TE TONY KE - UC Berkeley Industrial Engineering and Operations

TE TONY KE
Industrial Engineering and Operations Research
University of California, Berkeley
1117 Etcheverry Hall, Berkeley, CA, 94720-1777
+1(510) 984-8352
[email protected]
http://ieor.berkeley.edu/~kete/
RESEARCH
INTERESTS
Social Interactions and Social Networks, Search Theory, Economics of Information
Game Theory and Competitive Strategies, Supply Chain Management, Innovation Diffusion
EDUCATION
University of California, Berkeley
Ph.D. Candidate, Operations Research
M.A., Economics (concentration in theory and industrial organization)
M.A., Statistics (concentration in machine learning)
expected 2015
expected 2015
2012
Peking University, Beijing
B.S., Physics
B.S., Statistics
2010
2010
FELLOWSHIPS
AND AWARDS
Outstanding Graduate Student Instructor Award, Haas School of Business
Berkeley Graduate Study Fellowship, UC Berkeley
Engineering Leadership Professional Program Scholarship, UC Berkeley
China Education Department Innovation Grant for Undergraduate Research
Guanghua Scholarship, Peking University
Freshman Scholarship, Peking University
First Prize in National Physics Olympiad Winter Camp, China
WORKING
PAPERS
Te Tony Ke, Zuo-Jun Max Shen, and J. Miguel Villas-Boas. "Search for Information on
Multiple Products." (Dissertation Essay 1)
▪ Presented at INFORMS 2013/2014, MSOM 2014, Marketing Science 2014
2014
2010-2012
2011
2008
2007
2006
2005
Te Tony Ke. "Peer Effect of iPhone Adoptions on Social Networks" (Dissertation Essay 2)
▪ Presented at INFORMS 2014
PUBLICATIONS
Te Tony Ke, Zuo-Jun Max Shen, and Shan Li. "How Inventory Cost Influences Introduction
Timing of Product Line Extensions?" Production and Operations Management 22.5 (2013):
1214-1231. (Dissertation Essay 3)
▪ Presented at POMS 2012
Wei Chen, Alex Collins, Rachel Cummings, Te Tony Ke, Zhenming Liu, David Rincon,
Xiaorui Sun, Yajun Wang, Wei Wei, and Yifei Yuan. "Influence Maximization in Social
Networks When Negative Opinions May Emerge and Propagate." SIAM International
Conference on Data Mining (2011): 379-390.
▪ Presented at Microsoft Research Asia, Beijing, 2009
Te Tony Ke, Hao Huang, and Douglas N.C. Lin. "Rapid Mid-infrared Variability in
Protostellar Disks." Astrophysical Journal 745.1 (2012): 60.
▪ Presented at Newton Institute for Mathematical Science, University of Cambridge, 2009
Curriculum Vitae, Te Tony Ke, 1 of 4
WORK IN
PROGRESS
Gabe Fierro, Te Tony Ke, Guan Cheng Li, Vincent Sheu, and Lee Fleming. "Semantic
Distance between Patents: An Application to Technology Control Matching and A
Knowledge Diffusion Model."
Te Tony Ke. "Price, Quality, and Correlated Product Information."
TEACHING
Graduate Student Instructor at Haas School of Business, UC Berkeley
MFE 230K, Dynamic Asset Management
MFE 230G, Equity and Currency Market
MFE 230H, Financial Risk Measurement and Management
MBA 248, Supply Chain Innovation, Strategy and Analytics
UGBA 104, Analytic Decision Modeling Using Spreadsheet
Spring 2013/2014
Fall 2013
Fall 2013
Fall 2012
Fall 2011
Graduate Student Instructor at Department of Economics, UC Berkeley
Econ 140, Economic Statistics and Econometrics
GRADUATE
COURSEWORK
Optimization:
Mathematical Programming I, II
Applied Stochastic Processes I, II
Convex Optimization
Applied Dynamic Programming
Introduction to System Simulation
Statistics:
Advanced Probability Theory I
Statistic Modeling
Time Series Analysis
Statistical Learning Theory I, II
WORK
EXPERIENCE
Summer 2011
Economics:
Microeconomic Theory I, II
Macroeconomic Theory I
Econometrics I
Industrial Organization I, II
Management Science and Marketing:
Production and Logistic Models
Production and Inventory System
Interface between OM and Marketing
Doctoral Marketing Strategy
Financial Engineering System II
Intern, Charles Schwab, San Francisco
▪ Marketing Analytics Group
▪ Estimating customer lifetime value using dynamic panel data
Jun-Aug 2014
Intern, Walmart eCommerce, Mountain View
▪ Search Engine Marketing Group
▪ Developed bidding optimization and estimation methods for big data
May-Aug 2013
Intern, Xerox Research Centre Europe, Grenoble, France
▪ Machine Learning for Services Group
▪ Studied dynamic mechanism design in selling by lottery
May-Aug 2012
Consultant, Facebook, Palo Alto
▪ IEOR 280 Course Project
▪ Redesigned and optimized global server supply chain
Jan-May 2011
Intern, Microsoft Research Asia, Beijing, China
▪ Theory Group
▪ Built model on negative information propagation in social networks
Jun-Sep 2009
President, GYDO Student Organization, UC Berkeley
2011-present
Curriculum Vitae, Te Tony Ke, 2 of 4
Practice Reporter, Chutian Metropolis Daily, Hubei, China
REFEREE
Operations Research, Production and Operations Management, OMEGA
PERSONAL
INFORMATION
Age: 26
Marital status: Married, one child
Citizenship: China
REFERENCES
Zuo-Jun Max Shen (Committee Chair)
Chancellor’s Professor
Department of Industrial Engineering and Operations Research,
University of California, Berkeley
Phone: (510) 643-2392 Email: [email protected]
May 2005
J. Miguel Villas-Boas (Committee Co-Chair)
J. Gary Shansby Professor of Marketing Strategy, and Group Chair
Haas School of Business,
University of California, Berkeley
Phone: (510) 642-4700 Email: [email protected]
Lee Fleming
Professor, and Faculty Director of Fung Institute
Department of Industrial Engineering and Operations Research,
Management of Organizations, Haas School of Business
University of California, Berkeley
Phone: (510) 664-4586 Email: [email protected]
TEACHING
REFERENCE
Hayne E. Leland
Arno Rayner Professor Emeritus of Finance and Management,
Haas School of Business,
University of California, Berkeley
Phone: (510) 642-8694 Email: [email protected]
APPENDIX (RESEARCH ABSTRACTS)
Te Tony Ke, Zuo-Jun Max Shen, and J. Miguel Villas-Boas. "Search for Information on Multiple Products."
We develop a framework for continuous search for information on a choice set of multiple alternatives, and
apply it to consumer search in a product market. When a consumer considers purchasing a product in a product
category, the consumer can gather information sequentially on several products. At each moment the consumer
can choose which product to gather more information on, and whether to stop gathering information and
purchase one of the products, or decide not to purchase any of the available products. Given costly information
gathering, consumers end up not gathering complete information on all the products, and need to make decisions
under imperfect information. We solve for the optimal search, switch, and purchase or exit behavior in such a
setting, which is characterized by an optimal consideration set and purchase thresholds. The paper shows that
products are only searched if they have a sufficiently high expected valuation, and that, given that there are
multiple products in the consumer’s consideration set, the consumer only stops searching for information and
purchases a product if the expected valuation of the product is sufficiently greater than the expected valuations of
alternative products. Comparative statics show that negative information correlation among products widens the
purchase threshold, and so does an increase in the size of the choice set. We also show that a higher expected
Curriculum Vitae, Te Tony Ke, 3 of 4
valuation of one product might lead to lower sales of all products combined, and that it may be optimal for
sellers of multiple products to obfuscate information for high-valuation products, while facilitate consumer
search for low-valuation ones.
Te Tony Ke. "Peer Effect of iPhone Adoptions on Social Networks"
This paper studies the peer effect of iPhone adoptions in China. I use a unique data set from a provincial capital
city in China, in a span of over four years starting from iPhones first introduction to mainland China. I construct
a social network using six month's call transactions between iPhone adopters and all other users on a carrier's
network. Strength of social ties is measured by duration of calls. Based on the network structure, I test whether
an individual's adoption decision is influenced by his friends' adoptions. A fixed-effect model shows that, on
average, a friend's adoption increases one's adoption probability in next month by 0.79%, and the marginal effect
decreases in the size of his current neighboring adopters. To further control for potential time-varying correlated
unobservables, I instrument adoptions of one's friends by their birthdays, based on the fact that consumers are
more likely to adopt iPhones on birthdays. The IV estimation shows a comparable peer effect at 0.84%. I also
investigate how network structures modulate the magnitude of peer influence. My results show that peer effect is
stronger when the influencer has more friends or a stronger relationship with the influencee.
Te Tony Ke, Zuo-Jun Max Shen, and Shan Li. "How Inventory Cost Influences Introduction Timing of
Product Line Extensions?" Production and Operations Management 22.5 (2013): 1214-1231.
In the market of durable goods, it is common wisdom to introduce high-end product first, and follow by low-end
product-line extensions. A key decision in this “down-market stretch” strategy is the introduction time. High
inventory cost is pervasive in such industries, but its impact has long been ignored during the presale planning
stage. This study takes a first step toward filling this gap. We propose an integrated inventory (supply) and
diffusion (demand) framework and analyze how inventory cost influences the introduction timing of product-line
extensions, considering substitution effect among successive generations. We show that under low inventory cost
or frequent replenishment ordering policy, the optimal introduction time indeed follows the well-known “now or
never” rule. However, sequential introduction becomes optimal as the inventory holding gets more substantial or
the product life cycle gets shorter. The optimal introduction timing can increase or decrease with the inventory
cost depending on the marketplace setting, requiring a careful analysis.
Wei Chen, Alex Collins, Rachel Cummings, Te Tony Ke, Zhenming Liu, David Rincon, Xiaorui Sun, Yajun
Wang, Wei Wei, and Yifei Yuan. "Influence Maximization in Social Networks When Negative Opinions May
Emerge and Propagate." SIAM International Conference on Data Mining (2011): 379-390.
Influence maximization, defined by Kempe, Kleinberg, and Tardos (2003), is the problem of finding a small set
of seed nodes in a social network that maximizes the spread of influence under certain influence cascade models.
In this paper, we propose an extension to the independent cascade model that incorporates the emergence and
propagation of negative opinions. The new model has an explicit parameter called quality factor to model the
natural behavior of people turning negative to a product due to product defects. Our model incorporates
negativity bias (negative opinions usually dominate over positive opinions) commonly acknowledged in the
social psychology literature. The model maintains some nice properties such as submodularity, which allows a
greedy approximation algorithm for maximizing positive influence within a ratio of 1 − 1/𝑒. We define a quality
sensitivity ratio of influence graphs and show a tight bound of Θ 𝑛/𝑘 on it, where 𝑛 is the number of nodes in
the network and 𝑘 is the number of seeds selected, which indicates that seed selection is sensitive to the quality
factor for general graphs. We design an efficient algorithm to compute influence in tree structures, which is
nontrivial due to the negativity bias in the model. We use this algorithm as the core to build a heuristic algorithm
for influence maximization for general graphs. Through simulations, we show that our heuristic algorithm has
matching influence with a standard greedy approximation algorithm while being orders of magnitude faster.
Curriculum Vitae, Te Tony Ke, 4 of 4

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