Title: Assistant Professor
Address: 3765 Beyster
Degree: PhD, Computer Science, UC Berkeley, 2011
Research Interests: Jake's research draws from the field of Machine Learning (ML), but he has devoted much attention to a range of areas, including game theory, decision theory, optimization, market mechanism design, and financial applications. He is particularly interested in how algorithms utilized in ML, such as those for discovering patterns in data, are strongly related to methods used in large-scale optimization, as well as strategies for hedging financial derivatives and setting prices in securities markets.
Research Areas: Artificial Intelligence; Theory of Computation.
Areas of Specialty: Machine Learning; Electronic Commerce; Design and Analysis of Algorithms.