Summer Program

Summer Program 2018Summer Program 2017Summer Program 2016
No. Course Name Teacher Time Room
1 Large-Scale Statistical Inference Weijie Su
(Wharton)
July.9th-July.12th
Time:8:00-11:45
武东T9
2 Large-scale Integer Programming Santanu S. Dey
(Georgia Tech)
July.10th-July.13rd
Time:13:20-17:05
信息学院102
3 Queuing Theory Yuan Zhong
(Booth U of Chicago)
July.16th-July.20th
Time:8:00-11:45
信息学院104
4 Stochastic Process and Financial Risk Analysis David Yao
(Columbia University)
July.17th-July.20th
Time:13:20-17:05
武东T9
5 Stochastic System and Simulation Theory Peter Glynn
(Stanford University)
July.23rd-July.26th
Time:8:00-11:45
武东T9
6 A tutorial in doing quality research in OM Chris Tang
(UCLA)
July.24th-July.27th
Time:13:20-17:05
武东T9
7 Reinforcement learning Shipra Agrawal
(Columbia University)
July.24th-July.27th
Time:13:20-17:05
武东T5
8 Information Dynamics in Social Networks Yaron Singer
(Harvard University)
July.30th-Aug.2nd
Time:8:00-11:45
武东T9
9 Topics in Revenue Management Vineet Goyal
(Harvard University)
July.30th,July.31st,Aug.2nd,Aug.3rd
Time: 13:20-17:05
武东T9
10 Introduction to Machine Learning with Applications in R Xi Chen
(NYU Stern)
July.31st-Aug.03rd
Time:13:20-17:05
武东T5
11 Statistics Learning and Graph Theory Martin Wainwright
(UC Berkeley)
Aug.7th-Aug.10th
Time:8:00-11:45
武东T9
12 Topics in Operations Research Yinyu Ye
(Stanford University)
Jul.9th
Time:8:00-11:45;13:20-17:05
信息学院102
2017 Summer Program Course Information
Class Schedule

Course Name Teacher Time Notes
Stochastic Systems and Simulation Theory Peter Glynn
(Stanford University)
7.24-7.27
Stochastic Process and Financial Risk Analysis David Yao
(Columbia University)
7.3-7.6
Statistical Learning and Graph Theory Martin Wainwright
(UC Berkeley)
7.9-7.12
Stochastic Optimization Alexander Shapiro
(Georgia Tech)
7.10-7.13
Artificial Intelligence Tuomas Sandholm
(CMU)
7.18-7.21
Robust Optimization Aharon Ben-Tal
(Technion)
5.25-5.27
Information Dynamics in Social Networks Yaron Singer
(Harvard University)
7.31-8.3
Introduction to Machine Learning with Applications in R Xi Chen
(NYU Stern)
6.25-6.28
Optimization Algorithms for Machine & Deep Learning Guanghui Lan
(Georgia Tech)
6.26-29
Large-Scale Statistical Inference Weijie Su
(Pennsylvania Wharton)
7.17-7.20
Dynamic Pricing Stefanus Jasin
(Michgan Ross)
7.11-7.14
Time Series Analysis Haipeng Xing
(SUNY at Stony Brook)
7.7/10/12/14
Topics in Revenue Management Vineet Goyal
(Columbia University)
7.31-8.3

Series A

Data Analytics

Course Name
Teacher
Time
Notes
Business Statistics
Yichuan Ding
(UBC)
6.9 – 6.12
Time Series Analysis
Haipeng Xing
(Stanford)
6.27 – 6.30
Introduction to Pricing Analytics
Jun Li
(Wharton Ross)
6.29 – 6.30 &
7.3 – 7.4
Optimization for Modern Data Analysis
Tao Yao
(Stanford)
7.5 – 7.8
Microeconomic Theory in Practice
Chris Ryan
(Booth U of Chicago)
7.15 – 7.19
Introduction to Machine Learning
with Applications in R
Xi Chen
(CMU)
7.25 – 7.28

Series B

Modeling and Decision-Making

Course Name
Teacher
Time
Notes
Linear Optimization and Application
Yinyu Ye
(stanford)
7.1 – 7.4
Nonlinear Optimization
Dongdong Ge
(Shufe)
7.21 – 7.24
Revenue Management
Zizhuo Wang
(Minnesota)
7.29 – 8.1
Optimization Algorithms for Deep Learning
Guanghui Lan
(Georgia Tech)
8.1 – 8.4
Stochastics and Robust Optimization
Jiawei Zhang
(NYU Stern)
Mid August
Dynamic Optimization
Zhizu Zhu
(Stanford)
Mid August