[Google Scholar] [Twitter] [Github]

Contact: yangyic@NVIDIA.com / yangyichen6666@gmail.com

I’m a research scientist at NVIDIA working on agentic coding, with a focus on two problems: long-horizon bug fixing in large, complex repositories and long-running, end-to-end software engineering such as ML engineering, building products from scratch, and autoresearch.

I received my CS Ph.D. from UIUC (Advisor: Prof. Heng Ji)

Experience / Education

• NVIDIA, Research Scientist; 2025-Present

• University of Illinois Urbana-Champaign, Ph.D. in Computer Science; 2022-2025

• Huazhong University of Science and Technology, BS in Software Engineering; 2018-2022

Recent Work (2026)

[Full Publications]

^* indicates equal contribution

• Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning [paper]
  Contribute to Agentic Post-Training
  Technical Report

• Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation [paper]
  Zhuolin Yang^*, Zihan Liu^*, Yang Chen^*, Wenliang Dai^*, Boxin Wang^*, Chankyu Lee, Sheng-Chieh Lin, Yangyi Chen, Dongfu Jiang, Jiafan He, Renjie Pi, Grace Lam, Nayeon Lee, Alexander Bukharin, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping^*
  Technical Report

• Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning [paper]
  Contribute to SWE-Agents RL
  Technical Report

• Nemotron-Cascade: Scaling Cascaded Reinforcement Learning for General-Purpose Reasoning Models [paper]
  Boxin Wang^*, Chankyu Lee^*, Nayeon Lee^*, Sheng-Chieh Lin^*, Wenliang Dai^*, Yang Chen^*, Yangyi Chen^*, Zhuolin Yang^*, Zihan Liu^*, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping^* (ordered alphabetically by first name with equal technical contribution^*)
  NeurIPS (Oral)