Jaron Sanders

Jaron Sanders is an Assistant Professor in the Department of Stochastic Operations Research at Eindhoven University of Technology (TU/e). He holds M.Sc. degrees in Mathematics and Physics (2012) and a Ph.D. in Mathematics (2016) from TU/e. Previously, he was a post-doctoral researcher at KTH Royal Institute of Technology (2016–2017) and an Assistant Professor at Delft University of Technology (2017–2019). His research focuses on optimizing large complex systems through interdisciplinary approaches combining probability, statistics, operations research, and machine learning. He has received notable awards, including the ASML Graduation Prize (2012) and TU/e PhD Thesis Award (2017).

Education:

• PhD in Mathematics, TU/e (2016)
• MSc in Mathematics and Physics, TU/e (2012)

Research interests include stochastic optimization, Markov chains, random matrices, and applications in quantum computing, wireless networks, and machine learning. His work bridges theoretical foundations with practical systems, such as analyzing cluster detection in sequential data and developing noise-resilient optical neural networks.

Key contributions include advancements in Block Markov Chains, spectral analysis, and error accumulation models in quantum circuits. He leads projects like the Waardevol AI initiative and collaborates on spectral concentration in Markov chains. His teaching spans stochastic simulation, decision theory, and mathematical modeling.

Awards:

• ASML Graduation Prize for Mathematics (2012)
• TU/e PhD Thesis Award (2017)
• VvS+OR Master’s Thesis Award (2013)

He actively participates in conferences like ACM MobiHoc and organizes seminars to foster interdisciplinary collaboration. His research addresses both theoretical challenges and real-world applications, emphasizing scalable solutions for complex systems.