Professor
Zheng Tian
Assistant Professor. He obtained his PhD in Computer Science from University College London (UCL), UK. His doctorate research mainly focuses on multi-agent system, reinforcement learning and generative model. Many of his research results were published on first-class international conferences in related fields such as NeurIPS, AAAI, IJCAI and CoRL. He is the primary member of UCL's EXIT, a team that developed algorithm independent of and parallel with Google Deepmind AlphaGo. He has served as a PC member of NeurIPS, IJCAI, AAAI and other world-renowned conferences, as well as a reviewer of many international journals and conferences such as ACM Computing Surveys, Frontiers of Computer Science, etc.
Research Interests: Reinforcement learning, Multi-agent system, Environmental simulation, Intelligent speech Interaction and AI for art&design applications.
Admissions Major: Computer Science and Technology
Email: tianzheng@shanghaitech.edu.cn
Jun Wang
Distinguished Professor; Professor of the Department of Computer Science at the University of London College (UCL), Director of Internet Science and Big Data Analysis; Doctor of Delft University of Technology in the Netherlands; major researcher in intelligent information systems, including: data mining, computational advertising, recommendation systems, machine learning, reinforcement learning, generative models, etc. Wang Jun has published more than 100 academic papers and he won the best paper award multiple times. He is an internationally recognized expert in computational advertising and intelligent recommendation systems. (video)
Research Interests: Machine Learning, Multi-agent artificial intelligence and reinforcement learning, Generative models and the Fusion of artificial intelligence and art, etc.
Admissions Major: Computer Science and Technology
Email: wangjun@shanghaitech.edu.cn
Lab Students
Ruiqing Chen (Master's degree, 2019)
Graduate School：Anhui University/Computer Science and Technology
Research Direction：Active reasoning, multi-intelligence reinforcement learning
Research Interests：Research: active inference is a Bayesian approach that uses change inference for both perception and planning, two functions that maintain a natural consistency with the structure of an autoencoder. A Transformer-based model is proposed that treats active inference as a large-sequence modeling problem, with the expectation that the model outperforms other baselines in offline multitasking environments.
Wenbin Song (Master's degree, 2020)
Graduate School：University of Shanghai for Science and Technology/Electrical Engineering and Automation
Research Direction：Reinforcement learning and autonomous robot navigation
Research Interests：Traditional robot navigation algorithms generate future local trajectories by solving optimization problems with constraints, but this may suffer from complex modeling and time-consuming solving. By using reinforcement learning, a set of intelligent planning and obstacle avoidance strategies can be autonomously trained in a simulation environment and directly migrated to run on a physical robot, which has the advantages of flexible use and fast inference.
Yu Cheng (Master's degree, 2020)
Graduate School：ShanghaiTech University / Computer Science and Technology Program
Research Direction：Speech Synthesis and Audio Editing
Research Interests：Synthesize speech with high fidelity, model speaker's intonation and voice style, and pursue richer rhythmic features while synthesizing smooth speech stably; efficient audio editing tools make editing audio as fast and convenient as editing copy.
