Jan van den Brand

Jan van den Brand is an Assistant Professor in the School of Computer Science at Georgia Tech. Previously, he was a Postdoctoral Researcher at UC Berkeley and the Simons Institute for the Theory of Computing, and a visiting researcher at the Max Planck Institute for Informatics. He holds a PhD from KTH Royal Institute of Technology (advised by Danupon Nanongkai), and BSc/MSc degrees from Goethe University Frankfurt (Germany).

Education

• PhD in Computer Science, KTH Royal Institute of Technology (2021)
• MSc in Mathematics and Computer Science, Goethe University Frankfurt (2017-2016)
• BSc in Mathematics and Computer Science, Goethe University Frankfurt (2016-2011)

Research Interests Jan's work focuses on designing efficient algorithms and data structures, particularly for dynamic graphs and optimization problems. His research explores the interplay between dynamic algorithms and optimization techniques, leveraging fast matrix multiplication and algebraic methods to achieve breakthroughs in dynamic graph algorithms and convex optimization.

Awards & Honors

• EATCS Distinguished Dissertation Award (2021)
• SMC Prize for Excellent Doctoral Dissertation (2021)
• SOSA 2021 Best Paper Award

Advising & Grants Jan supervises PhD students in dynamic algorithms and optimization. His NSF CAREER Award supports the project CAREER: From Dynamic Algorithms to Fast Optimization and Back. He has advised students including Emile Anand (2024–present), Albert Weng (2024–present), Anastasiia Alokhina (2022–present), and Daniel J. Zhang (2022–present).

Labs & Tools Developed the Complexity Term Balancer tool to compute upper bounds for algebraic algorithms, widely used in algorithm design research.