Applied research, post-training, reinforcement learning
I am a Senior Director of Applied Research at NVIDIA where I lead post-training teams responsible for Nemotron post-training. Before that I helped grew NVIDIA's NeMo from 1 person (myself) into a multi-team effort.
Before NVIDIA, I worked as applied scientist at Apple, working on AppStore App and Games recommendations. And before that I worked at Microsoft where I wrote first version of GPU backend for CNTK.
I received my Ph.D. (in 2010) an and M.Sc. (in 2009) degrees in Information and Computer Science from University of California, Irvine. My advisor was: Prof. Natasa Przulj. I also go M.Sc. (in 2007) and B.Sc. (in 2005) in Applied Mathematics from National Taras Shevchenko University of Kyiv, Ukraine.
The best way to reach me is via kuchaev at gmail dot com.
Notes on applied research, systems, and modeling.
On August 26, 2026, I had the pleasure of giving a talk at the Mathematics for the Real World 2026 conference, jointly organized by the International Centre for Mathematics in Ukraine (ICMU) and the Centre for Quantum Mathematics (QM) at the University of Southern...
Read postBanning open-source AI would be a historic mistake — and a self-inflicted wound to U.S. AI leadership.I’ve been in this field long enough to remember when GPT-2 was called “too dangerous to release.” That didn’t age well — and it drew heavy criticism from...
Read postWe are likely at the start of a significant paradigm shift in artificial intelligence (AI), comparable to how AlexNet marked the transformative arrival of deep learning in 2012 [1].
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