Jeffrey A. Bilmes
Jeffrey A. Bilmes is a professor at the Department of Electrical Engineering at the University of Washington, Seattle Washington. He is also an adjunct professor in Computer Science & Engineering and the department of Linguistics. Prof. Bilmes is the founder of the MELODI (MachinE Learning for Optimization and Data Interpretation) lab here in the department. Bilmes received his Ph.D. from the Computer Science Division of the department of Electrical Engineering and Computer Science, University of California in Berkeley. He was also a researcher at the International Computer Science Institute, and a member of the Realization group there.
Prof. Bilmes is a 2001 NSF Career award winner, a 2002 CRA Digital Government Fellow, a 2008 NAE Gilbreth Lectureship award recipient, and a 2012/2013 ISCA Distinguished Lecturer. Prof. Bilmes was a UAI (Conference on Uncertainty in Artificial Intelligence) program chair (2009) and then the general chair (2010). He was also a workshop chair (2011) and the tutorials chair (2014) at NIPS (Neural Information Processing Systems). He is currently an action editor for JMLR (Journal of Machine Learning Research).
Prof. Bilmes's primary interests lie in statistical modeling (particularly graphical model approaches) and signal processing for pattern classification, speech recognition, language processing, bioinformatics, machine learning, submodularity in combinatorial optimization and machine learning, active and semi-supervised learning, and audio/music processing. He is particularly interested in temporal graphical models (or dynamic graphical models, which includes HMMs, DBNs, and CRFs) and ways in which to design efficient algorithms for them and design their structure so that they may perform as better structured classifiers. He also has strong interests in speech-based human-computer interfaces, the statistical properties of natural objects and natural scenes, information theory and its relation to natural computation by humans and pattern recognition by machines, and computational music processing (such as human timing subtleties). He is also quite interested in high performance computing systems, computer architecture, and software techniques to reduce power consumption.
Prof. Bilmes has also pioneered (starting in 2003) the development of submodularity within machine learning, and he received a best paper award at ICML 2013, a best paper award at NIPS 2013, and a best paper award at ACM-BCB 2016, all in this area. In 2014, Prof. Bilmes also received a most influential paper in 25 years award from the International Conference on Supercomputing, given to a paper on high-performance matrix optimization. Prof. Bilmes has authored the graphical models toolkit (GMTK), a dynamic graphical-model based software system widely used in speech, language, bioinformatics, and human-activity recognition.
Current and Recent Past Activities
Long term participant in the Simons Institute for the Theory of Computing, Foundations of Machine Learning Program, 2017
Visiting Scientist at Google Research, Fall 2016
Tutorial Speaker at Computer Vision and Pattern Recognition (CVPR), 2016 Optimization Algorithms for Subset Selection and Summarization in Large Data Sets, June 26th, 2016
Invitation to give the Yale Institute for Network Science (YINS) Distinguished Lecture, May 4th, 2016
Some previous work on musical modeling is apparently gaining some utility for streaming music applications
Invited speaker at the Workshop on Data-driven Algorithmics at Harvard University, September 2015
Invited lecturer at the Non-convex Optimization for Machine Learning (NOML) Summer School, IIT Bombay, India, June 2015
The Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) Senior Program Committee
33rd International Conference on Machine Learning (ICML-2016) Senior Program Committee
Invited lecturer in the IMA workshop Convexity and Optimization: Theory and Applications, February 23 - 27, 2015
Senior Program Committee at UAI 2015
Area Chair at ICML 2015
Co-organizer of the UW-MSR Machine learning workshop, 2015
Giving a tutorial on Submodular Applications in Machine Learning at AAAI-2015
I am co-organizing a NIPS-2014 Workshop on Discrete Optimization in Machine Learning: Structures, Algorithms and Applications (DISCML). Sixth year running.
NIPS 2014 Both Area Chair and the Tutorials Chair
The GMTK 1.0 source code distribution is now available.
A paper I wrote as a graduate student was selected as one of the most influential ICS papers in 25 years, and will be included in the special issue "25 years of International Conference on Supercomputing, 2014"
Tutorial speaker at the Machine Learning Summer School (MLSS) in Reykjavik, Iceland, April 2014.
Senior Program Committee at UAI 2014
Senior Program Committee at AI-STATS 2014
Action editor for Journal of Machine Learning Research (JMLR) 2013-2016
I am co-organizing a NIPS-2013 Workshop on Discrete Optimization in Machine Learning: Structures, Algorithms and Applications (DISCML). Fifth year running.
Invited speaker at International Conference on Learning Representations (ICLR2013) A video of the talk is available here
Faculty Affiliate for the Center For Statistics And The Social Sciences (CSSS)
NIPS 2013 Area Chair
Area chair for the International Conference on Machine Learning (ICML), 2013
I am co-organizing a NIPS 2012 Workshop on Discrete Optimization in Machine Learning: Structures, Algorithms and Applications (DISCML). Forth year running.
Invited speaker at the Modern Aspects of Submodularity workshop at Georgia Tech in March, 2012.
I was selected to be an ISCA Distinguished Lecturer for the 2011/2012 year.
I am a workshop co-chair for NIPS 2011 in Granada, Spain.
I am co-organizing a NIPS 2011 Workshop on Discrete Optimization in Machine Learning: Structures, Algorithms and Applications (DISCML). Third year running.
I am on the Scientific Program Committee of the 2011 Joint ICML/ACL Symposium on Machine Learning in Speech and Language Processing. Deadline submission is April 15th, 2011. Please submit.
I am co-organizing a NIPS 2010 Workshop on Discrete Optimization in Machine Learning: Structures, Algorithms and Applications (DISCML). Submission deadline is Friday October 29, 2010.
I am on the committee for the UAI 2010 Approximate inference evaluation. See here for details.
Starting in March 2010, I began a three-year term as a member of the editorial board of the IEEE Signal Processing Magazine
I am the general chair of the 26th Conference on Uncertainty in Artificial Intelligence in 2010 (UAI2010).
I am on the senior program committee of AAAI-2010. Submission deadline is Jan 18th, 2010.
I am co-organizing a NIPS 2010 workshop on submodularity and discrete optimization in machine learning. The program is here
I am a technical chair of IEEE Automatic Speech Recognition and Understanding (ASRU) in 2009.
Organizer of the Japan-America Frontiers of Engineering Symposium, Kobe Japan, 2008 sponsored by the NAE.
Less Recent Activities
Senior Program Committee: International Conference on Machine Learning (ICML) in 2007
Program Committee: Association for the Advancement of Articial Intelligence (AAAI), 2007.
IEEE Speech Technical Committee, 2003-2007
Program Chair for HLT/NAACL in 2006.
Workshop co-chair for 2005 NIPS workshop on Advances in Structured Learning for Text and Speech Processing
Program committee (2nd year in a row) for Neural Information Processing Systems (NIPS), in 2005
Program committee for Neural Information Processing Systems (NIPS), in 2004
General chair for IEEE Automatic Speech Recognition and Understanding (ASRU), in 2003.
Senior Group member, Johns Hopkins summer workshop on automatic speech recognition in 2002.
Group leader, Johns Hopkins summer workshop on automatic speech recognition in 2001.