Lawrence Carin earned the BS, MS and PhD degrees in Electrical Engineering from the University of Maryland in 1985, 1986 and 1989, respectively. Since 1995 he has been with the Electrical and Computer Engineering (ECE) Department at Duke University, where he is now a professor. He held the William H. Younger distinguished professorship from 2003-2014. He was the ECE Department Chairman from 2011-2014, and in July 2014 he became the Vice Provost for Research at Duke. Professor Carin co-founded Signal Innovations Group, Inc. in 2005, and that small business was acquired by BAE Systems in 2014. Professor Carin is a Fellow of the IEEE, and he has published over 300 peer-reviewed papers. His current research interests are in machine learning, with a recent focus on deep learning.
Jun Zhu is an associate professor at Department of Computer Science and Technology, Tsinghua University, and an adjunct faculty at Machine Learning Department, Carnegie Mellon University. He received his Ph.D. in Computer Science from Tsinghua in 2009. Before joining Tsinghua in 2011, he did post-doctoral research in CMU. His research interest lies in developing scalable machine learning methods to understand complex scientific and engineering data. Dr. Zhu has published over 60 peer-reviewed papers in the prestigious conferences and journals. He is an associate editor for IEEE Trans. on PAMI. He served as area chair for ICML, NIPS, UAI, IJCAI and AAAI. He was a local chair of ICML 2014. He is a recipient of the IEEE Intelligent Systems "AI's 10 to Watch" Award, NSFC Excellent Young Scholar Award, and CCF Young Scientist Award. His work is supported by the "221 Basic Research Plan for Young Talents" at Tsinghua.
John Paisley is an assistant professor of Electrical Engineering at Columbia University and is also a member of the Data Science Institute at Columbia. Prior to joining Columbia in 2013, he was a postdoctoral researcher in the Computer Science departments at Princeton University and at the University of California, Berkeley. He received the BSEE (2004) and PhD (2010) degrees in Electrical & Computer Engineering from Duke University. His research interests focus on probabilistic models for machine learning applications, particularly on approximate inference techniques, Bayesian nonparametrics and scalable model learning with variational inference.
Liwei Wang is a professor of School of Electronics Engineering and Computer Sciences, Peking University. He received his PhD from School of Mathematical Sciences, Peking University at 2005; B.S. and M.S. from Department of Electronic Engineering, Tsinghua University at 1999 and 2002 respectively. His research interest is machine learning theory. He was a recipient of the IEEE Intelligent Systems "AI's 10 to Watch" in 2010.
Xiaolin Hu is an Associate Professor in Department of Computer Science and Technology at Tsinghua University. He got his PhD degree of Automation and Computer-Aided Engineering from The Chinese University of Hong Kong in 2007. Then he became a post-doc researcher at the Department of Computer Science and Technology, Tsinghua University. Since 2009, he has been a faculty member of this department. His current research interests include artificial neural networks and computational neuroscience. On one side, He is trying to integrate more neuroscience knowledge into deep learning models for boosting their performances for object recognition and detection. On the other side, he is studying the mechanisms of sensory information processing and decision in the brain using computational models (including deep learning) and functional magnetic resonance imaging (fMRI) technique. He has published over 30 papers in top-tier journals and conferences including IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Image Processing, Neural Computation, Journal of Neurophysiology, CVPR and NIPS. He is an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems.
David Carlson is a postdoctoral researcher at Duke University in the department of Electrical and Computer Engineering and the department of Psychiatry and Behavioral Science. He has previously completed postdoctoral training at the Data Science Institute and the Department of Statistics at Columbia University, New York, NY. He received the B.S.E, M.S, and Ph.D. degrees in electrical and computer engineering from Duke University in Durham, NC in 2010, 2014, and 2015, respectively. His research interests involve using machine learning to perform data-driven science, neuro statistics, optimization, and statistical inference.
Finale Doshi-Velez is an Assistant Professor in the School of Engineering and Applied Sciences (SEAS) at Harvard University. She completed her PhD at MIT and her MSc as a Marshall Scholar at the University of Cambridge. Her core research in machine learning, computational statistics, and data science is inspired by---and often applied to---the objective of accelerating scientific progress and practical impact in healthcare and other domains. She was an NSF CI-TRaCS Postdoctoral Fellow at the Center for Biomedical Informatics at Harvard Medical School, a recipient of the IEEE Intelligent Systems "AI's 10 to Watch" Award in 2013, and was selected as one of IJCAI's Early Career spotlights in 2016.
David Wipf is a lead researcher with the Visual Computing Group at Microsoft Research. He completed his Ph.D. at the University of California, San Diego as an NSF Fellow in Vision and Learning in Humans and Machines. Subsequently he was an NIH Postdoctoral Fellow at the University of California, San Francisco working on Bayesian estimation as applied to the problem of finding sparse representations of signals using overcomplete (redundant) dictionaries of candidate features. In 2011, he joined the Visual Computing Group at Microsoft Research in Beijing.
Minlie Huang now is an associate professor of Dept. of Computer Science and Technology, Tsinghua University. He received his PhD degree in 2006. He was awarded “Tsinghua Excellent Researcher Fellowship” in 2006 and was selected by “Beijing Century Young Elite Program” in 2013. His research interests include artificial intelligence, deep learning, natural language processing, sentiment understanding, and dialogue systems. He has published 40+ papers on premier conferences such as ACL, AAAI, IJCAI, EMNLP, COLING, KDD, ICDM, CIKM, and highly-impacted journals like ACM Transactions on Information System, Bioinformatics, Genome Biology, JAMIA etc. He served as Senior PC of IJCAI 2017, area chairs for ACL 2016, EMNLP 2014, EMNLP 2011, and reviewers for ACL, IJCAI, AAAI, EACL, COLING, EMNLP, NAACL, CIKM, ICDM, SDM, and reviewers for TOIS, TKDE, TALIP, etc. As principle investigator, he had established many collaborations with industrial companies such as Samsung, Microsoft, HP, Fujitsu, Google, ExxonMobil, and Tencent.