2024 Global Graduate Student Summer Forum(2024暑期8040www威尼斯-apple app store全球博士生论坛)

发布日期:2024-04-23    来源:国际合作处

Forum Objectives

The forum aims to strengthen international educational cooperation and promote cross-cultural exchange by providing a platform for exceptional doctoral students, from home and abroad, to engage in academic and intellectual discourse. Encompassing fields such as economics, finance, business administration, data science and artificial intelligence, the forum focuses on critical issues that impact global economic development. Additionally, the forum aspires to offer new perspectives and innovative approaches to address these global economic challenges. It endeavors to help young scholars worldwide gain a deeper understanding of the Chinese economy and society while assisting domestic graduate students in broadening their global perspectives and fostering innovative thinking.

Forum Dates

Registration Date: June 30th, 2024

Forum Date: July 1st to July 7th, 2024

Participating Disciplines

1. Economics (including Economics, Finance)

2. Management (including Business Administration, International Business)

3. Data Science and Business Artificial Intelligence (including Statistics and Mathematics, Information Science)

We welcome participants from a broad range of disciplines that are relevant to our program.

The forum has invited world-renowned experts to provide academic guidance. Please refer to the appendix for a detailed list of academic mentors.


1. The Forum Organizing Committee warmly welcomes full-time doctoral students from various countries worldwide to apply, aiming to select participants with diverse cultural backgrounds.

2. Applicants are required to submit a CV, and a paper manuscript or a research proposal (less than 50 double-spaced pages). These documents should be sent to our contact email with the title "Name + University Name + Summer Forum." The Forum Organizing Committee guarantees applicants' submission materials will remain confidential.

3. The forum organizing committee and academic committee will conduct a comprehensive evaluation based on the applicants' personal backgrounds, papers (research plans), and the quality of academic presentations. The forum will present outstanding paper awards and provide financial rewards. In addition, a China-themed award will be set up to encourage research projects related to China; a summer camp service award will be established to recognize participants who actively participate or make special contributions during summer camp activities.

4. Application Deadline: May 28th, 2024. Applications will be accepted on a rolling basis.

Forum Schedule

The schedule for the doctoral student forum includes the following series of activities:

1. Academic guidance and exchange: Each academic expert will be responsible for a specific academic sub-forum. The expert will deliver an academic lecture and engage in academic discussions with the participating students. Students will have the opportunity to present their academic perspectives and the experts will participate in discussions and provide feedback.

2. Excursions to local businesses: Participants will have the opportunity to visit companies in China's digital economy (Internet), finance, new energy vehicles, as well as other emerging industries.

3. Culture related outings: Participants will travel on China's high-speed rail system and visit various cultural landmarks. They will also be introduced to classical Chinese culture, such as traditional drama, music, and dance.

Funding Support

1. The Forum Organizing Committee covers all expenses for participants during the forum, including meals, accommodation, etc. The Forum Organizing Committee encourages doctoral students to seek funding from multiple sources for their travel expenses (airfares). If there are specific needs, participants can contact the committee, which may provide travel grants based on individual circumstances.

2. Participants are responsible for purchasing relevant insurance and must provide the corresponding documentation upon registering at the conference.

3. The allocation of awards and grants is contingent upon active participation in forum activities, and the Forum Organizing Committee retains the ultimate authority for the final interpretation of these terms.


Ji Ting (Division of International Cooperation)

Email: jiting@cufe.edu.cn

Telephone: +86(10) 62288337

Appendix: Participating Academic Mentor

Lin William Cong

Lin William Cong is the Rudd Family Professor of Management (endowed faculty chair by the Rudd Family Foundation) and a Tenured Professor of Finance at the Johnson Graduate School of Management at Cornell University SC Johnson College of Business. He is also the founding faculty director for the FinTech Initiative at Cornell, a faculty scientist at the Initiatives for Cryptocurrencies and Contracts (IC3), and a research associate at the National Bureau of Economic Research. Mr. Cong has served as a Finance Editor for the Management Science, and as associate or advisory editors for the Journal of Financial Intermediation, Journal of Portfolio Management, Journal of Corporate Finance, and the Journal of Banking and Finance, among other editorial roles. He is also a member of multiple professional organizations such as the American Economic Association, European Finance Association, and the Econometric Society. Mr. Cong’s research concentrates on the fields of financial economics, information economics, FinTech and Economic Data Science, Entrepreneurship as well as topics related to China. His academic interests include financial innovation, mechanism and information design, blockchains, cryptocurrencies, digital economy, real options, financial policy and markets in China, machine learning, AI for Finance, and alternative data.

Jean Imbs

Jean Imbs is a Professor of Economics at New York University Abu Dhabi and Paris School of Economics and a Research Director at France’s Centre National de la Recherche Scientifique (CNRS). He received a Master's degree in International Business from HEC Paris, and a PhD in Economics from New York University. Until 2010, he was a Professor at the London Business School and at the University of Lausanne. Mr. Imbs’ research focuses on international macroeconomics, with an interest in the consequences of microeconomic complexity for macroeconomic phenomena. He has published in the major professional journals in Economics, including the American Economic Review, the Quarterly Journal of Economics, the Journal of Financial Economics, the Journal of Monetary Economics, and the Journal of International Economics. Mr. Imbs consults regularly with major policy institutions, including the International Monetary Fund, the World Bank, the European Central Bank, the European Commission, the Bank of England, the UK Treasury, and many other central banks around the world. He has taught among others at Princeton University, the University of Chicago Booth School of Business, New York University, HEC Paris, and INSEAD.

Jia Li

Jia Li is the Lee Kong Chian Professor of Economics at School of Economics at Singapore Management University. He received a PhD in Economic from Princeton University, and was a professor of economics at Duke University from 2011 to 2021. His research focuses on semiparametric and nonparametric methods in time series analysis, with a special emphasis on the analysis of high frequency financial data. His work has been published in leading journals across economics, statistics, and probability, including American Economic Review, Econometrica, Review of Economic Studies, Review of Economics and Statistics, Journal of Econometrics, JASA, Annals of Statistics, and Annals of Applied Probability. He is an elected fellow of the Society of Financial Econometrics and the Journal of Econometrics, Co-Editor of Econometric Theory, and Associate Editor of Econometrica, Journal of Financial Econometrics, Journal of Business and Economic Statistics, and Journal of Econometrics.

Yong Li

Yong Li is the Lee Professor of Entrepreneurship in the Lee Business School and Research Director of Troesh Center for Entrepreneurship and Innovation at University of Nevada, Las Vegas. He is a Co-Editor for Strategic Entrepreneurship Journal (SEJ), a leading entrepreneurship journal, and on the editorial boards of several other leading journals including AMJ, AMR, JBV, and JIBS. Yong Li conducts research at the intersection of entrepreneurship, strategy and international business by studying venture capital, crowdfunding, new venture innovation and international expansion. He examines investment decisions under uncertainty primarily from two angles: keeping options open and getting the institutions right. Mr. Li has published extensively in major management journals such as AMJ, JIBS, OS, and SMJ, and in major entrepreneurship journals including SEJ, JBV, and ETP. His research has been supported by the Kauffman Foundation and SSHRC Canada, recognized by AOM, SMS and IACMR, and featured on Forbes, Entrepreneur, Crowdfund Insider, and Knowledge@Wharton. He has led the SMS Doctoral Workshop and organized several PDWs at AOM on advancing theory development in entrepreneurship.

Guanyi Lu

Guanyi Lu is an Associate Professor and Dean's Emerging Scholar in the Department of Business Analytics, Information Systems and Supply Chain at Florida State University's College of Business. His areas of expertise are retail operations, supply chain structure and integration, supply chain risk and security, and information and communication technology. Mr. Lu's research has appeared in Manufacturing & Service Operations Management, Journal of Operations Management, Production and Operations Management, Decision Sciences among others. He serves as an Associate Editor for Journal of Operations Management and Decision Sciences. His service was recognized by the 2018 Best Reviewer Award of Decision Sciences, the 2020 Best Reviewer Award of Journal of Operations Management, and the 2022 Best Associate Editor Award of Journal of Operations Management. Lu earned both his master's degree (in MIS) and his Ph.D. (in Operations & Supply Chain Management) from the Mays Business School, Texas A&M University.

Michael Pinedo

Michael Pinedo is the Julius Schlesinger Professor of Operations Management in the Department of Technology, Operations, and Statistics at New York University Leonard N. Stern School of Business. From 1982 to 1997, he taught in the Industrial Engineering and Operations Research department at Columbia University. He taught at the Instituto Venezolano de Investigaciones Cientificas (Caracas) from 1978 to 1980 and at the Georgia Institute of Technology from 1980 to 1982. Professor Pinedo's research focuses on the modeling of production and service systems, more specifically, on the planning and scheduling of these systems. He is the author of the books Scheduling: Theory, Algorithms, and Systems (Springer), and Planning and Scheduling in Manufacturing and Services (Springer), and the coauthor of Queueing Networks: Customers, Signals and Product Form Solutions (Wiley). He is co-editor of Creating Value in Financial Services: Strategies, Operations, and Technologies (Kluwer), and editor of Operational Control in Asset Management - Processes and Costs (Palgrave/McMillan).

Yu Qin

Yu Qin is Dean’s Chair and Associate Professor in the Department of Real Estate at the NUS Business School. Her research interests include urban economics (on topics related to transportation and real estate market) and environmental economics (on topics related to air pollution and climate change). Her research is published in leading journals, including Nature Climate Change, Nature Human Behaviour, Nature Water, Journal of Public Economics, Journal of Labor Economics, among others. Currently, she is the co-editor of the China Economic Review, associate editor of Journal of Economic Behavior & Organization, and in the editorial board of Journal of Economic Geography. Yu completed her PhD in applied economics and management at Cornell University in 2014.

Vincenzo Quadrini

Vincenzo Quadrini is a Professor of Finance and Business Economics and James McN. Stancill Chair in Business Administration at the University of Southern California. He is a macroeconomist who focuses on international economics, entrepreneurship, and financial contracts. His research has been published in the American Economic Review, Journal of Political Economy, Review of Economic Studies, and other Journals. He has been coordinating editor for the Review of Economic Dynamics and he is a faculty research fellow at the Center for Economic Policy Research. Before joining USC, Professor Quadrini was on the faculty at New York University, Duke University, and Pompeu Fabra University.

Silvia Sarpietro

Silvia Sarpietro is an Assistant Professor of Economics at the University of Bologna, and a visiting Assistant Professor at Duke University. She received Ph.D. in Economics from University College London (UCL). Her research interests are Panel Data Econometrics and Forecasting, with an applied focus on earnings and firm dynamics.

Arthur Taburet

Arthur Taburet is an Assistant Professor of Finance at the Fuqua School of Business, Duke University. He holds a PhD in Finance from the London School of Economics. His research interests are Banking, Empirical Industrial Organization and Contract Theory.

Maytal Saar-Tsechansky

Maytal Saar-Tsechansky is a Professor at the McCombs School of Business, the University of Texas at Austin. Her research focuses on developing machine learning and artificial intelligence methods to improve decision-making and to benefit people, organizations, and society. Most of her work aims to augment ML & AI by bringing to bear the particular problems that machine learning and AI inform (e.g., health care, business decisions) and the context in which learning itself occurs, with the goal of effectively dealing with the constraints and taking advantage of the opportunities presented in these environments. Her research integrates business, machine learning and artificial intelligence, and she has addressed challenges in different domains, including health care, smart electricity grid, fraud, finance, and the future of work, such as making online labor markets work better for all. She serves as Senior Editor at MISQ and at the INFORMS Journal of Data Science, as an Associate Editor at Management Science, and is also an Editorial board member of the Machine Learning journal.

Dacheng Xiu

Dacheng Xiu is a Professor of Econometrics and Statistics at Booth School of Business, University of Chicago. His research interests include developing statistical methodologies and applying them to financial data, while exploring their economic implications. His earlier research involved risk measurement and portfolio management with high-frequency data and econometric modeling of derivatives. His current work focuses on developing machine learning solutions to big-data problems in empirical asset pricing. Mr. Xiu’s work has appeared in Econometrica, Journal of Political Economy, Journal of Finance, Review of Financial Studies, Journal of the American Statistical Association, and Annals of Statistics. He has served as Co-Editor for the Journal of Financial Econometrics, and has been on the editorial board as an Associate Editor for many journals, including the Review of Financial Studies, Journal of the American Statistical Association, Management Science, and Journal of Econometrics. He has received several recognitions for his research, including Fellow of the Society for Financial Econometrics, Fellow of the Journal of Econometrics, Swiss Finance Institute Outstanding Paper Award, AQR Insight Award, and Best Conference Paper Prize from the European Finance Association. He has been recognized as one of Poets & Quants’ Best 40-under-40 Business School Professors.