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 automating machine learning in real-world applications, in particular democratizing model learning and tuning for diverse tasks outside the widely-studied vision and language domains. Besides, I’m also interested in studying theories of explainable machine learning.
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
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 Deep RL with nearest neighbor function 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
