Junhong Shen
1st-Year Ph.D. Student in Machine Learning
Carnegie Mellon University
I’m a first-year Ph.D. student in the Machine Learning Department at CMU, advised by Ameet Talwalkar. My current research focuses on automated machine learning (AutoML), in particular building practical and easily accessible model development tools for diverse applications in real life.
I obtained my B.S. in Mathematics of Computation at UCLA, where I was fortunate to work with Dr. Lin Yang on sample-efficient reinforcement learning. I also studied multi-agent RL and Theory of Mind, advised by Professor Song-Chun Zhu and Professor Ying Nian Wu.
Recent Updates
04/2022: Check out our new work on NAS for diverse tasks!
09/2021: Our work on Iterative Teacher-Aware Learning is accepted by NeurIPS 2021!
05/2021: I'll be joining CMU this Fall as a Machine Learning Ph.D. student!
01/2021: Mathematical Reconstruction of Patient-Specific Vascular Networks is accepted for publication!
12/2020: Our work on accelerating RL with nearest neighbor approximation is accepted by AAAI 2021! Check out the code and slides.
Interests
- AutoML and Interpretable ML
- Reinforcement Learning and Control
Education
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Doctor of Philosophy, Machine Learning
Carnegie Mellon University, 2021 - present
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B.S. in Mathematics of Computation (GPA 4.0/4.0)
University of California, Los Angeles, 2017 - 2021
