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Author Information
David Cox (MIT-IBM Watson AI Lab)
Alexander Gray (IBM Corporation)
Alexander Gray serves as VP of Foundations of AI at IBM, and currently leads a global research program in Neuro-Symbolic AI at IBM. He received AB degrees in Applied Mathematics and Computer Science from UC Berkeley and a PhD in Computer Science from Carnegie Mellon University. Before IBM he worked at NASA, served as a tenured Associate Professor at the Georgia Institute of Technology, and co-founded and sold an AI startup in Silicon Valley. His work on machine learning, statistics, and algorithms for massive datasets, predating the movement of "big data" in industry, has been honored with a number of research honors including the NSF CAREER Award, multiple best paper awards, selection as a National Academy of Sciences Kavli Scholar, and service as a member of the 2010 National Academy of Sciences Committee on the Analysis of Massive Data. His current interests generally revolve around the injection of non-mainstream ideas into ML/AI to attempt to break through long-standing bottlenecks of the field.
More from the Same Authors
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2020 Poster: Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations »
Joel Dapello · Tiago Marques · Martin Schrimpf · Franziska Geiger · David Cox · James J DiCarlo -
2020 Spotlight: Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations »
Joel Dapello · Tiago Marques · Martin Schrimpf · Franziska Geiger · David Cox · James J DiCarlo -
2020 : Opening Remarks & Logical Neural Networks »
Alexander Gray -
2020 Expo Workshop: Perspectives on Neurosymbolic Artificial Intelligence Research »
Alexander Gray · David Cox · Luis Lastras -
2020 : Opening Remarks »
David Cox -
2019 Poster: More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation »
Quanfu Fan · Chun-Fu (Richard) Chen · Hilde Kuehne · Marco Pistoia · David Cox -
2019 Poster: ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization »
Xiangyi Chen · Sijia Liu · Kaidi Xu · Xingguo Li · Xue Lin · Mingyi Hong · David Cox