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Personal profile

Research profile

Nikhil Bansal is a Full Professor and Chair of Combinatorial Optimization in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e).  Nikhil’s main research interests are theoretical computer science with emphasis on design and analysis of algorithms for discrete optimization problems.  He also works in related areas such as discrete math, complexity theory, machine learning and probability.

Nikhil Bansal’s VICI-funded reserch, ‘Making discrete decisions in a continuous way’ explores the interface between continuous and discrete mathematics. The aim is to design a variety of new and powerful algorithmic techniques that find an arrangement or structure in discrete objects, which is in some sense optimal and applicable to a wide variety of problems.

Academic background

Nikhil Bansal received his BSc in Computer Science from IIT Mumbai (1999) and obtained his PhD from Carnegie Mellon University in 2003. He worked at the IBM T.J. Watson Research Center until 2011, where he also managed the Algorithms group. He has received several best paper awards for his work and is the recipient of the NWO VIDI, TOP and VICI grants, and an ERC consolidator grant.

In addition to his work at TU/e, Nikhil is also a researcher at CWI, the Dutch National Research Institute for Mathematics and Computer Science in Amsterdam. He has served or is active on several Editorial Boards (Journal of the ACM, SIAM  Journal on Computing, Mathematics of  Operations Research) and Program Committees: FOCS 2018, HALG 2018, ICALP,  Approx, IPCO, SPAA, IPDPS 2017, WAOA, ITCS, ESA (chair 2015), STOC 2014 and FOCS. He has also organized and participate at workshops at CWI Amsterdam, UC Berkeley and HIM, Bonn.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being


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