Jonathan Lacotte

Jonathan Lacotte

Jonathan is pursuing a Ph.D. in Electrical Engineering from Stanford University. Prior to joining Stanford in 2016, he received a Bachelor of Science in 2014 and a Master’s degree in Applied Mathematics in 2015, both from the Ecole Polytechnique. He carried out his master’s thesis under the supervision of Prof. Laurent El Ghaoui at UC Berkeley, working on optimization algorithms for the control of energy systems and statistical analysis of news media. Then, he completed Part III in Mathematics at the University of Cambridge.

Jonathan’s research interests span control theory, optimization and statistics, for stochastic decision-making problems. He is currently investigating different ways robots should assess risk in order to take decisions in face of uncertainty, and designing provable algorithms to compute optimal decisions.

Awards:

  • Dean and Bessie Watkins Graduate Fellowship (2016-2017)