Research Seminar: Distribution of Scientific Project Funds Using Big-Data and Operations Research Methods

This talk explores the use of operations research and big-data methods to optimize fund allocation for scientific projects, addressing inefficiencies in manual methods and challenges in balancing diverse fields. Leveraging adaptive similarity fitting and historical project data, an input-output model is developed and aligned with pending projects using scaling factors. By framing fund distribution as a multi-objective optimization problem, the NSGA-II algorithm is applied to enhance allocation. Case studies show significant improvements in research and talent output, with potential reductions in total funding while maintaining output levels.

About the Speaker: Dr. Victor Chan is a Professor and Co-Deputy Director of the Tsinghua-Berkeley Shenzhen Institute at Tsinghua University, China. Previously, he was a faculty member at Rensselaer Polytechnic Institute. Dr. Chan has held leadership roles in major conferences, served as an editor for leading journals, and acted as a reviewer and panelist for multiple international funding agencies.