Summary
Sayan Mukherjee is a Project Assistant Professor at the University of Tokyo with a Ph.D. in Discrete Mathematics and roughly a decade of experience bridging combinatorics, quantum computing, and software research. His thesis on extremal graph and hypergraph problems informs current work on tensor network contraction, quantum algorithms, and graphics, supported by JST and UTokyo quantum initiatives and a JSPS Start-up Grant. He has blended academic and industry roles—from research positions at blueqat and Elyah to collaborative visits at Warwick—bringing theory-driven solutions to practical quantum software problems. Notably, his background in stochastic simulation and combinatorial methods gives him a rare ability to translate discrete-math insights into algorithmic and implementation advances for quantum and graphical systems.
10 years of coding experience
3 years of employment as a software developer
Secondary, Secondary at Hare School, Kolkata
Higher Secondary, Higher Secondary at Bharatiya Vidya Bhavan, Kolkata Kendra
Doctor of Philosophy (PhD), Discrete Mathematics, Doctor of Philosophy (PhD), Discrete Mathematics at University of Illinois at Chicago - Graduate College
Bachelor in Mathematics, MATHEMATICS AND STATISTICS, Bachelor in Mathematics, MATHEMATICS AND STATISTICS at Indian Statistical Institute, Bangalore
English, Bengali, Hindi, Japanese