Scholars@Duke
Feng Tian

Feng Tian

Professor of Data Science at Duke Kunshan University
DKU Faculty

Overview

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

MGGA: Universal Perturbations against Deepfake via Multiple Model-based Gradient-Guided Feature Layer Attack

Conference Proceedings of the 1st on Deepfake Forensics Workshop Detection Attribution Recognition and Adversarial Challenges in the Era of AI Generated Media Dff 2025 · October 27, 2025 The application of deepfake models for image editing has become increasingly popular, yet their malicious use poses significant risks. Recent studies using active defense mechanisms achieve satisfactory results while maintaining the forgery model and datas ... Full text Cite

An Adaptive Boundary Material Point Method With Surface Particle Reconstruction

Journal Article Computer Animation and Virtual Worlds · September 1, 2025 The expression of fine details such as fluid flowing through narrow pipes or split by thin plates poses a significant challenge in simulations involving complex boundary conditions. As a hybrid method, the material point method (MPM), which is widely used ... Full text Cite

Image Inpainting Algorithm Based on Structure-Guided Generative Adversarial Network

Journal Article Mathematics · August 1, 2025 To address the challenges of image inpainting in scenarios with extensive or irregular missing regions—particularly detail oversmoothing, structural ambiguity, and textural incoherence—this paper proposes an Image Structure-Guided (ISG) framework that hier ... Full text Cite
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Education, Training & Certifications

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