Jerry L. Kung

PhD Candidate,
Operations Research Center,
Massachusetts Institute of Technology

Contact Information:
jkung "at" mit.edu
View Jerry Kung's LinkedIn profileLinkedIn
77 Massachusetts Ave, E40-130
Cambridge, MA 02139


MIT

About me

My expected graduation date is June 2017, and I am currently seeking full-time industry opportunities in data science and analytics. My expertise is in prescriptive analytics, specifically the confluence of mathematical optimization and applied machine learning. For a current copy of my résumé, please contact me.

I am a final-year PhD candidate in the Operations Research Center at the Massachusetts Institute of Technology (MIT) under the supervision of Professor Dimitris Bertsimas. I am broadly interested in analytics: the science of distilling data into actionable insights that add societal value. I have applied analytics to projects in health care and air transportation. I am proud to be supported as a National Science Foundation Graduate Research Fellow.

I completed my undergraduate degree at Harvard College (AB, summa cum laude, 2011) in Applied Mathematics: Computer Science and worked with Professor David Parkes as a member of the EconCS Group. I am grateful to The Star-Ledger of New Jersey for recognizing me as the Mort Pye Scholar and for their full financial support during my undergraduate studies.

I also completed Part III of the Mathematical Tripos at Emmanuel College, Cambridge (MASt, 2012). I am thankful for the full support of the Harvard Herchel Smith Postgraduate Scholarship, which made my year abroad possible.

Publications

  • An Analytics-Based Decision System for Kidney Offer Acceptance.
    With Dimitris Bertsimas, Nikos Trichakis, Parsia Vagefi, David Wojciechowski.
    In preparation.

  • Optimal Selection of Health Care Providers.
    With Dimitris Bertsimas.
    In preparation.

  • Robust Aircraft Routing [PDF]
    With Chiwei Yan.
    Accepted to Transportation Science, 2015.
    Anna Valicek Best Student Paper Award Winner, Presented at the 55th Annual Symposium of AGIFORS, Washington D.C.

  • A Course on Advanced Software Tools for Operations Research and Analytics [PDF]
    With Iain Dunning, Vishal Gupta, Angie King, Miles Lubin, John Silberholz.
    INFORMS Transactions on Education 15(2): 169-179, 2015.

  • Incentive Design for Adaptive Agents [PDF]
    With Yiling Chen, David C. Parkes, Ariel D. Procaccia, Haoqi Zhang.
    In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Taipei, Taiwan, May 2011.

  • Teaching

    I have a passion for teaching, and I have had the privilege of instructing many groups of extraordinary students at the Executive MBA, MBA, and undergraduate levels. Few activities exhilarate me as much as the challenge of crafting supplemental lenses to break down complex topics. I am honored to be recognized with the only 2015-2016 MIT Sloan Outstanding Teaching Assistant Award based on student nominations.

  • MIT 15.727 (EMBA), 15.071 (MBA): The Analytics Edge
    Teaching Assistant (Spring 2016, Spring 2015, Spring 2014).
    [Student Evalutions]

  • MIT 15.060: Data, Models, and Decisions
    Teaching Assistant (Fall 2015)
    [Student Evalutions]

  • MITx 15.071x: The Analytics Edge
    Teaching Assistant (Summer 2015)

  • MIT 15.S60: Software Tools for Operations Research
    Teaching Assistant for Introduction to R (IAP 2016, IAP 2015, IAP 2014)

  • Harvard Applied Math 121: Intro to Optimization: Models and Methods
    Head Teaching Fellow (Spring 2011), Teaching Fellow (Spring 2010)
    [Student Evaluations]

  • Coursework

    Probability and Machine Learning
    • Machine Learning (MIT 6.867)
    • Fundamentals of Probability (MIT 6.436)
    • The Analytics Edge (MIT 15.071)
    • Probability Theory (Harvard Math 154)
    Mathematical Optimization
    • Statistical Learning via a Modern Optimization Lens (MIT 15.097)
    • Robust Modeling, Optimization, and Computation (MIT 15.094)
    • Nonlinear Programming (MIT 6.252)
    • Introduction to Mathematical Programming (MIT 6.251)
    • Introduction to Optimization: Models and Methods (Harvard Applied Math 121)
    Computer Science
    • Efficient Algorithms (Harvard CS226r)
    • Data Structures and Algorithms (Harvard CS124)
    • Introduction to the Theory of Computation (Harvard CS121)
    • Graph Theory and Combinatorics (Harvard Applied Math 107)
    • Introduction to Computer Science (Harvard CS50 and CS51)
    Applications
    • Applications of Operations Research in Social Networks (MIT 15.099)
    • Behavioral Decision Theories and Applications (MIT 15.795)
    • Topics at the Interface between CS and Economics (Harvard CS286r)

    Miscellaneous

    I serve as a peer mediator and counselor for the ORC as part of the MIT Resources for Easing Friction and Stress (REFS) Program. I am also an Applied Math Non-Resident Tutor for Leverett House at Harvard.

    I am fascinated by the complexity of international relations and foreign affairs. During my undergraduate years, I was an active member of the Harvard International Relations Council. I served on the Board of Directors and as the Chief Auditor in 2011. I was also a member of the executive committee for the Harvard Model United Nations Conference in 2010.

    In my spare time, I enjoy cooking and photography. My Erdős number is 3.