Kai Chang

Kai Chang is a Researcher in the Department of Computational Science and Engineering (CSE) at the Massachusetts Institute of Technology (MIT), affiliated with the School of Engineering. His research is advised by Themis Sapsis and focuses on applied probability, stochastics, statistics, numerical analysis, and machine learning. He holds a B.S. in Mathematics from Emory University with a minor in Computer Science.

His research investigates advanced numerical methods and machine learning techniques for computational modeling, with recent work emphasizing operator complexity reduction in multigrid and algebraic multigrid systems. Kai contributes to MIT's CSE doctoral and master's programs, and his work aligns with MIT's broader initiatives in uncertainty quantification and learning from data.

Though no specific awards or grants are listed, his publications reflect a strong focus on computational science innovation. Kai is housed in Room 5-423 at MIT, indicating active involvement in campus-based research.