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  • Homepage
  • Call for Papers
    • Abstract Submission for Session Presentation
    • Application to CSAMSE Management Science Practice Award
    • Full Paper Submission for Best Paper Award Competition
    • Full Paper Submission to JMSE Special Issue
    • Application to CSAMSE Early Career Fellows Program
  • Program
    • Important Dates
    • Program Schedule
    • Session Schedule
  • Key Events
    • Keynote Speech
    • Panel Discussion
    • Youth Scholars Colloquium
    • Female Scholars Luncheon
    • Best Paper Award Competition
    • Practice Award Competition
    • Research Development Workshop
    • Early Career Fellow Program
  • Committee
    • Organizing Committee
    • Best Paper Award Committee
    • Practice Award Committee
    • Program Committee
  • Registration
  • Transportation
    • Public Transportation
    • Shuttle Bus
  • Hotel
  • Review
电子科技大学
English

Key Events

  • Keynote Speech
  • Panel Discussion
  • Youth Scholars Colloquium
  • Female Scholars Luncheon
  • Best Paper Award Competition
  • Practice Award Competition
  • Research Development Workshop
  • Early Career Fellow Program

Keynote Speech




    Prof René B.M. de Koster

    Erasmus University


Topic

Warehouses of the Future. Robots and the Human Factor

Abstract

The new generation of warehouses is gradually becoming robotized. Managers can select from many different competitive robotic techniques to store and retrieve loads and to fulfil the customer orders. In my talk, I discuss three very popular order picking systems involving robots, including cobot order picking systems, where people work together with robots to pick the orders in warehouses. Using a mix of deterministic and stochastic quantitative modelling and empirical research, I show how questions can be answered like 1) How to measure the performance of such systems? 2) how to use these insights to create good-quality designs? 3) How do human factors influence performance how can we increase the well-being of workers in these systems?

Speaker Bio

René (M.) B.M. de Koster is a professor of Logistics and Operations Management at Rotterdam School of Management, Erasmus University. He holds or has held guest professorships in various universities and is the 2018 honorary Francqui Professor at Hasselt University. His research interests are warehousing, material handling, terminal operations, and behavioral operations. He is the founder of the Material Handling Forum and is author / editor of 8 books and over 300 papers in academic journals and books. He was recently mentioned as “the most influential researcher” in material handling. He currently is associate editor of Transportation Science and Operations Research and member of the editorial boards of International Journal of Production Research and Transportation Research-E.







    Prof 
Houmin Yan

    City University of Hong Kong


Topic

Paradigm shift in supply chain finance: smart credit and the new landscape of real-world assets (RWA)

Abstract

Traditional cross-border supply chain finance mainly relies on inventory pledges, and warehouse receipt financing is widely used in China. However, this model has structural problems such as opaque information, high risk of fraud, and low financing efficiency. With the rapid development of modern financial technology, cross-border supply chain finance is undergoing a profound paradigm transformation: the financing model is gradually shifting from inventory pledge to accounts receivable, especially relying on real-time sales and logistics data generated by cross-border e-commerce platforms (such as Amazon, Shopee, and TikTok). The core technology that underpins this new model is a new generation of credit risk models represented by KMV. The KMV model and its patents were originally developed by KMV and later purchased by Moody's for $210 million. and become the core technology of Moody's. AIFT has launched an upgraded version with U.S.-China patent protection, which is designed for non-listed companies that rely on platform data. The model not only supports the credit risk assessment of small and medium-sized enterprises, but also has the ability of risk aggregation and real-time dynamic update. This paradigm shift has also promoted the evolution of the financial structure from bank-led asset-backed loans (ABL) to market-oriented asset securitization (ABS), which may eventually realize real-world asset-based (RWA)-based tokens, greatly improving the liquidity of assets and the marketization of financing.

Speaker Bio

Professor Houmin Yan is Chair Professor of Management Sciences, and director of MSc in Accounting and Finance with AI and Fintech Applications, City University of Hong Kong and Beijing National Accounting Institute.  He is also the Director, Hong Kong Laboratory of AI-Powered Financial Technologies, Ltd. He was Dean of the College of Business at the City University of Hong Kong from Jan. 2013 to June 2020 (Acting Dean June 2019-June 2020) . Prior to joining CityU he served as Professor at the Chinese University of Hong Kong, and as Associate Director and Science Advisor for the Hong Kong R&D Center for Logistics and Supply Chain Management Enabling Technologies. He has also worked as a tenured Associate Professor at the School of Management, University of Texas at Dallas.

Professor Yan's main research areas are stochastic models, machine learning and algorithms, risk modeling and analysis, and supply chain management. He has published in journals such as Operations Research, Manufacturing and Service Operations Management, IIE Transactions, Production and Operations Management, Journal of Optimization: Theory and Applications, and IEEE Transactions. Professor Yan's work has won widespread recognition. In a commissioned citation study by Journal of Operations Management on the knowledge evolution in Operations  Management over last thirty years, his research work in supply chain coordination has been recognized as part of general knowledge structure for Operations Management of 2000s. In 2004, his paper (co-authored with Gan and Sethi) "Coordination of Supply Chains with Risk-Averse Agents" (POM, Vol. 13, 2004, 135 -149) received the Wickham-Skinner Best paper Award from the 2nd World Conference on Production and Operations Management and the Society of Production and Operations Management (POMs). In 2005, his paper (co-authored with Lee and Tan) "Designing An Assembly Process with Stochastic Material Arrivals" (IIE Transactions, Vol. 35, 2003, 803-815) has been awarded the Best Paper Award for "the focus issues on Operations Engineering for 2003-2004" from the Institute of Industrial Engineers(IIE). In 2012, his paper (co-authored with Buzacott and Zhang) "Risk Analysis of Commitment-Option Contracts with Forecast Updates" (IIE Transactions, Vol. 43, 2011, 415-431) has been awarded the Best Paper Prize in Scheduling and Logistics from the Institute of Industrial Engineers(IIE).

He received his BSc. and MSc. from Tsinghua University, both in electrical engineering, and his Ph.D. from the University of Toronto in business. He is a member of Business Studies, Research Grant Council (RGC), a member of Hongkong Academy of Finance, a member of EQUIS Committee, EFMD,  and a member of CIR Committee, AACSB.






    Prof Shouyang Wang(汪寿阳)

    University of Chinese Academy of Sciences


Topic

TEI@I Methodology for Economic Forecasting: Insights from Over Two Decades of Practice

Abstract

TEI@I methodology was proposed in 2002, and since then the methodology has been successfully applied to many areas in economic forecasting, including forecasting of macroeconomic indices such GDP growth rate and CPI, forecasting of demand, supply and prices of resources such as water and energy, forecasting of financial markets such as foreign exchange rates and stock prices. Based on the methodology, several decision support systems of economic early warning, forecasting and policy simulations have been developed for the governmental departments such as The State Commission of Development and Reform, The Central Bank of China, The State Administration of Foreign Exchange, The Ministry of Commerce, and many large companies such Sinopec, PetroChina, China Energy Investment, The State Grid Corporation of China and Air China.

In this talk, TEI@I methodology is introduced and six real applications in economic forecasting are presented to show some advances and features of the methodology in economic forecasting.

Speaker Bio

Shouyang Wang is a distinguished professor of Chinese Academy of Sciences (CAS) and the founding director of the Center for Forecasting Science, CAS. He is a fellow of The Third World Academy of Sciences and an academician of The International Academy for Systems and Cybernetic Sciences. He is/was the president of China Systems Engineering Society, the president of International Society of Knowledge and Systems Sciences, a vice president of International Society of Global Optimization, a vice president of International Academy for Systems and Cybernetic Sciences, and an executive board member of The International Institute of Forecasters. He is/was the editor in chief or an area editor of 12 journals including Energy Economics and China Journal of Econometrics.. He has published 46 monographs (including 21 monographs by Springer and Taylor & Francis in English) and published more than 500 papers in leading journals, including Science, Nature, Journal of Economic Theory, International Economic Review, Journal of Econometrics, and International Journal of Forecasting.






    Prof Zizhuo Wang(王子卓)

    The Chinese University of Hong Kong, Shenzhen


Topic

Large Language Models for Optimization Modeling

Abstract

This talk presents recent advances in the application of large language models (LLMs) to mathematical optimization modeling, with a focus on industrial and operational research contexts.

We introduce ORLM (Operations Research Language Model) — the first open-source LLMs fine-tuned specifically for optimization tasks. To mitigate the scarcity of domain-specific training data, the proposed framework includes OR-Instruct, a semi-automated pipeline designed to generate instruction-style datasets across a broad range of problem types. OR-Instruct employs two core strategies: Expansion and Augmentation. Expansion leverages advanced LLMs to generate new problem scenarios and question types from seed data, while Augmentation diversifies the dataset by modifying objectives and constraints, rephrasing problem statements, and incorporating varied modeling techniques. ORLMs trained under this framework achieved superior performance on public benchmarks such as NL4OPT and MAMO, surpassing most of the leading LLMs. We also develop the IndustryOR benchmark, encompassing real-world optimization scenarios from 13 industries, spanning five categories and three levels of complexity.

Speaker Bio

Prof Wang Zizhuo is currently a professor and associate dean at the School of Data Science, The Chinese University of Hong Kong, Shenzhen. He is also the co-founder and Chief Technology Officer (CTO) of ShanShu Technology. Prof Wang graduated with a degree in Mathematics from Tsinghua University and earned his Ph.D. in Management Science and Engineering from Stanford University in 2012. He previously served as a tenured professor at the Department of Industrial and Systems Engineering, University of Minnesota. Prof Wang is currently the director of the Guangdong Key Lab of Mathematical Foundations of Artificial Intelligence and has received the National Overseas High-Level Talent Youth Program and the National Science Fund for Distinguished Young Scholars. Prof Wang’s main research interests lie in machine learning and operations management. He has published over 60 papers in top-tier international journals in operations research and management science. He also serves on the editorial boards of leading journals such as MS, OR, MSOM, and POMS. Since 2016, Prof Wang co-founded ShanShu Technology and has served as its CTO. Over the past nine years, he has provided smart decision-making consulting and services to more than 300 companies in China, with clients including leading enterprises such as JD.com, SF Express, Didi, Huawei, and China Southern Airlines.




Contact

CSAMSE Email:csamse2025@163.com

Prof. Yunqiang Yin, University of Electronic Science 

and Technology of China yinyq@uestc.edu.cn

Prof. Longfei He, Tianjin University helf@tju.edu.cn

Prof. Mei Xue, Boston College mei.xue@bc.edu

Conference Chairs

Wei Zhang(张维)Conference Chair, President of CSAMSE

Chair Professor, College of Management & Economics, Tianjin University

Fangruo Chen(陈方若)Conference Chair, CSAMSE’s Founding President

Chair Professor & Dean of Antai College of Economics & Management, 

Shanghai Jiao Tong University

Xu Chen (陈旭)Conference Chair

Professor & Dean of School of Management and Economics,

University of Electronic Science and Technology of China

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