Professor at University of Texas at Austin, USA

Kristen Grauman is a Professor in the Department of Computer Science at the University of Texas at Austin and a Research Director in Facebook AI Research (FAIR). Her research in computer vision and machine learning focuses on video, visual recognition, and embodied perception.

Before joining UT-Austin in 2007, she received her Ph.D. at MIT. She is an IEEE Fellow, AAAI Fellow, Sloan Fellow, and recipient of the 2013 Computers and Thought Award. She was inducted into the UT Academy of Distinguished Teachers in 2017. She and her collaborators have been recognized with several Best Paper awards in computer vision, including a 2011 Marr Prize and a 2017 Helmholtz Prize (test of time award).

She served as an Associate Editor-in-Chief for the Transactions on Pattern Analysis and Machine Intelligence (PAMI) and a Program Chair of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2015 and Neural Information Processing Systems (NeurIPS) 2018.

Assistant Professor at IIIT Hyderabad, India

Makarand Tapaswi is an Assistant Professor at the Computer Vision group at IIIT Hyderabad, India. His academic research interests revolve around machine understanding of videos and language. He enjoys working with movies and TV series, especially teaching machines about human behavior and analyzing storylines. Two large projects from his past are MovieGraphs and MovieQA. Other topics such as clustering and identifying characters in videos, a crucial building block for high-level understanding, continue to remain a favorite problem.

Previously, Makarand was a PostDoctoral Fellow at Inria Paris, working in the Willow group with Ivan Laptev and Josef Sivic. Before that he was with the Machine Learning group at the University of Toronto and the Vector Institute, working with Sanja Fidler. Makarand completed his PhD at the Computer Vision for Human Computer Interaction (CVHCI) lab at the Karlsruhe Institute of Technology, Germany, advised by Rainer Stiefelhagen.