Yuda Song

Hi, I am a first-year master student at Machine Learning Department, Carnegie Mellon University . I am currently advised by Kris Kitani and working with Wen Sun. I completed my undergraduate at UCSD with CS and Math double major and I am very fortunate to be advised by Sicun Gao at UCSD.

Email / CV / Github

Research

I am broadly interested in machine learning, especially reinforcement learning. I am interested in developing algorithms with theoretical guarantees and also testing their empirical counterparts in practice. My current focus is on model-based RL, imitation learning and exploration in RL.

Publication

	PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration Yuda Song, Wen Sun ICML, 2021 [code]
	Provably Efficient Model-based Policy Adaptation Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao ICML, 2020 [Project Page] [code]

Teaching Assistant

UCSD CSE291: Topics in Search and Optimization (Winter 2020)

UCSD CSE154: Deep Learning (Fall 2019)

UCSD CSE150: Introduction to AI: Search and Reasoning (Winter 2019, Spring 2020)

UCSD CSE30: Computer Organization and Systems Programming (Spring 2019, Winter 2018)

UCSD CSE11: Introduction to CS & OOP (Fall 2018)

Service

Reviewer: AAAI (2021), ICML (2021), NeurIPS (2021).

Source code from here