Feng Tian

Prof Feng Tian focuses his research on machine learning, with particular interest in developing advanced approaches on representation learning and data clustering. He is a prolific researcher with more than 120 papers published in peer-reviewed journals and international conferences, including top-tier venues such as International Conference on Machine Learning (ICML), International Joint Conference on Artificial Intelligence (IJCAI), Association for the Advancement of Artificial Intelligence (AAAI), IEEE Transactions on Cybernetics, IEEE Transactions on Visualization & Computer Graphics and ACM Transactions on Modelling & Computer Simulation. In addition to his research, Prof Tian is deeply committed to teaching and enjoys interacting with students. His teaching interests include programming, data structure, algorithms, machine learning and artificial intelligence. Before joining Duke Kunshan University (DKU), Prof Tian was a faculty member at Bournemouth University in the UK and Nanyang Technological University in Singapore. He holds a B.Eng. and Ph.D. from Xi'an Jiaotong University, China.

Current Appointments & Affiliations

Professor of Data Science at Duke Kunshan University · 2021 - Present DKU Faculty

Chair of the Division of Natural and Applied Sciences of Undergraduate Program at Duke Kunshan University · 2024 - Present DKU Faculty

Recent Publications

A Coordination Optimization Framework for Multi-Agent Reinforcement Learning Based on Reward Redistribution and Experience Reutilization

Journal Article Electronics Switzerland · June 1, 2025 Cooperative multi-agent reinforcement learning (MARL) has emerged as a powerful paradigm for addressing complex real-world challenges, including autonomous robot control, strategic decision-making, and decentralized coordination in unmanned swarm systems. ... Full text Cite

An autonomous differential evolution based on reinforcement learning for cooperative countermeasures of unmanned aerial vehicles

Journal Article Applied Soft Computing · January 1, 2025 In recent years, reinforcement learning has been used to improve differential evolution algorithms due to its outstanding performance in strategy selection. However, most existing improved algorithms treat the entire population as a single reinforcement le ... Full text Cite

Web3D-Based Lightweight Simulation for Mass Evacuation at Transportation Hubs

Conference Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics · January 1, 2025 With urban populations soaring, subway systems have become vital arteries of transportation, necessitating robust safety measures. In light of this, the need for effective fire evacuation strategies in these complex infrastructures is both urgent and criti ... Full text Cite

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Education, Training & Certifications

Xi'an Jiaotong University (China) · 1997 Ph.D.