Xiaodong He is an Affiliate Professor in the Department of Electrical Engineering
at the University of Washington, Seattle, WA. He is also a 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 70 papers and one book, and has published in Proc. IEEE, IEEE SPM, IEEE/ACM TASLP, ACL, EMNLP, NAACL, CVPR, SIGIR, WWW, CIKM, ICLR 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 a member of ACL.
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)
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
Amittai Axelrod, PhD, 2014. Domain Adaptation for Machine Translation. (co-adv. with Mari Ostendorf)
MSR intern students
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 about my research.