Speakers

Sanja Fidler is vice president of AI research at NVIDIA, leading the company’s Spatial Intelligence Lab research lab in Toronto. She is also an associate professor at the University of Toronto, and an affiliate faculty member at the Vector Institute, which she co-founded. Previously, she was a research assistant professor at Toyota Technological Institute at Chicago, a philanthropically endowed academic institute located in the University of Chicago campus. Fidler co-authored over 130 scientific papers in the fields of computer vision, machine learning and NLP. She has served as Area Chair for a variety of conferences, including the Conference on Computer Vision and Pattern Recognition (CVPR), International Conference in Computer Vision (ICCV), the Conference on Empirical Methods in Natural Language Processing (EMNLP), the International Conference on Learning Representations (ICLR), the Conference on Neural Information Processing Systems (NeurIPS), and SIGGRAPH.

Jia Deng is a Professor of Computer Science at Princeton University. His research focuses on computer vision and machine learning. He received his Ph.D. from Princeton University and his B.Eng. from Tsinghua University, both in computer science. He is a recipient of the Sloan Research Fellowship, the NSF CAREER award, the ONR Young Investigator award, an ICCV Marr Prize, a CVPR test-of-time award and two ECCV Best Paper Awards. 

James Hays is a professor in the School of Interactive Computing at the College of Computing, Georgia Institute of Technology. His research interests span computer vision, robotics, and machine learning. He works on problems related to recognition, synthesis, and manipulation. His research often involves finding new data sources to exploit (e.g. geotagged imagery) or creating new data sets where none existed (e.g. sketches or grasps). Before joining Georgia Tech, he was the Manning Assistant Professor of Computer Science at Brown University. He was a postdoc at MIT with Antonio Torralba, completed his Ph.D. at Carnegie Mellon University with Alexei Efros, and received his B.S. from Georgia Tech. He is the recipient of the Alfred P. Sloan Fellowship, the NSF CAREER award, the PAMI Mark Everingham Prize, and the ECCV Koenderink Prize.

Francesco Ferroni is a principal researcher at NVIDIA. His current interests are multi-modal models (i.e. text+vision), zero/few-shot and open-set learning, and NeRFs. Prior to NVIDIA, he was a software engineering manager at ArgoAI, where he led multiple teams working on computer vision and machine learning for autonomous vehicles, primarily in the context of onboard perception and mapping/localization. He enjoys being at the interface of large-scale engineering projects and cutting edge academic research. He has a track record of delivering innovative solutions to machine learning problems, either embedded in robots or in the cloud.

Ishan Misra is a Director, Research Scientist in the TBD Labs research division at Meta's SuperIntelligence group. He works on computer vision and machine learning research specifically in generative AI and representation learning. Previously he was at the GenAI group at Meta where he led the research efforts on video generation models. He was the tech lead for Meta's Movie Gen project for foundation models in video generation, video editing, video personalization, and audio generation. Prior to GenAI, He worked at FAIR in Meta on self-supervised learning in computer vision and multimodal learning. He got his PhD at Carnegie Mellon University.

Bryan Wilder is an Assistant Professor in the Machine Learning Department at Carnegie Mellon University. He studies the foundations of machine learning in social, policy, and healthcare settings, blending new methodology with field evaluations to improve AI’s societal impact. His work is shaped by collaborations with governments, nonprofits, health systems, and other partners. At CMU, he directs the Lab for AI and Social Impact. The research has been funded by Schmidt Sciences, NSF, NIH, CDC, the Engler Family Foundation, and ARO. He completed his PhD in Computer Science at Harvard University. Before joining CMU, he was a postdoctoral Schmidt Science Fellow at the Harvard School of Public Health. He serves as Chair of the Board of Directors for EAAMO and the associated ACM EAAMO conference.