Xiao-Yue Gong

Xiao-Yue Gong

xiaoyue

Xiao-Yue Gong 龚小月

My name is pronounced "shout yeah" without the "t". Some friends just call me "XY".

xygong AT mit.edu

CV

Google Scholar Site

orc logo

mit logo

Hi! I am a fifth-year Ph.D. student at the MIT Operations Research Center. I am co-advised by Professor David Simchi-Levi and Professor James Orlin. My current research interests lie broadly in online algorithms, reinforcement learning, data-driven revenue management and supply chain optimization.

Prior to coming to MIT, I finished my undergrad with summa cum laude in 2017 at New York University and NYU Shanghai, with double majors in Honors Mathematics and Interactive Media Arts. In summer 2015, I studied at Budapest Semesters in Mathematics. In summer 2014, I studied with full scholarship in the Business Entrepreneurship program at Tel Aviv University. Also in 2014, my friends and I organized the largest international college hackathon in China at that time, the inaugural HackShanghai. During the same year, I was a Legal Intern at Citibank (China) in Shanghai.

I was a Research Intern at Google Research (Cambridge) in summer 2021. I was a Research Intern at Microsoft Research AI (Redmond) in summer 2020, and a Quantitative Analyst Intern at D.E. Shaw in New York City in summer 2019.


Journal Publications

Bandits Atop Reinforcement Learning: Tackling Online Inventory Models With Cyclic Demands. With David Simchi-Levi.

- Major Revision at Management Science.

Online Assortment Optimization with Reusable Resources. With Vineet Goyal, Garud Iyengar, David Simchi-Levi, Rajan Udwani and Shuangyu Wang.

- Management Science Nov, 2021.

- RM&P Conference Spotlight Talk, June 2021.

A Fast Max Flow Algorithm. With Jim Orlin.

- Networks, Nov 2020.

- Featured on Special Issue on Celebrating 50 Years of Networks, March 2021.

- Best Presentation award at MIT LIDS Student Conference, Jan 2019.


Conference and Workshop Papers

Provably More Efficient Q-Learning in the One-Sided-Feedback/Full-Feedback Settings. With David Simchi-Levi.

- ICML 2020 Workshop Theoretical Foundations of Reinforcement Learning. June 2020.

Efficient Entropy For Policy Gradient with Multi-Dimensional Action Space. With Yiming Zhang, Quan Ho Vuong, Kenny Song, Keith W. Ross.

- ICLR Workshop. Vancouver, April 2018.


Select On-Going Projects

Robust Scheduling with Correlated Jobs with David Simchi-Levi, in partnership with IBM.

A Survey of Online Resource Allocation and Assortment Optimization for Reusable Resources with Yiding Feng, Rad Niazadeh, and David Simchi-Levi.

Cloud Server Fulfilment Under Uncertainty with Konstantina Mellou.


EDUCATION

Ph.D. in Operations Research, Massachusetts Institute of Technology, 2017-present.

- GPA: 5.0 out of 5.0.

- Teaching score: 6.7 out of 7.0.

B.S. in Honors Mathematics, New York University (New York & Shanghai), 2013-2017.

- Double major in Interactive Media Arts.

- GPA: 3.9 out of 4.0.

- summa cum laude.


TEACHING

At MIT: (Teaching evaluation: 6.7 out of 7)

Teaching assistant for 1.267 Statistical Learning in Operations. PhD course.

Teaching assistant for 1.275/IDS.305 Business & Operations Analytics. MBA course.

Guest speaker for 1.267 Statistical Learning in Operations. PhD course.

Teaching assistant for 15.077 Statistical Learning and Data Mining. PhD course.

Co-instructed 15.S60 Computing in Optimization & Statistics. PhD/master course

Co-instructed 15.S41 Software Tools for Business Analytics. Undergrad course.

At NYU:

Tutor for MATH-UA 140 Calculus I at NYU Courant Institute of Mathematical Sciences.

Grader for MATH-UA 121 Linear Algebra at NYU Courant Institute of Mathematical Sciences.

Teaching Assistant of CSCI-UA 0061 Introduction to Web Development & Programming at NYU Tandon School of Engineering.


RECENT TALKS

MIT Data Science Lab Seminar in Oct 2021.

MIT ORC Student Seminar in Sept 2021.

Google Intern Research Talk in July 2021.

RMP Conference in June 2021 (Spotlight Session).

MSOM Conference in June 2021.

MIT Data Science Lab Seminar in May 2021.

MIT LIDS & Stats Tea Talk in April 2021.

ICML Theoretical Foundations of Reinforcement Learning Workshop in July 2020.

MSOM Conference in July 2019.

MIT Data Science Lab seminar in April 2019.

MIT LIDS Student Conference in January 2019.


SELECT HONORS

Bayer Women in Operations Research Scholarship by the Analytics Society of INFORMS 2021.

Best Presentation award at MIT LIDS Student Conference 2019.

MIT Lockheed Martin Tech for Truth hackathon (Supply Chain Track) Grand Prize 2019.

MIT IDEAS Global Challenge winner 2018.

MIT Bitcoin Hackathon ARCC Prize 2018.

Rhodes Scholarships China Finalist 2017.

NYU Shanghai Provost’s Award 2017.

Resolution Fellowship at Youth Assembly at the United Nations Headquarters 2016.

NYU President’s Service Award 2016.

NYU Courant Summer Undergraduate Research Experience 2016.

NYU Reynolds Changemaker Challenge Best Venture 2015.

Autodesk IMA Smart Home Design Challenge Winner 2015.

NYU Shanghai Recognition Award 2013-2016.

Israeli CPB Scholarship for Summer Entrepreneur Program at Tel Aviv University 2014.