People

Rob NowakRobert Nowak (PI) is the McFarland-Bascom Professor of Engineering at the UW-Madison (http://nowak.ece.wisc.edu) and an Adjoint Professor at TTIC. His research interests include interactive machine learning and adaptive sensing. Nowak has received numerous awards for his research, including the 2014 IEEE W. R. G. Baker Award for most outstanding paper in any IEEE publications. Nowak leads the UCoE and the thrust on data efficient ML.

 
 


Yingyu LiangYingyu Liang (senior personnel) is an Assistant Professor in the Computer Sciences Department
at the UW-Madison (http://pages.cs.wisc.edu/ yliang/). Liang works on the theoretical foundations of modern machine learning, including generalization bounds and provable nonconvex optimization and designing efficient algorithms for real world applications involving text and image data. Liang helps coordinating the thrust on adversarial robustness.

 


Mikko LipastiMikko Lipasti (co-PI) is the Philip Dunham Reed Professor of Electrical and Computer Engineering at the UW-Madison (http://pharm.ece.wisc.edu/mikko/). His research focuses on the design of high-performance, low-power, and reliable processor cores; networks-on-chip for manycore processors; and new, biologically-inspired models of computation. He is an IEEE Fellow and an inaugural member of all three Halls of Fame in computer architecture, and has received best paper and Test of Time awards for his research. Lipasti leads the thrust on computational efficiency.
 
 


Karen LivescuKaren Livescu (co-PI) is an Associate Professor at TTIC (http://ttic.edu/livescu). Karen’s main research interests are in speech/natural language processing, learning from multi-modal data, and related machine learning problems. Her work has received several Best Paper and Best Student Paper awards. She is an elected member of the IEEE Spoken Language Technical Committee and an associate editor for IEEE Transactions on Audio, Speech, and Language Processing. Livescu helps coordinate the thrust on operational robustness.
 
 


Dimitris PapailiopoulosDimitris Papailiopoulos (co-PI) is an Assistant Professor of Electrical and Computer Engineering at the UW-Madison (http://papail.io). His research focuses on problems in the intersection of machine learning, coding theory, and distributed systems. He received the 2015 IEEE Signal Processing Society, Young Author Best Paper Award, and is a co-organizer of the new SysML Conference. Papailiopoulos helps coordinate the thrust on computational efficiency.
 
 
 


Greg ShakhnarovichGreg Shakhnarovich (co-PI) is an Associate Professor at TTIC (ttic.edu/gregory). His research interests include computational vision and machine learning, with recent work focusing on self-supervised learning of visual perception. He regularly serves as an Area Chair for flagship computer vision conferences, and is an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence. He has received the IBM Faculty Award in 2013. Greg helps coordinate the thrust on data efficient ML.

 


Rebecca WillettRebecca Willett (co-PI) is an Associate Professor of Electrical and Computer Engineering and Harvey D. Spangler Faculty Scholar at the UW-Madison  (https://willett.ece.wisc.edu). Her research focuses on developing machine learning and signal processing theory and methodology that exploit underlying low-dimensional models, including sparse and low-rank representations of data. Willett has received numerous awards, including the Air Force Office of Scientific Research Young Investigator Program award. Willett leads the thrust on operational robustness.
 
 


Jerry ZhuXiaojin (Jerry) Zhu (co-PI) is the Sheldon & Marianne Lubar Professor in Computer Science at the UW-Madison (http://cs.wisc.edu/ jerryzhu/). His research focuses on machine learning, in particular optimal teaching, active learning, and semi-supervised learning. He is a recipient of a National Science Foundation CAREER Award in 2010 and several best paper awards, and was the co-chair for AISTATS 2017. Zhu  leads the thrust on adversarial ML.
 
 
 


For a broader view of machine learning faculty at UW-Madison go to https://machinelearning.wisc.edu/people/