Short Bio
Martin Takac is an Associate Professor and the Deputy Department Chair of Machine Learning at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in the UAE. Prior to joining MBZUAI, he was an Associate Professor in the Department of Industrial and Systems Engineering at Lehigh University, where he had been on faculty since 2014. He earned his B.S. (2008) and M.S. (2010) degrees in Mathematics from Comenius University, Slovakia, and his Ph.D. (2014) in Mathematics from the University of Edinburgh, United Kingdom. Martin’s research focuses on the development and analysis of algorithms for machine learning, AI-driven scientific discovery, protein-DNA interaction studies, and the application of machine learning to energy systems. He has received funding from multiple U.S. National Science Foundation programs, including a TRIPODS Institute grant in collaboration with Lehigh, Northwestern, and Boston University. Recently, he was also awarded a grant in partnership with the Weizmann Institute of Science. He has served as an Associate Editor for journals such as Mathematical Programming Computation, Journal of Optimization Theory and Applications, and Optimization Methods and Software. Additionally, Martin has taken on the role of Area Chair for top conferences such as AISTATS, ICML, NeurIPS, and ICLR. Martin Takac is an Associate Professor at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), UAE. Before joining MBZUAI, he was an Associate Professor in the Department of Industrial and Systems Engineering at Lehigh University, where he has been employed since 2014. He received his B.S. (2008) and M.S. (2010) degrees in Mathematics from Comenius University, Slovakia, and Ph.D. (2014) degree in Mathematics from the University of Edinburgh, United Kingdom. He received several awards during this period, including the Best Ph.D. Dissertation Award by the OR Society (2014), Leslie Fox Prize (2nd Prize; 2013) by the Institute for Mathematics and its Applications, and INFORMS Computing Society Best Student Paper Award (runner up; 2012). His current research interests include designing and analyzing algorithms for machine learning, AI for science, understanding protein-DNA interactions, and using ML for energy.
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arXiv-e preprints
orcid.org/0000-0001-7455-2025Workshops/Conferences
I have co-organized following workshops- HOO-2022 - Order up! The Benefits of Higher-Order Optimization in Machine Learning at NeurIPS'22
- OPT2021: Optimization for Machine Learning at NeurIPS'21
- OPT2020: Optimization for Machine Learning at NeurIPS'20
- MOPTA'16 - Modeling and Optimization: Theory and Applications
- MOPTA'15 - Modeling and Optimization: Theory and Applications