IEEE SLTC for the term of 2015-2017. He is a senior member of IEEE and Chair of the IEEE Seattle Section in 2016.

News & Activities

Amittai Axelrod graduated in August 2014 (co-adv. with Mari Ostendorf, group photo and ceremony!) Amittai is now a postdoc with University of Maryland.

Our MSR entry won the 1st Prize, tie with Google, in the MS COCO Captioning Challenge 2015, generated the most captions that pass the Turing Test. See the CVPR paper, demo, and recent media coverage: MS blog, TechNet, SlashGear, etc.

Lecture at UW/EE Research Colloquium Series , on the topic of Towards Deep Understanding: Deep Learning for Selected Natural Language Applications, on Oct. 14, 2014. (slides and video record)

Lecture at UW/EE517: Statistical Language Processing -- Continuous Space Methods, on Feb. 19, 2015.

Lecture at UW/ISE Seminar Series, on the topic of Deep Learning: for Machines to Understand Human Languages, on Feb. 24, 2015.

Invited talk at the CVPR DeepVision workshop on Deep semantic learning: teach machines to understand text, image, and knowledge graph, on June 11, 2015, at Boston.

Our speech-to-speech translation system is demostrated by Rick Rashid during his keynote in Tianjin at MSRA’s 21 Century Computing Conference on October 25, 2012 (New York Times report)

Academic Services

Chair, IEEE Seattle Section. 2016

Member of the IEEE Speech and Language Processing Technical Committee (SLTC) 2015-2017

Area Chair, Spoken Language Processing, NAACL 2015

Associate Editor, IEEE Signal Processing Letters since 2014

Member of the Organizing Committee, Chair of Special Sessions, IEEE ICASSP 2013

Associate Editor, IEEE Signal Processing Magazine since 2012

Guest Editor, Special Issue on Continuous-space and related methods in natural language processing, in IEEE Transactions on Audio, Speech, and Language Processing, 2014

Guest Editor, Special Issue on Large-Scale Optimization for Audio, Speech, and Language Processing, in IEEE Transactions on Audio, Speech, and Language Processing, 2013

Lead Guest Editor, Special Issue on Statistical Learning Methods for Speech and Language Processing, in IEEE Journal of Selected Topics in Signal Processing, 2010

Co-Chair, NIPS 2008 Workshop on Speech and Language: Learning-Based Methods and Systems, Whistler, BC, Canada, 2008

PhD students

Ji He, EE Dept., Deep Reinforcement Learning for Language Understanding. (co-adv. with Mari Ostendorf)

Amittai Axelrod, PhD, 2014. Domain Adaptation for Machine Translation. (co-adv. with Mari Ostendorf)

MSR intern students

Ji He, EE Dept., 2016. Deep Reinforcement Learning for Language Understanding

Hao Cheng, EE Dept., 2015. Deep learning for semantics

Ji He, EE Dept., 2015. Deep generative models

Hao Fang, EE Dept., 2014. Automatic image captioning

Bin Zhang, EE Dept., 2012. Statistical query relaxation models

Amittai Axelrod, EE Dept., 2010 & 2011. Domain adaptation for MT and Topic modeling for SLT

Mei Yang, EE Dept., 2007. System combination for machine translation

Xin Lei, EE Dept., 2005. Feature adaptation for speech recognition

(And students from other universities.)

More Info

More about my research.