Yaser Sheikh

Tuesday, January 8
Machine Perception of Social Signals

Yaser Sheikh is the director of the Facebook Reality Lab in Pittsburgh and is an Associate Professor at the Robotics Institute at Carnegie Mellon University. His research is broadly focused on machine perception of social behavior, spanning computer vision, computer graphics, and machine learning. With colleagues, he has won Popular Science’s “Best of What’s New” Award, the Honda Initiation Award (2010), best student paper award at CVPR (2018), best paper awards at WACV (2012), SAP (2012), SCA (2010), ICCV THEMIS (2009), best demo award at ECCV (2016), and placed first in the MSCOCO Keypoint Challenge (2016); he has also received the Hillman Fellowship for Excellence in Computer Science Research (2004). Yaser has served as a senior committee member at leading conferences in computer vision, computer graphics, and robotics including SIGGRAPH (2013, 2014), CVPR (2014, 2015, 2018), ICRA (2014, 2016), ICCP (2011), and served as an Associate Editor of CVIU. His research is sponsored by various government research offices, including NSF and DARPA, and several industrial partners including the Intel Corporation, the Walt Disney Company, Nissan, Honda, Toyota, and the Samsung Group. His research has been featured by various media outlets including The New York Times, The Verge, Popular Science, BBC, MSNBC, New Scientist, slashdot, and WIRED.


Dhruv Batra 

Wednesday, January 9
A-STAR: Agents that See, Talk, Act, and Reason

Dhruv Batra is an Assistant Professor in the School of Interactive Computing at Georgia Tech and a Research Scientist at Facebook AI Research (FAIR). His research interests lie at the intersection of machine learning, computer vision, natural language processing, and AI, with a focus on developing intelligent systems that are able to concisely summarize their beliefs about the world with diverse predictions, integrate information and beliefs across different sub-components or `modules’ of AI (vision, language, reasoning, dialog), and interpretable AI systems that provide explanations and justifications for why they believe what they believe. In past, he has also worked on topics such as interactive co-segmentation of large image collections, human body pose estimation, action recognition, depth estimation, and distributed optimization for inference and learning in probabilistic graphical models. He is a recipient of the Office of Naval Research (ONR) Young Investigator Program (YIP) award (2017), the National Science Foundation (NSF) CAREER award (2014), Army Research Office (ARO) Young Investigator Program (YIP) award (2014), Outstanding Junior Faculty awards from Virginia Tech College of Engineering (2015) and Georgia Tech College of Computing (2018), two Google Faculty Research Awards (2013, 2015), Amazon Academic Research award (2016), Carnegie Mellon Dean’s Fellowship (2007), and several best paper awards (EMNLP 2017, ICML workshop on Visualization for Deep Learning 2016, ICCV workshop Object Understanding for Interaction 2016) and teaching commendations at Virginia Tech. His research is supported by NSF, ARO, ARL, ONR, DARPA, Amazon, Google, Microsoft, and NVIDIA. Research from his lab has been extensively covered in the media (with varying levels of accuracy) at CNN, BBC, CNBC, Bloomberg Business, The Boston Globe, MIT Technology Review, Newsweek, The Verge, New Scientist, and NPR. From 2013-2016, he was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, where he led the VT Machine Learning & Perception group and was a member of the Virginia Center for Autonomous Systems (VaCAS) and the VT Discovery Analytics Center (DAC). From 2010-2012, he was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), a philanthropically endowed academic computer science institute located on the University of Chicago campus. He received his M.S. and Ph.D. degrees from Carnegie Mellon University in 2007 and 2010 respectively, advised by Tsuhan Chen. In past, he has held visiting positions at the Machine Learning Department at CMU, CSAIL MIT, Microsoft Research, and Facebook AI Research.


Devi Parikh

Wednesday, January 9

Devi Parikh is an Assistant Professor in the School of Interactive Computing at Georgia Tech, and a Research Scientist at Facebook AI Research (FAIR).

From 2013 to 2016, she was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. From 2009 to 2012, she was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), an academic computer science institute affiliated with University of Chicago. She has held visiting positions at Cornell University, University of Texas at Austin, Microsoft Research, MIT, Carnegie Mellon University, and Facebook AI Research. She received her M.S. and Ph.D. degrees from the Electrical and Computer Engineering department at Carnegie Mellon University in 2007 and 2009 respectively. She received her B.S. in Electrical and Computer Engineering from Rowan University in 2005.

Her research interests include computer vision and AI in general and visual recognition problems in particular. Her recent work involves exploring problems at the intersection of vision and language, and leveraging human-machine collaboration for building smarter machines. She has also worked on other topics such as ensemble of classifiers, data fusion, inference in probabilistic models, 3D reassembly, barcode segmentation, computational photography, interactive computer vision, contextual reasoning, hierarchical representations of images, and human-debugging.

She is a recipient of an NSF CAREER award, an IJCAI Computers and Thought award, a Sloan Research Fellowship, an Office of Naval Research (ONR) Young Investigator Program (YIP) award, an Army Research Office (ARO) Young Investigator Program (YIP) award, a Sigma Xi Young Faculty Award at Georgia Tech, an Allen Distinguished Investigator Award in Artificial Intelligence from the Paul G. Allen Family Foundation, four Google Faculty Research Awards, an Amazon Academic Research Award, an Outstanding New Assistant Professor award from the College of Engineering at Virginia Tech, a Rowan University Medal of Excellence for Alumni Achievement, Rowan University’s 40 under 40 recognition, a Forbes’ list of 20 “Incredible Women Advancing A.I. Research” recognition, and a Marr Best Paper Prize awarded at the International Conference on Computer Vision (ICCV).


Blaise AgĂĽera y Arcas

Thursday, January 10
Scaling laws, neural computation, and personal augmentation

Blaise leads an on-device Machine Intelligence program at Google—including both basic research and new products. His group works extensively with deep neural nets for machine perception, distributed learning, machine creativity, and agents, as well as collaborating with academic institutions on computational neuroscience and connectomics research. Until 2014 he was aDistinguished Engineer at Microsoft, where he worked in a variety of roles, from inventor to strategist, and led teams with strengths in interaction design, prototyp-ing, machine vision, augmented reality, wearable computing and graphics. Blaise has given TED talks on Seadragon and Photosynth (2007, 2012), Bing Maps (2010), and machine creativity (2016). In 2008, he was awarded MIT’s TR35 prize.