李建目前是清华大学交叉信息研究院助理教授。他在中山大学取得的学士学位和复旦大学取得的硕士学位，马里兰大学博士毕业。他的研究兴趣主要包括算法设计与分析，数据库，在线学习与优化算法，随机优化与组合优化。他已经在主流国际会议和杂志上发表了60余篇论文，并获得了 VLDB 2009 和 ESA 2010 的最佳论文奖，清华221基础研究青年人才支持计划以及教育部新世纪人才支持计划。
报告摘要：The world is full of uncertainty and very often decisions have to be made way before the uncertainty is resolved. Stochastic optimization studies optimization problems with uncertain inputs or parameters, in which the uncertainty is modeled using probability theory. The area was initiated by Danzig in 1950s and has been subject to extensive research in many disciplines including computer science, math, operation research, economics, management science and social science. In this talk, I will talk about some of my recent efforts on stochastic geometric and combinatorial optimization problems. In particular, I will talk about some new results on the stochastic models for several fundamental geometric and combinatorial problems, such as minimum spanning tree, closest pair, minimum enclosing ball, shortest path and knapsack.