The Deep and Reinforcement Learning Group at Microsoft Research Asia pushes forward the research of deep learning and reinforcement learning from both algorithmic and practical aspects. Our interests include
- Deep representation learning (opens in new tab), with focus on sequence to sequence learning and applications to machine translation (opens in new tab), speech synthesis (opens in new tab) and recognition, music understanding and composition, pre-training, etc.
- Deep structure learning, with focus on graph neural networks and applications to target discovery (in healthcare), protein modeling, drug design, etc.
- Deep reinforcement learning, with focus on distributional RL and offline RL and applications to logistics and supply chain management, etc.
- Learning to teach and AutoML (opens in new tab), transfer learning, generative models, and causal learning.
Our dual learning (opens in new tab) and other techniques helped Microsoft achieve human parity in Chinese-English (opens in new tab) news translation in 2018, and win the first place for 8 translation tasks (opens in new tab) in WMT 2019. We built the world-best Mahjong AI (opens in new tab), named Suphx (opens in new tab), which achieved 10 DAN on the Tenhou platform in mid 2019. Our FastSpeech (opens in new tab) model is the backbone of Azure TTS (opens in new tab) and has supported 50+ languages/locals and 80+ voices.
People
Tao Qin
Partner Research Manager
Li Zhao
Principal Researcher
Yingce Xia
Principal Researcher
Shufang Xie
Senior Research SDE
Rui Wang
Senior Researcher
Jindong Wang
Senior Researcher
Chang Liu
Senior Researcher
Renqian Luo
Senior Researcher
Guoqing Liu
Senior Researcher
Junliang Guo
Senior Researcher