The AI-Embedded Industry Software Team at the Fudan University Center for Applied Mathematics conducts research across three interconnected pillars: scientific foundations, core algorithms, and application validation. The team focuses on: developing AI fundamentals, theories, and algorithms for CAX (Computer-Aided technologies) kernels in industrial software, addressing mathematical challenges in intelligent computing and decision-making for industrial technologies, advancing digital experimentation techniques and core mathematical modeling/algorithms. Through industry-academia collaboration, the team drives applied mathematics research from practical problems, aiming to develop independently innovated, industry-leading CAX algorithms and software cores.

The team is led by Professor Wenlian LU and includes the following members (in alphabetical order by pinyin surname): WANG Tianyu, WEN Dong, and ZHANG Shuqin.

Team Leader

Prof. Wenlian LU

Professor and Ph.D. Supervisor at Fudan University, Senior Member of the IEEE.

  Prof. Lu' s research focuses on neural networks, computational neuroscience, and complex networks, with long-term contributions to AI, computational neuroscience, and intelligent control of complex network systems. He has developed AI algorithm-based technological innovations and products, advancing both theoretical and applied research in these fields.

He received his Ph.D. in Applied Mathematics from Fudan University and has held key academic positions, including Postdoctoral Researcher at the Max Planck Institute for Mathematics (Germany, 2005–2007) and Visiting Scholar at CUHK, CityU Hong Kong, University of Warwick, RIKEN Brain Science Institute, among others.

Prof. Lu has published over 150 research papers with more than 8,000 citations, demonstrating his significant impact in the field. His major honors include the National Natural Science Award (Second Prize, 5th contributor, 2015), the Natural Science Award (Second Prize, 1st contributor) from the Ministry of Education (2015), the Outstanding Young Researcher Award from the Asia Pacific Neural Network Assembly (2011), the Shanghai Natural Science Award (Second Prize, 2nd contributor, 2008 & 2023), and the National Excellent Doctoral Dissertation Award (2007).

He has led multiple research grants, including as Principal Investigator of NSFC General Projects (2009, 2013, 2017, 2021), Lead Scientist of the National Key R&D Program 'New Generation AI' (2019–present), and recipient of the New Century Excellent Talents Program (2014), Shanghai Rising-Star Program (2011), and Shanghai Pujiang Talent Program (2008).

Additionally, Prof. Lu has fostered strong industry collaborations, leading applied mathematics research projects with State Grid Shanghai Electric Power Company, SAIC Motor, and Shanghai Electric, bridging academic research with real-world applications.

Team Members

WANG Tianyu, Junior Researcher at Shanghai Center for Mathematical Sciences, Fudan University. Prof. Wang's research focuses on machine learning, with publications in top-tier journals and conferences including IEEE Transactions on Information Theory, Journal of Machine Learning Research (JMLR), NeurIPS, and ICML. He received his Ph.D. in Computer Science from Duke University.

WEN Dong, Business Collaboration Director at Center for Applied Mathematics, Fudan University, leading external partnerships with industry ecosystem and government agencies. With 17 years of professional experience including key leadership roles at Huawei (Director of Computing Foundation Software Ecosystem Development, General Manager of Enterprise Shanghai Region) and TCL/Alcatel (APAC Business Director), he has been instrumental in pioneering Huawei's enterprise business in Western Europe and expanding its computing industry ecosystem.

ZHANG Shuqin, Professor and Ph.D. Supervisor at School of Mathematical Sciences, Fudan University. Prof. Zhang's research spans scientific computing, data science and bioinformatics, with publications in Nature Communications, Bioinformatics and PLoS Computational Biology. She holds a Ph.D. from University of Hong Kong and was Visiting Associate Professor at Yale School of Public Health. Her current research projects include NSFC General Program on 'Mixed Non-negative Matrix Factorization Methods for Spatial Transcriptomics Data Analysis' and Shanghai STI Action Plan on 'Mathematical Methods for Heterogeneous Data Integration'.

Current Research Topics：

Fundamental Research in Intelligent Science

• Brain-Inspired Computational Frameworks

• Hybrid Optimization and Reinforcement Learning Algorithms

• Mathematical Methods for Heterogeneous Data Integration

Core AI Algorithm Development for Industrial Software

• Computational Graphics and Geometry Based on AI Methods

• Physics Simulation Models (Fluid/Aerodynamics) Using Neural Operators

• Modular Industrial-Grade Mathematical Optimization Solvers