Yoni Kasten

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

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.

Haoyu Yang

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.

Cooperative Profile Guided Optimization

Existing feedback-driven optimization frameworks are not suitable for video games, which tend to push the limits of performance of gaming platforms and have real-time constraints that preclude all but the simplest execution profiling. While Profile Guided Optimization (PGO) is a well-established optimization approach, existing PGO techniques are ill-suited for games for a number of reasons, particularly because heavyweight profiling makes interactive applications unresponsive.

Charbel Sakr

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.

Sebastian Cammerer

Sebastian Cammerer is a Senior Research Scientist at NVIDIA working on the intersection of wireless communications and machine learning. Before joining NVIDIA, he received his PhD in electrical engineering and information technology from the University of Stuttgart, Germany, in 2021. He is one of the maintainers and core developers of the Sionna open-source link-level simulator. His main research topics are machine learning for wireless communications and channel coding. Further research interests include accelerated computing for wireless signal processing and information theory.