Research and industry experience Publications Teaching
I am a graduate student in the Machine Learning PhD program at the Georgia Institute of Technology, advised by Prof. Hongyuan Zha and mentored by Prof. Tuo Zhao.
I received my MS in Computer Science from Georgia Tech, and completed my BS in EECS with High Honors at UC Berkeley.
- Machine Learning
- Deep reinforcement learning and multi-agent reinforcement learning
- Mean field games
- Precision medicine
- Modeling macroscopic population behavior
- Learning to Incentivize Other Learning Agents. Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes, Hongyuan Zha. Neural Information Processing Systems (NeurIPS), 2020.
Code Emergent division of labor
- GraphOpt: Learning Optimization Models of Graph Formation. Rakshit Trivedi, Jiachen Yang, Hongyuan Zha. International Conference on Machine Learning (ICML), 2020.
- Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery. Jiachen Yang, Igor Borovikov, Hongyuan Zha. International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020.
Code STS2 simulator code
- Integrating Independent and Centralized Multi-Agent Reinforcement Learning for Traffic Signal Network Optimization. Zhi Zhang, Jiachen Yang, Hongyuan Zha. International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS, extended abstract), 2020.
- Single Episode Policy Transfer in Reinforcement Learning. Jiachen Yang, Brenden Petersen, Hongyuan Zha, Daniel Faissol. International Conference on Learning Representations (ICLR), 2020.
- CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning. Jiachen Yang, Alireza Nakhaei, David Isele, Hongyuan Zha, Kikuo Fujimura. International Conference on Learning Representations (ICLR), 2020.
Code Example policy
- Learning Deep Mean Field Games for Modeling Large Population Behavior.
Jiachen Yang, Xiaojing Ye, Rakshit Trivedi, Huan Xu, Hongyuan Zha. International Conference on Learning Representations (ICLR), 2018. Oral presentation (top 2%)
- Fake News Mitigation via Point Process Based Intervention. Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit Trivedi, Elias Khalil, Shuang Li, Le Song, Hongyuan Zha. International Conference on Machine Learning (ICML), 2017.
Research and Industry Experience
Georgia Institute of Technology
- Graduate Research Assistant
- Multi-agent reinforcement learning and transfer learning
DeepMind, DMG Research team
- Learning to incentivize in multi-agent reinforcement learning
Electronic Arts, Data & AI
- Hierarchical multi-agent reinforcement learning
Lawrence Livermore National Laboratory
- Deep reinforcement learning for precision medicine
Honda Research Institute (USA)
- Multi-agent reinforcement learning
- Mixed-Signal Product Engineer
- Behavioral modeling and automated characterization of Phase-Locked Loops
Teaching and Mentoring
- Deep Learning - Georgia Tech CS7643 - Spring 2020
- Machine Learning - Georgia Tech 7641 (OMSCS) - Fall 2017
- Data and Visual Analytics - Georgia Tech CSE 6242 (OMSCS) - Spring 2017
- NSF Graduate Research Fellowship (2018) - Honorable Mention
- Publix Atlanta Half Marathon 2020 - first half marathon in 1:26:07, on ~10mpw
- San Francisco Marathon 2015 - first marathon in 3:23:51, on < 20mpw