Xingchen Sha is a first-year PhD student in computer science at Northwestern University, advised Edith Elkind. He earned dual bachelor's degrees from Columbia University and the City University of Hong Kong. His research interests include algorithmic game theory, large language models and automatic mechanism design, with a broad interest in fairness and efficiency in collective decision-making. He has worked closely with researchers including Haris Aziz, Hau Chan, Minming Li, Toby Walsh and Lirong Xia and others across Hong Kong and the United States. Beyond research, he is committed to inclusive teaching and community engagement, including supporting the Hong Kong Secondary School Coding Challenge. He is also a project member of an NSF-CSIRO-funded initiative on fair sequential collective decision-making.