I am a research scientist associated with the autonomous vehicle research group at Nvidia. I'm interested in planning and decision making of safety-critical autonomous systems and multi-agent systems.  

Hello! I joined NVIDIA Research in July 2021 after completing my PhD at Carnegie Mellon University. My research interests are in designing architecture support for optimizing sparse, irregular workloads (for example, graph analytics). More information about my research can be found at my website (https://bvignesh.github.io/)

Publications at NVIDIA

Yoni Kasten joined NVIDIA Research in July 2021. 

His research is mostly in the domain of 3D computer vision (e.g. Camera Localization, Structure From Motion and 3D reconstruction) and has recently focused on deep neural models for computer vision problems that involve geometry.

Yoni completed his Ph.D. under the supervision of Prof. Ronen Basri at the Weizmann Institute in Israel. Prior to that, he completed his M.Sc. with Prof. Shmuel Peleg and Prof. Michael Werman from the Hebrew University of Jerusalem, Israel. 

Jakob Hoydis is a Distinguished Research Scientist at NVIDIA working on the intersection of machine learning and wireless communications. Prior to this, he was Head of a research department at Nokia Bell Labs, France, and co-founder of the social network SPRAED. He obtained the diploma degree in electrical engineering from RWTH Aachen University, Germany, and the Ph.D. degree from Supéléc, France.

I'm currently a Research Scientist at NVIDIA Research, where I actively conduct research on computational lithography and machine learning. Prior that, I was a postdoctoral fellow in the Department of Computer Science and Engineering, the Chinese University of Hong Kong. My research interests include (1) Machine Learning in VLSI Design for Manufacturability (2) High Performance VLSI Physical Design with Parallel Computing and (3) Machine Learning Security.

Check my personal webpage for more details.

Charbel Received his PhD (2021) from the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. His research interests are in resource-constrained machine learning, with a particular focus on analysis and implementation of reduced precision models and algorithms and their co-design with machine learning accelerator hardware.