CV

Education

• Ph.D. in Computer Science, UCLA, 2025 (expected)
• B.S. in Automation, Beihang University, 2019
  • GPA: 3.86/4.00
  • rank: 2/175

Work experience

• Fall 2019: Visiting Researcher
  • Star AI Lab, University of California, Los Angeles
  • Research topic: Tractable inference on probabilistic graphical models, and its application on reinforcement learning.
  • Supervisor: Professor Guy Van den Broeck
• Spring 2019: Research Intern
  • Seattle AI Lab, Kwai Inc.
  • Project: User pass rate prediction system for a level-oriented mobile game “joy city”. The system is powered by a game AI using reinforcement learning (RL) and Monte Carlo tree search (MCTS) that achieves master-level performance in the mobile game.
  • Supervisor: Professor Ji Liu and Jianshu Chen

Skills

• Programming languages
  • C/C++, Python, MATLAB, Julia

Publications

Balance Gate Controlled Deep Neural Network

Liu A, Laili Y. "Balance Gate Controlled Deep Neural Network." Neurocomputing. 320(2018) 183-194.

Deep Reinforcement Learning with Analogous Disentangled Exploration

Liu A, Liang Y, Van den Broeck G. "Deep Reinforcement Learning with Analogous Disentangled Exploration." International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) 2020.

Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search (Oral presentation)

Liu A, Chen J, Yu M, Zhai Y, Zhou X, Liu J. "Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search." International Conference on Learning Representation (ICLR), 2020.