Operations Research Center...Research focusing on making methodological and algorithmic...

Operations Research Center Massachusetts Institute of Technology

GRADUATE STUDENT DIRECTORY

November 2019

Ryan Cory-Wright

Operations Research Center Massachusetts Institute of Technology 77 Massachusetts Avenue, E40-103 Cambridge, MA 02139

Email: [email protected] Cell: 617-955-5710

Website: ryancorywright.github.io

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2022. GPA: 5.0/5.0 Advisor: Dimitris Bertsimas

University of Auckland, Auckland, New Zealand BE (1st Class Honours) in Engineering Science, May 2017. GPA 8.84/9.00 (9.00/9.00 in Major). Advisors: Golbon Zakeri, Andy Philpott.

Research Methodological: Optimization (discrete/conic/stochastic/robust), machine learning, statistics Interests Applications: Finance, energy (market design/renewable integration)

Research Experience 2017-Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Dimitris Bertsimas Research focusing on making methodological and algorithmic contributions to conic and discrete optimization problems. More recently, research focussing on solving central problems in the optimization, machine learning and statistics literatures to certifiable optimality at scale.

2016-2017 University of Auckland, Auckland, New Zealand Research Assistant Advisor: Golbon Zakeri

Teaching Experience 2019 15.095 Machine Learning Under a Modern Optimization Lens TA (MBaN/MSc/PhD level). (Fall) Instructor in charge: Dimitris Bertsimas

Teaching Assistant for a course which provides masters/PhD students with a modern treatment of Machine Learning using the lenses of convex, robust and mixed-integer optimization. Duties: Assisting students, leading recitations, writing and marking assignments and exams.

2019 15.089 Analytics Capstone Project: Student Mentor Instructor in charge: Dimitris Bertsimas (Summer) Advised a project completed by two MBAn students, who applied prescriptive analytics to

prescribe actions which optimize fund flows for a large investment management company.

2019 15.S60 Computing in Operations Research and Statistics Instructor (MSc/PhD level). (IAP) Taught a 3-hour session which aims to provide PhD students with an overview of state-of-the-art

software tools used in optimization and statistics. Material available here.

2018 15.093 Optimization Methods TA (MBaN/MSc level). Instructor in charge: Bart Van Parys (Fall) Teaching assistant for a course which aims to provide masters students with a unified overview

of the main algorithms and areas of application in optimization. Duties: Assisting students, leading recitations, writing and marking assignments and exams.

2018 15.089 Analytics Capstone Project: Student Mentor. Instructor in charge: Dimitris Bertsimas

https://github.com/adelarue/cos_2019/tree/master/7_advanced_jump

(Summer) Advised a project completed by two MBaN students, who applied machine learning techniques to predict fund flows at the financial advisor level for a large investment management company.

• Mentees received an award for the best capstone presentation in their graduating class. Work Experience 2014-2016 Derceto Ltd, Auckland, New Zealand Assistant Optimization Engineer

Assisted with installing a pump-scheduling optimization tool for two municipal water providers. Refurbished 5+ VBA spreadsheet tools used in day-to-day operations.

Professional Activities and Service

2019 Tester and Proctor, MIT Operations Research Center Qualifying Exam 2018-present Reviewer, European Journal of Operational Research; INFORMS Journal On Computing 2017-present Student member, INFORMS; Mathematical Optimization Society

Publications “On Polyhedral and Second-Order Cone Decompositions of Semidefinite Optimization Problems”, with Dimitris Bertsimas, Operations Research Letters, under review.

“On Stochastic Auctions in Risk-Averse Electricity Markets With Uncertain Supply”, with Golbon Zakeri, Operations Research Letters, under review.

“A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms”, with Dimitris Bertsimas and Jean Pauphilet, Operations Research, under review.

• Awarded 1st place, INFORMS Computing Society Best Student Paper Competition (2019).

“A Scalable Algorithm for Sparse Portfolio Selection”, with Dimitris Bertsimas, Operations Research, under 2nd round of review (submitted June 2018).

“Payment Mechanisms for Electricity Markets With Uncertain Supply”, with Andy Philpott and Golbon Zakeri, Operations Research Letters. 46(1):116-121, 2018.

• Awarded 1st place, ORSNZ Young Practitioner’s Prize (2016). Talks

“A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms”, presented at: ICCOPT, August 2019; INFORMS Annual Meeting, October 2019.

“A Scalable Algorithm for Sparse and Robust Portfolios”, presented at: INFORMS, November 2018; LIDS student conference, January 2019.

“Payment Mechanisms and Risk-Aversion in Electricity Markets With Uncertain Supply”, presented at: EPOC mini workshop, July 2017; ISMP Bordeaux, July 2018.

“Cost-Recovering, Revenue-Adequate Single-Settlement Schemes for Electricity Markets”, presented at: ORSNZ, December 2016.

Honors and Awards 2019 First place, INFORMS Computing Society, Best Student Paper Award For: “A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms” 2017 Senior Scholar Award, University of Auckland (top of graduating class). 2016 First place, Young Practitioner’s Prize, Operations Research Society of New Zealand.

For: “Payment Mechanisms for Electricity Markets with Uncertain Supply” 2014-2016 Deans Honours List, Faculty of Engineering, University of Auckland (top 5% of class). 2014-2016 First in Course Award x5, University of Auckland. 2013 NZQA Outstanding Scholar Award (top 50 high school students in New Zealand).

Skills and Activities

Programming Languages: Julia (preferred), R, VBA, SQL, MATLAB, C++, HTML, CSS. Optimization Software: JuMP (preferred), CPLEX (preferred), MOSEK (preferred), most other languages/solvers. Languages: English (native), French (conversational), German (beginner). Extracurriculars: Skiing, Running, Hiking.

Citizenship Citizen of New Zealand, Ireland

Georgia Dimaki

Operations Research Center Massachusetts Institute of Technology 77 Massachusetts Avenue, E40-103 Cambridge, MA 02139 Email: [email protected]

235 Albany St, Ashdown House, 3023C Cambridge, MA, 02139

857-999-7459

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for SM in Operations Research; expected completion, August 2020. GPA: 4.0/5.0 Advisor: Eytan Modiano Athens University of Economics and Business, Athens, Greece

BS in Computer Science, April 2018. Thesis title: Envy Free Allocation

Research Experience 2018–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Eytan Modiano Clustered Optical Data Center Network Architectures: The aim of this research is to explore and quantify the benefit of dynamic clustering based on traffic changes in Optical DCNs, a well as deploying clustering algorithms for network clusters reconfiguration.

2017-2018 Athens University of Economics and Business, Athens, Greece

Research Assistant Supervisor: Stavros Toumpis The Unsurpassed Project: Experimentation on the performance of ad hoc, delay-tolerant and information-centric routing protocols as well as security mechanisms suitable for use by Unmanned Surface Vehicles (USVs) operating autonomously over very large areas.

Publications

”Demo: Wireless Maritime NetworkingExperiments with Dedalus”, with Aliaj et al., submitted to WiNTECH’18, November, 2018.

”A platform for wireless maritimenetworking experimentation”, with Aliaj et al., submitted to 2018 Global Information Infrastructure and Networking Symposium (GIIS), October, 2018.

Honors and Awards 2016 I. Flitzanis Award For high distinction in courses (BS): "Automata and Complexity", "Logic", "Computational

Complexity" 2015 I. Kavouras Award For high distinction in courses (BS): "Operating Systems" and "Computer Systems Organization"

2014 M.Dimopoulou Award For high distinction in courses (BS) related with Mathematics Skills and Activities

Languages: English, Greek Programming Languages: Java, Python, C++, Javascript, HTML/CSS, PHP Optimization/Analytics: Gurobi, Julia, Ampl, R, Python, MATLAB

MIT Ashdown House Events Officer, 2019 Volunteering for MIT Community, 2019 AUEB CS Lab Administrator, 2015 Database skills: SQL, MongoDB, MySQL Soft skills: Teamwork, Creativity, Detail-Driven Extra-curricular Activities: Knitting, Sewing, Songwriting, Singing, Dancing, Exercising

Citizenship Citizen of Greece

Victor Gonzalez


235 Albany St., 4015 Cambridge, MA 02139

512-769-5200

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2024. Advisor: Patrick Jaillet Rice University, Houston, TX

BA in Computational and Applied Mathematics, June 2019. Summa Cum Laude

Work Experience 2016 Piney Point, Milwaukee, WI (Summer) Hedge Fund Intern

Researched energy companies and worldwide factors to determine catalysts for movement in stock prices.


Research Assistant Advisor: Patrick Jaillet Developing algorithms which will solve problems related to online matching. I am studying how competitive these algorithms are, and I am working to improve the efficiency of these algorithms.

2017-2019 Rice University, Houston, TX

Research Assistant Supervisor: Andrew Schaefer Worked on generalizing facet-defining inequalities in a subset of variable upper bound problems under uncertainty. This could be used improve computational time for certain network optimization problems under uncertainty. This could also be extended to variable upper bound problems in general.

Teaching Experience 2016-2019 Rice University, Houston, TX Teaching Assistant for Introduction to Engineering Compuation (CAAM 210)

Helped organize an introductory class teaching students Matlab and its applications to engineering. I held a weekly recitation and office hours to help students understand the week's material. I also graded the students' assignments.

Honors and Awards

2019 James W. Waters Award, Rice University (Spring) Awarded for creativity in research 2018 CAAM Chevron Award, Rice University (Fall) Awarded for class performance and research 2017-2019 LJ Walsh Scholarship 2015-2019 Rice University President's Honor Roll Skills and Activities

Programming: Python, C, C++, Matlab, Gurobi, CPLEX, LaTex Baker Academic Mentor, 2016-2019

Baker Head Academic Mentor, 2017-2019 Hispanic Association for Cultural Enrichment at Rice

Citizenship Citizen of United States of America

Zachery Halem


33 Rogers St, Apt 213 Cambridge MA, 02142

914-715-1870

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for SM in Operations Research; expected completion, June 2020. Advisor: Dr. Andrew Lo Princeton University, Princeton, NJ

BSE in Operations Research and Financial Engineering, High Honors, Elected to Phi Beta Kappa, June 2018. GPA: 3.93/4.00.

Work Experience 2015-2019 PayRay, New York, NY Founder and CEO

Formed a retail tech start-up that allows customers to enter a store, scan products they wish to purchase with their smartphone, and exit the store without having to wait in a checkout line.

2018 Blue Labs, Washington, D.C. (Fall) Associate Campaign Analyst (Midterms)

Developed and managed an election night tracker; leveraged internal polls to target underperforming demographics and redistribute advertisement spending in major media markets for several major Senate and Gubernatorial races

2016 BoomBang, Los Angeles, CA (Summer) Intern

Conceptualized an innovative recovery-enhancing wearable technology for a major athletic company

2015 DidIt Labs, New York, NY (Summer) Intern

Developed metrics around user intent signaling that formed the basis of the social media startup's revenue model


Research Assistant Advisor: Dr. Andrew Lo Developing portfolio and investment models by utilizing creative financial engineering techniques to incentivize the funding of nuclear fusion in the private sector; examining how market dynamics of Fortune 500 companies have induced energy transitions and GHG reduction efforts.

2017-2018 Princeton University, Princeton, NJ Senior Thesis Research Supervisor: Professor Matthew Weinberg Formulated a game theoretical model for allowance flows in a cap and trade scheme, and subsequently evaluate different auction, reserve sale, and price ceiling formats.

2017 Princeton University, Princeton, NJ

Junior Thesis Research Supervisor: Professor Warren Powell Developed a novel sequential decision-making framework that uses stochastic modeling and Markov dependent processes to optimize the manner in which a baseball manager utilizes relief pitchers in his bullpen.

2017-Present Lisman Research Laboratories at Toolik Field Station, Fairbanks, AK

Researcher Supervisor: Dr. Rachel Cox Collecting yearly spruce samples along a latitudinal transect in northern boreal forest, and performing methylation, acetylation, photosynthetic rate, and morphological measurements to investigate whether epigenetic changes due to the harsh environmental conditions are manifested in mitosis and/or meiosis .

2012-2014 Lisman Molecular Ecology Research Laboratories, New York, NY

Researcher Supervisor: Dr. Rachel Cox Performed a study on the effect of stressful environmental conditions on endocrine functions of the Atlantic ribbed mussel, which was the first to demonstrate a correlation between low dissolved oxygen and disruptions in androgynous steroid levels, physiological development, and maturation.

Publications

“A Game Theoretical Approach to Cap and Trade System Modeling and Auction Design.” Princeton Senior Thesis, with Matthew Weinberg, working paper.

”Quantification of heat shock protein 70 and acetylcholinesterase over a time course suggests environmental adaptation in a foundational molluscan species”, with Andrew Ravaschiere, Caroline Cutler, and Rachel Cox, in Ecotoxicology and Environmental, April, 2017.

”Evidence for intraspecific endocrine disruption of Geukensia Desmissa (Atlantic ribbed mussel) in an urban watershed”, with Dustin Ross & Rachel Cox, in Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, May, 2014.

Patents

Application No. 15/491,807, “Geo Detection System and Methods,” Filed April 19, 2017 Application No. 14/885,149, “Payment Method and System”, Filed October 16, 2015

Honors and Awards 2018 Selected to the Phil Beta Kappa Honor Society, Tau Beta Pi Engineering Honor Society, and

Sigma Xi Scientific Research Honor Society 2018 Gates Scholarship Finalist 2016 Participant in competitive Silicon Valley TigerTrek program; named Princeton Entrepreneur of

the Month 2014 Awarded Marjot Foundation grant, Bausch & Lomb Honorary Science Award, and Charmatz

Science Award Skills and Activities

Technical: Java, R, MATLAB, SQL and AMPL Skills, Proficient with Adobe InDesign and Microsoft Office Language: English (native), Mandarin (proficient) Composer of jazz, classical, and lyrical music, including completion of a symphony entitled A Centennial Overture, which premiered at the Taplin Auditorium in Princeton University

Member of Princeton Polo Team, 2014-2018 Founding Member & Donation Manager of Effective Altruism Investments at Princeton University, 2015-2017 Volunteer, Peace Memorial Foundation, 2015-2017

Citizenship Citizen of United States of America

Michael Lingzhi Li


580 Washington St, Unit 712 Boston, 02111 857-998-9610

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2021. GPA: 5.0/5.0 Advisor: Prof. Dimitris Bertsimas

Massachusetts Institute of Technology, Cambridge, MA Master’s in Business Analytics, June 2018. GPA: 5.0/5.0 Focus: Integer Optimization, Statistics, Applications of Machine Learning

University of Cambridge, Cambridge, UK Bachelor of Arts (Hons.) in Mathematics, June 2017. 1st Class Honors (Wrangler); Top 10% of Class

Work Experience 2018 StubHub (Ebay), San Francisco, CA Machine Learning & Quantitative Analyst

Led development of StubHub’s first machine learning system to predict ticket pricing Designed new algorithm for heterogeneous treatment detection that exceeds current state-of-the-art; Paper accepted by Manufacturing & Service Operations Management

2017 Boston Consulting Group, London, UK Summer Associate (Received Full-Time Offer)

Led data analytics effort in a 9-person team for a $50 million operational transformation case Employed Alteryx and Tableau to redesign key KPIs and provide insights into over 25M rows of CSV data; constructed interactive dashboard for global monitoring Recommended 10+ actionable business moves to senior management using analytics, creating impact of over $10 million.

2016-17 Royal Dutch Shell, London, UK Remote Quantitative Analyst (Received Full-Time Offer)

Analyzed financial market data using PCA and Support Vector Machines Created Deep Learning architecture for predicting supply chain movements in European energy markets using Recurrent Neural Networks and Residual Connections.

2016 J.P. Morgan Chase, London, UK Structuring Intern (Received Full-Time Offer)

Helped team in structuring multiple >$100 million strategic loans and building financial models Revamped Python deal monitoring script to reduce compile time by 90% 2nd Place in firm-wide trading competition; Best Communication Presentation Award.


Research Assistant Advisor: Dimitris Bertsimas My primary research interests fall under two fields: (1) High-performance machine learning algorithms with an interpretability focus, and (2) Application of machine learning in real-world projects. My past work includes using ideas from discrete optimization to develop new algorithms for regression and matrix completion. Currently, we are focusing on precision medicine – specifically the creation and evaluation of precision medicine methods.

Teaching Experience 2019 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Machine Learning under a Modern Optimization Lens (15.095)

Conducted weekly recitations on advanced machine learning/optimization topics for 90 students. Created 6 problem sets, midterm, and responsible for mentoring final project. Holds weekly office hours to further engage with students.

2019 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for The Analytics Capstone (15.089)

Mentored two students in Master’s of Business Analytics program on “Predicting Disease From Longitudinal Laboratory Data” with Quest Diagnostics

Publications

”Interpretable Matrix Completion: A Discrete Optimization Approach”, with D. Bertsimas, 2019. Submitted to Operations Research. ”Fast Exact Matrix Completion: A Unifying Optimization Framework”, with D. Bertsimas, 2019. Submitted to Journal of Machine Learning Research. “Accounting for Significance and Multicollinearity in Building Linear Regression Models”, with D. Bertsimas, 2019. Submitted to Operations Research Letters. ”Targeted Workup after Initial Febrile Urinary Tract Infection: Using a Novel Machine Learning Model to Identify Children Most Likely to Benefit from Voiding Cystourethrogram”, with D. Bertsimas, J. Dunn, D. Zhuo, and Advanced Analytics Group of Pediatric Urology, 2019. Journal of Urology, 202(1), 144-152.

”Experimental Evaluation of Individualized Treatment Rules”, with K. Imai, 2019. Submitted to Journal of Royal Statistical Society (Series B). “Pricing for heterogeneous products: Analytics for ticket reselling”, with M. Alley, M. Biggs, R. Hariss, C. Hermann, G. Perakis, 2019. Under Revision at MSOM.

Honors and Awards 2019 Finalist in 2019 MSOM Practice-Based Paper Competition 2015, 2016 Christine and Hermann Bondi Prize for Mathematics (Top of College) 2015 Finalist in Mathematical Competition in Modeling (Top 0.2%)

2014 Longmeng Scholarship (Surpassing All-time High School Academic Record) Professional Qualifications and Activities Associate Member of the Institute and Faculty of Actuaries (Pending) Chartered Enterprise Risk Actuary (Pending)

Programming: Python, Julia, R, Matlab, SQL Optimization/Machine learning: Gurobi, Tensorflow, Pytorch, CPLEX Interests: Piano (ABRSM Grade 8), Swimming, Diving, Mountain Biking

Citizenship Citizen of Canada

Zhen Lin


Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2024. Advisor: Prof. Dimitris Bertsimas The Chinese University of Hong Kong, Shenzhen, China

BS in Statistics, May 2019. Research Experience 2019–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Prof. Dimitris Bertsimas Optimization and Machine Learning.

2017-2019 Shenzhen Research Institute of Big Data, Shenzhen, China

Research Intern Supervisor: Prof. Zhi-Quan Luo Waveform Optimization for MIMO Systems.

Teaching Experience 2018-2019 The Chinese University of Hong Kong, Shenzhen, Shenzhen, China Teaching Assistant for Linear Algebra (MAT2040)

Gave weekly tutorials in English, held weekly office hours, answered students’ questions online.

2017 The Chinese University of Hong Kong, Shenzhen, Shenzhen, China (Spring) Teaching Assistant for Probability and Statistics I (STA2001)

Gave weekly tutorials in English, held weekly office hours, answered students’ questions online.

2016, 2017 The Chinese University of Hong Kong, Shenzhen, Shenzhen, China (Fall) Teaching Assistant for Calculus I (MAT1001)

Gave weekly tutorials in English, held weekly office hours, answered students’ questions online. Publications

”Minimax Design of Constant Modulus MIMO Waveforms for Active Sensing”, with Wenqiang Pu, and Zhi-Quan Luo, published in IEEE Signal Processing Letters, October, 2019.

”Minimax Design of Constant Modulus MIMO Waveforms”, with Wenqiang Pu, and Zhi-Quan Luo, published in The 52nd Asilomar Conference on Signals, Systems, and Computers, October, 2018.

Honors and Awards 2019 Presidential Award for Outstanding Students 2019 (Spring) This Award represents the highest honor the University can bestow on its graduates who have a

proven track record of academic excellence and leadership over the period time of their undergraduate study at The Chinese University of Hong Kong, Shenzhen.

2017, 2018 Master’s List of Shaw College

Awarded twice due to outstanding academic performance. Awarded RMB 1,000. (The Chinese University of Hong Kong, Shenzhen)

2016-2017 Undergraduate Research Awards

Awarded three times. Awarded RMB 10,000 in total. (The Chinese University of Hong Kong, Shenzhen)

2016, 2017 Academic Performance Scholarship – Class A

Awarded twice. Awarded RMB 80,000 each time. (The Chinese University of Hong Kong, Shenzhen)

2016 Student Outstanding Performance and Leadership Award

The award is to recognize students who have best demonstrated, and have been recognized for, their achievements or contributions in areas such as leadership, student activities, creative and performing arts, campus involvement, or career accomplishments. (The Chinese University of Hong Kong, Shenzhen)

2015-2018 Dean’s List

Awarded four times due to outstanding academic performance. (The Chinese University of Hong Kong, Shenzhen)

2015, 2018 Academic Performance Scholarship – Class C

Awarded twice. Awarded RMB 20,000. (The Chinese University of Hong Kong, Shenzhen) 2014 Entrance Scholarship

Awarded RMB 47,500. (The Chinese University of Hong Kong, Shenzhen) Skills and Activities

Programming Skills: Julia, MATLAB, Python, R, C++, C. Optimization Software: JuMP, Gurobi, MOSEK Software: Latex

Editorial Team, Fall 2014 – Fall 2015, The Chinese University of Hong Kong, Shenzhen Student Helper for Orientation Activities, Fall 2014, Summer 2015, Fall 2015, The Chinese University of Hong Kong, Shenzhen

Citizenship Citizen of China

Galit Lukin


40 Bow St. APT 1 Cambridge, MA 02138

857-253-1425

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for SM in Operations Research; expected completion, June 2020. GPA: 4.5/5.0 Advisor: Dimitris Bertsimas Technion, Israel Institute of Technology, Haifa, Israel

BS, Faculty of Industrial Engineering and Management, June 2016. Work Experience 2017-2018 Microsoft, Herzelya, Israel Education Team, Data Scientist

Developed, implemented, and researched unique data driven algorithms that measure the success of adaptive learning algorithms used in the field of education. Created analytics and data visualizations for teachers based on students’ ability, learning, and advancement.

2016-2017 Microsoft, Herzelya, Israel Recommendations Team, Data Engineer

Assessed and maintained the quality of Microsoft’s Virtual Stores on all platforms including Xbox, Desktop, and HoloLens through algorithm development, added features and varied filters for Top Charts, such as Frequently Bought Together, Best Rated, and Most Popular. Integrated signals received from other teams, such as purchase, usage, and ratings data.

2012 Israel Defense Forces, Israel Commander of the “SarEl” International Army Experience Course

Commanded 23 soldiers in all aspects of day to day duties.

2010-2011 Israel Defense Forces, Israel "SarEl” Group Leader

IDF international volunteers’ group leader. Led group, logistics, lectures, and activities throughout Israel.


Research Assistant Advisor: Dimitris Bertsimas Research optimization methods for Personalization in the fields of Education and Medicine. Build prescriptive algorithms based on clustering and optimal classification trees which create personalized learning paths – experiments conducted through the edX MOOC, “The Analytics Edge” using personal web app. Build regression models to predict diseases & provide personalized interventions.

2016 Technion, Israel Institute of Technology, Haifa, Israel

Research Assistant Supervisor: Malka Gorfine Conducted statistical data analysis and hyperparameter optimization for the prediction of breast cancer.

Teaching Experience 2019-2020 Massachusetts Institute of Technology, Cambridge, MA Teaching Assistant for The Analytics Edge 15.071x

Head TA - resposnsible for administrating the course, building content and exams, and answering ML forum questions and manage TAs.

2019 Massachusetts Institute of Technology, Cambridge, MA (Winter) Teaching Assistant for Computing in Optimization and Statistics 15.S60

Taught git and bash session. 2016 Technion, Israel Institute of Technology, Haifa, Israel (Fall) Teaching Assistant for Operations and Supply Chain Management

Technion, Israel Institute of Technology. 2015 Technion, Israel Institute of Technology, Haifa, Israel (Spring) Teaching Assistant for Production and Service Operation

Created and taught weekly recitations, assisted students one on one, created and graded assignments and exam.

Publications

”EGotsky: Sequencing Content using the Zone of Proximal Development”, with Vainas, O., Bar-Ilan, O., Ben-David, Y., Gilad-Bachrach, R., Ronen, M., Shillo, R. and Sitton, D., submitted to EDM, 07, 2019.


Proficient: Python, R, SQL Familiar: Golang, JavaScript, HTML, Julia, C#, MATLAB, C, C++ Fluent in English, Spanish, and Hebrew INFORMS Officer, 2019-2020, Responsible for all monthly social activities at MIT’s Operations Research Center “Mehamemet” (Israeli Women in STEM) Volunteer, 2017-2018, Taught monthly workshops using MIT App Inventor.

Citizenship Citizen of United States, Israel

Liangyuan Na


70 Pacific St Cambridge, MA 02139

615-918-2651

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2022. GPA: 5.0/5.0 Advisor: Prof. Dimitris Bertsimas University of California, Berkeley, CA

BA in Applied Mathematics and in Operations Research and Management Science, May 2018. Work Experience 2018-2019 Anheuser-Busch InBev, Global Team Research Assistant

Utilized state-of-the-art prescriptive methods to optimize pricing.

2016 China International Trade Research Institute, Dalian, China Resesarch Intern

Short description of your position and what you worked on. Research Experience 2018–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Dimitris Bertsimas Less conservative robust optimization. Machine learning framework for robust optimization. Interpretable machine learning algorithms. Predictive and prescriptive methods in personalized agriculture.

2017-2018 University of California, Berkeley, Berkeley, CA

Research Assistant Supervisor: Anil Aswani De-anonymizing Body Sensor Activity Data with Machine Learning.

2017 University of California, Berkeley, Berkeley, CA

Research Assistant Supervisor: Mariana Olvera-Cravioto The Impact of Degree-degree Correlations on PageRank.

2016 University of California, Berkeley, Berkeley, CA

Research Assistant Supervisor: Ganesh Iyer E-commerce Pricing and Unstructured Data Analytics.

Teaching Experience 2019 Massachusetts Institute of Technology, Cambridge, MA (Winter) Teaching Assistant

Co-founder and instuctor for IAP course “Exploring the Beauty of Gu-zheng” 2017 University of California, Berkeley, Berkeley, CA (Fall) Teaching Assistant

Co-founder and instructor for course ENERES 98: Modeling, How to Understand the World Publications

”Feasibility of Reidentifying Individuals in Large National Physical Activity Data Sets From Which Protected Health Information Has Been Removed With Use of Machine Learning”, with C. Yang, C.C. Lo, F. Zhao, Y. Fukuoka, and A. Aswani, published in JAMA Network Open, December, 2018.

Presentations

“Is Robust Optimization Constraint-wise?”, INFORMS, Seattle, WA, October 2019.

”Re-identifying Physical Activity Data with Machine Learning”, INFORMS Healthcare, Cambridge, MA, July 2019.

“Driving Towards the Future: Modeling the Impact of Driverless Vehicles on Traffic Patterns”, MAA MathFest, Chicago, IL, July 2017.

Honors and Awards 2019 Honorable Mention, Undergraduate Operations Research Prize

INFORMS 2019 Runner-up, MIT FinTech Challenge 2018 High Distinction in General Scholarship University of California, Berkeley 2018 Phi Beta Kappa 2017 Outstanding Winner, MAA Award, Two Sigma Scholarship Award

Mathematical Contest in Modeling (MCM) 2017 Best Use of Outside Data, ASA DataFest

American Statistics Association 2017 Leadership Award x2

Cal Alumni Association


Programming Languages: Julia, Python, R, MATLAB Languages: Mandarin Chinese (native), English (proficient), Spanish (beginner) Cultural & SPICE Chair, MIT Sidney-Pacific Graduate Residence

Co-founder, MIT Chinese Music Ensemble Founder & President, Phoenix Symphony at Berkeley Outreach & Professional Director, Mathematics Undergraduate Student Association at Berkeley


Julie Poullet


235 Albany Street, Apt 3023B Cambridge, 02139

617-514-0719

Education Massachusetts Institute of Technology, Cambridge, MA

Candidate for SM in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Relevant coursework: Linear Programming, Robust Optimization, Semidefinite Optimization, Machine Learning, Machine Learning under a Modern Optimization Lens, Optimization Methods.

Advisor: Matthias Winkembach Ecole Polytechnique, Palaiseau, France

MS in Applied Mathematics, June 2019 Multidisciplinary curriculum in Mathematics, Computer Science, Physics, followed by a specialization in Probability and Operations Research. Lycée privé Saint Geneviève, Versailles, France September 2013, June 2015 Intensive preparation in Mathematics, Physics and Computer Science for the highly competitive national entrance exams to the French Grandes Écoles.

Work Experience 2019 - 2020 Swiggy, Bangalore, India Research Partner

Designing new batching and picker assignment algorithms to tackle large food order and delivery problems. Proposing new batching policies for one of the biggest online food ordering and delivery platforms and a highly realistic simulator to assess them.

2018-2019 UPS, Atlanta, GA Research Partner

Developed novel algorithms for last-mile logistics using drone-and-truck and multi-echelon distribution models. Created a strategic fleet composition tool to increase operational efficiency.

2018 Air France, Paris, France (Summer) Operations Research Intern

Improved the resilience of ground staff scheduling with respect to delay propagation: 5\% cost improvement and 20\% disruption decrease. Modeled the nonlinear propagation of delay along ground staff schedules using the Monoid Resource Constrained Shortest Path framework.

2017 CNH Industrial, Basildon, England (Summer) Logistics Summer Intern

Created an automated planning tool that enabled analysts to identify missing parts. Produced a daily report on the main missing parts directed to suppliers.


Research Assistant Advisor: Matthias Winkembach Megacity Logistics Lab, part of MIT Center for Transportation and Logistics. Applying optimization methods to help companies and cities better design their last mile distribution networks and delivery models. Focusing on integrating machine learning to solve very large scale routing problem.

Teaching Experience 2015 Lycée Privé Sainte Geneviève, Versailles, France Teaching Assistant for Mathematics

Preparation for national examination. Publications

”Shift planning under delay uncertainty at Air France: a vehicle scheduling problem with outsourcing”, with Axel Parmentier, accepted to Transportation Sciences, October, 2020.

Honors and Awards 2018 Prix de la Fondation de l'X (Summer) “Shift planning under delay uncertainty at Air France: a vehicle scheduling problem with outsourcing”

Awarded the first prize across all Polytechnique students for the most promising research developments in industry.


Programming: C++, Caml, Java, Julia, Python, SQL, VBA ETL & Visualization: Tableau, PowerPoint Languages: French (mother tongue). English (fluent). German (basic) Interests: Mountain biking, Swimming, Cooking, Reading, Tea Citizenship Citizen of France

Nicholas Renegar


225 Chestnut St. Apt. 6 Cambridge, MA 02139

206-518-0193

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2021. GPA: 5.0/5.0 Advisor: Prof. Retsef Levi Cornell University, Ithaca, NY

BSc, Operations Research & BA, Mathematics, May 2010. Work Experience 2019 Google, Inc., Mountain View, CA (Summer) Research Intern

Mechanism Design for Google Search Ads

2010-2015 Milliman, Inc., Seattle, WA Healthcare Consulting Actuarial Analyst

Developed commercial software to price claims to Medicare fee schedule, built funding models for WA state healthcare exchange, created proprietary risk score models and other funding model pieces for Department of Veterans Affairs, research on the impact of the ACA.

2008 Solamere Capital, New York, NY (Summer) Private Equity Intern

Created methods of identifying private companies for investment through use of technology, and developed LBO models.


Research Assistant Advisor: Retsef Levi Supply chain analytics, optimization, food safety, healthcare, and internet advertising.

Teaching Experience 2019 Massachusetts Institute of Technology, Cambridge, MA (Winter) Teaching Assistant for Risk Management (15.731)

Assisting Students on Course Projects, Grading 2018 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Healthcare Lab: Intro to Healthcare Delivery in the US (15.777)

Teaching Background Seminars, Assisting Students on Action-Learning Projects, Grading

2018 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Introduction to Operations Management (15.761)

Teaching Weekly Seminars, Running Simulation-Based Projects, Grading 2010 Cornell University, Ithaca, NY (Spring) Teaching Assistant for Introduction to Game Theory (ORIE 4350)

Teaching Weekly Seminars, Grading Publications

”The Second-Price Knapsack Problem: Near-Optimal Real Time Bidding in Internet Advertisement”, with Jon Amar and Haihao Lu. Submitted 2019.

”Supply Chain Network Analytics Guiding Food Regulatory Operational Policy”, with Retsef Levi, Stacy Springs and Tauhid Zaman. Submitted 2019.

”Testing at the Source: Analytics-Enabled Risk-Based Sampling of Food Supply Chains in China”, with Cangyu Jin , Qiao Liang, Retsef Levi, Stacy Springs, Jiehong Zhou, and Weihua Zhou. Submitted 2019.

”Food Regulatory Policy Enforcement in China: Insights from Big Data Analytics”, with Retsef Levi, and Qi Yang. Working Paper.

”Food Safety Inspections and the Adoption of Traceability: Evidence from Wholesale Market Surveys in China”, with Cangyu Jin , Qiao Liang, Retsef Levi, and Jiehong Zhou. Working Paper.


Programming: Python, R, JAVA, C#, Julia, SAS, SQL Citizenship Citizen of the United States of America

Deeksha Sinha

Operations Research Center Massachusetts Institute of Technology 77 Massachusetts Avenue, E40-103 Cambridge, MA 02139 617-902-8094 Email: [email protected]

872 Massachusetts Avenue, Apt 401 Cambridge, MA 02139

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2021. GPA: 5.0/5.0 Advisor: Prof. Vivek Farias Indian Institute of Technology Bombay, Mumbai, India

Masters and Bachelors in Technology, June 2014, GPA: 9.32/10 Minor in Computer Science. Thesis title: Sleep-Wake Up Mechanisms for Cellular Heterogeneous Networks National University of Singapore, Singapore Semester Exchange, Fall 2012, GPA: 4.83/5.

Work Experience 2017 Target Corporation, Minneapolis, MN (Summer) Intern, Revenue Management

Built latent class choice models for predicting purchase of products by different population segments.

2016 Xerox Research Centre India, Bangalore, India (Winter) Intern, Revenue Management

Worked on algorithms for fast assortment optimization over arbitrary feasible sets. 2014-2015 Deutsche Bank, Mumbai, India Quant Analyst, Equity Product Development Team

Developed a machine learning based multiday unwind and hedging strategy for European cash equities using client history, liquidity, volatility and correlation information. Designed and implemented prediction models for stock daily volume and factor flow. Built a Django-based platform for sharing and maintaining data for the Regulatory Market Initiatives team.

2012 IBM India Research Lab, Bangalore, India (Summer) Intern, nPlug Scheduling Algorithms for Electric Vehicles and Inverters

Worked on scheduling algorithms for nPlug - a device to ensure that the load on the electrical grid remains almost constant throughout the day. Developed the PNLB+ (Probabilistic Negative Linear Backoff) algorithm to utilize the flexibility offered by devices whose working can be broken into smaller chunks which increased throughput and achieved better peak to average ratio. Performed simulations to ensure performance in varying grid capacity scenarios, fair resource allocation among users and absence of side effects like memory effect.


Research Assistant Advisor: Prof. Vivek Farias Agricultural lending for small farmers: Working on developing a fair credit scoring system for small farmers in developing countries and also analyzing the impact of government policies on the repayment behavior in farm loans. Early detection of cancer: Worked on algorithms for low-cost early detection and classification of cancer using genetic mutation data. The algorithm is based on a decomposition at the gene level that scales to full genomic sequences across thousands of patients. AB Testing: Worked on algorithms for optimally allocating test subjects in presence of a large number of covariates in online and offline settings. Illustrate the gains achieved by the algorithm over a randomized allocation. Revenue Management: Worked on algorithms for solving large scale assortment optimization problems in sublinear time leveraging fast nearest neighbor methods to solve the problem.

2013-2014 Indian Institute of Technology Bombay, Mumbai, India

Research Assistant Supervisors: Abhay Karandikar and V. Kavitha Determined the maximum fraction of base stations that can be switched off for given traffic condition and required quality of service in a linear deployment of base stations (using optimization results of Multimodular functions). Determined the optimal on-off pattern of base stations and user-base station association policy. Structural properties of the optimal policy were studied and a closed form expression of the average waiting time of users under this policy was obtained.

2013 Tohoku University, Sendai, Japan (Summer) Research Intern

Supervisors: Fumiyuki Adachi and Abolfazl Mehbodniya Studied horizontal handover mechanisms and analyzed the need for differences in designing vertical handover algorithms for heterogeneous networks. Critically examined merits and shortcomings of available vertical handover algorithms and proposed possible improvements.

2011 Indian Institute of Science, Bangalore, India (Summer) Research Intern

Supervisor: Phaneendra Yalavarthy Explored use of Graphics processing unit (GPU) for performing matrix multiplication of large sized matrices. Implemented GPU multiplication in BLT and DOT image reconstruction problems. Compared CPU and GPU performance for performing matrix multiplication through extensive simulations.

Teaching Experience 2016, 18, 19 Massachusetts Institute of Technology, Cambridge, MA Teaching Assistant for Introduction to Operations Management

Took weekly recitations, graded problem sets and provided assistance to students through weekly office hours.

2017 Massachusetts Institute of Technology, Cambridge, MA Teaching Assistant for Analytics of Operations Management

Took weekly recitations, graded problem sets and provided assistance to students through weekly office hours.

2012-2014 Indian Institute of Technology Bombay, Mumbai, India Teaching Assistant for Data Analysis and Interpretation, Communication Systems, Probability and

Random Processes Took weekly recitations, graded problem sets and exams.

Leadership Experience 2016-2018 Member, Academic, Research and Careers Committee, MIT

Led the Travel Grant program of the Graduate Student Council meant to provide financial support to graduate students for attending conferences.

2016-2017 INFORMS Officer and GWAMIT Departmental Representative, MIT

Organized regular social events in the Operations Research Center and served as the ORC representative to the Graduate Women’s Association.

2013-2014 President, ShARE IITB

Led IITB chapter of ShARE, an international student organization connecting students with corporate leaders.

2011-2012 Internship Coordinator, Practical Training Committee, IITB

Facilitated internship process of 1500+ students as part of a 24 member team. 2010-2011 Vice President, Campus Radio, IITB

Revamped the working of the college radio and mentored 2 web based college radios. Publications

“Near Optimal AB testing” with N. Bhat, V.F. Farias, C.C. Moallemi, Management Science, 2019. “Optimizing Revenue Over Data-Driven Assortments” with T. Tulabandhula, submitted to NIPS workshop on Nearest Neighbor Methods, 2017. ”Load Dependent Optimal ON-OFF Policies in Cellular Heterogeneous Networks”, with V. Kavitha and Abhay Karandikar, submitted to 5th International Workshop on Indoor and Outdoor Small Cells, Wiopt 2014.

”nPlug: An Autonomous Peak Load Controller”, with T. Ganu, D.P. Seetharam, V. Arya, J. Hazra, R. Kunnath, L.C. De Silva, S.A. Husain and S. Kalyanaraman, submitted IEEE Journal on Selected Areas in Communication, July, 2013.

Honors and Awards 2014 Best Paper Award (Summer) “Load Dependent Optimal ON-OFF Policies in Cellular Heterogeneous Networks”

5th International Workshop on Indoor and Outdoor Small Cells, Wiopt 2014.

2014 Undergraduate Research Award (Summer) “Sleep-Wake Up Mechanisms for Cellular Heterogeneous Networks”

Awarded by IIT Bombay for senior thesis 2012 Honda Young Engineer and Scientist Award (Spring) 1 of 12 awardees in India 2012 Temasek Foundation Leadership Enrichment and Regional Networking Award (Fall) 1 of 3 awardees in India

Scholarship to pursue a semester exchange in the National University of Singapore and enrolled in the program to nurture the next generation of Asian leaders

2009 Dhirubhai Ambani Scholarship Awarded scholarship for securing state rank 5 in CBSE XIIth Board Exam

Description of award and related paper etc. (Organization or Conference) 2014 Secured class rank 8 in 300+ students in IIT Bombay

Description of award and related paper etc. (Organization or Conference) Skills and Activities

Technical Skills: Python, MATLAB, C++, Scilab, LaTeX, q, SQL, Django Certification: CFA Level I Interests: Bollywood Dancing , Cooking, Traveling, Reading, Voice-Over

Citizenship Citizen of India

Fransisca Susan


70 Pacific Street Cambridge, MA

617-583-3599

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2023. GPA: 5.0/5.0 Advisor: Prof. Negin Golrezaei Massachusetts Institute of Technology, Cambridge, MA

BS in Mathematics and Computer Science, minor in Economics, June 2018. GPA: 5.0/5.0 Work Experience 2018 Goldman Sachs, New York, NY (Summer) Securities Division Summer Strategist

Ten-week rotational internship program involving five-week segments with two teams, automated the sector hedge fund VIP custom basket automation.

2017 Goldman Sachs, New York, NY (Summer) Securities Summer Analyst

Short description of your position and what you worked on.

2017 Traveloka, Jakarta, Indonesia (Winter) Data Scientist

Developed a recommendation system algorithm for the hotel business using various machine learning and statistics approach.

2016 Twitter, Inc., San Franciscso, CA (Summer) Software Engineering Intern

Conducted feature experiments on who to follow modules for new users and resurrected users, created web reonboarding feature, a flow to refine social graph of resurrected users, implemented IOS feature for Datalytics, a hack week project to measure the amount of data usage spent on Twitter application.

Research Experience 2019-Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Professor Negin Golrezaei Currently working on a computationally efficient combinatorial learning algorithm for various applications, such as assortment planning, influence maximization, submodular welfare maximization and product ranking on online platforms.

2018-2019 Massachusetts Institute of Technology, Cambridge, MA Research Assistant Advisor: Professor Andrew Lo - Developed a multi-party computation algorithm to share secretive financial cyber risk data securely across companies. - Simulated, formulated and created heuristics to solve large-scale pharmaceutical portfolio stochastic optimization.

2017-2018 Massachusetts Institute of Technology, Cambridge, MA

Undergraduate Research Assistant Supervisor: Professor James Glass, Yonatan Belinkov Developed a classifier to investigate how well Neural Machine Translation model infers multiple senses from homonyms, investigated the effects of the different layers, target languages and model architecture on word disambiguation ability.

2015 Massachusetts Institute of Technology, Cambridge, MA

Undergraduate Research Assistant Supervisor: Professor Jack Dennis Implemented parallel BFS Algorithm on Fresh Breeze Machine, a new multiprocessor chip architecture, built a benchmark for testing codes on Fresh Breeze Machine as a multi-core system.

Teaching Experience 2018 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Introduction to Machine Learning, 6.036/6.862

Duties: holding office hours, making and grading homeworks and exams Honors and Awards 2019-2020 Tau Beta Pi Fellow 2017-2018 Keel Foundation Undergraduate Research and Innovation Scholars 2017 William Lowell Putnam Mathematical Competition Honorable Mention 2012-2014 International Mathematics Olympiad 1 Silver, 2 Bronze Medals

2014-2018 Presidential Scholarship Skills and Activities

Languages: Indonesian (native), English, Malay, Chinese (basic) Programming: Python, Julia, Gurobi, Java, Scala, R, C++, Javascript, HTML, CSS INFORMS MIT Chapter, Treasurer, 2019 Association of Indonesian Student in New England, President, 2018-Present

Citizenship Citizen of Indonesia

Li Wang


60 Wadsworth St 7E Cambridge, MA 02142

607-379-5636

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Advisor: Prof. David Simchi-Levi Cornell University, Ithaca, NY

BS in Operations Research and Computer Science, May 2015. Thesis title: The Topology of Overlapping Portfolio Networks

Work Experience 2019 Lyft, San Francisco, CA (Summer) Research Scientist Intern

Designed and implemented a new model for surge pricing (primetime), and shipped it into production after A/B testing.

2018 Alibaba Group, Bellevue, WA (Summer) Research Intern

Worked on online learning algorithms for large-scale product selection problems. Research Experience 2015–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Prof. David Simchi-Levi Dynamic pricing collaboration with a retail company. Supply chain analytics in collaboration with a high-tech company. Data-driven revenue management research.

2013-2015 Cornell University, Ithaca, NY

Research Assistant Supervisors: Prof. Andreea Minca, Prof. Peter Frazier Network analysis of portfolio defaults in the financial network. Statistical prediction of the stability of small interfering RNA.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Supply Chain Planning (15.762J/ESD.267J/1.273J)

Led weekly recitations of 90 students. Graded cases. 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Manufacturing System and Supply Chain Design (15.763J/ESD.268J/1.274J)

Led weekly recitations of 50 students. Graded cases. 2014 Cornell University, Ithaca, NY (Spring) Teaching Assistant for Industrial Data and Systems Analysis (ORIE 3120)

Led weekly recitations of 50 students and graded homework and exams. Helped design exams and grading rubrics.

Publications

”Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses”, with R. Jin, D. Simchi-Levi, X. Wang and S. Yang, major revision at Management Science, 2019. ”The Topology of Overlapping Portfolio Networks”, with W. Guo and A. Minca, published on Statistics & Risk Modeling, December, 2016.

Honors and Awards 2015 Merrill Presidential Scholar (Spring) The highest honor given to a graduating senior student. (Cornell University) 2015 Cornell University Class of 2015 College Banner Bearer (Spring) Top 5 GPA among 800 students in College of Engineering. (Cornell University) 2015 Byron W. Saunders Award (Spring) Best academic performance in Operations Research. (Cornell University) Citizenship Citizen of People’s Republic of China

Yuchen Wang


100 Memorial Drive Cambridge, 02142

617-676-8855

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Advisor: Prof. Dimitris Bertsimas

Peking University, Beijing, China BS in Mathematics and Economics, June 2016. Summa Cum Laude.

Work Experience 2019 Facebook Research, Menlo Park, CA Research Scientist Intern working in Economics, Algorithmic, Optimization team

Using machine learning algorithm to decide personalize reserve price for second price auction in advertisement. Find potential opportunity to improve the total revenue. Find advertisement market abstractions for simulation by matrix completion and clustering method. Can be used to predict the result of Budget A/B Test. Plan to write a paper about this.


Research Assistant Advisor: Dimitris Bertsimas Primary research interest is the intersection of modern optimization and machine learning with application in healthcare. We are currently working on the algorithm about developing Optimal Nonlinear Trees. We use global optimization solution to replace the original greedy method when building decision trees in order to increase the accuracy of the whole model. Using the tool that we developed, we improve the prediction rules of children after head trauma who need computed tomography (CT). We also propose a new rule for liver allocation using the advanced machine learning tools we developed.

2014-2015 Peking University, Beijing, China

Research Assistant Supervisor: Lan Wu Used the knowledge of nonsynchronous trading to find the influence of T+1 mechanism in Chinese stock market.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for The Analytics Capstone (15.089)

Mentored four Masters of Business Analytics (MBAn) Student to do two projects with McKinsey & Company. The first topic is spatiotemporal analysis of industrial agglomeration. The second topic is extract named topics from unlabeled test.

2016 MIT edx.org, Cambridge, MA (Spring) Teaching Assistant for The Analytics Edge (15.071x)

Hosted online forum and answered questions. 2018 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for 15.095: Machine Learning Under a Modern Optimization Lens

Conducted weekly recitations about machine learning and optimization for 60 students, created and graded 6 problem sets and midterms. Graded final project.

Publications

”Improved triaging of diagnostic computed tomography for children after head trauma”, with D. Bertsimas, J. Dunn and T. Trikalinos, , 2019, JAMA Pediatrics. ”Optimized prediction of mortality(OPOM): a novel machine-learning approach to prioritize liver transplant candidate”, with D. Bertsimas, J. Kung, N. Trichakis, P. Vagefi, R.Hirose, , 2019, American Journal of Transplantation. "Visualizing tradeoffs in liver transplantation: the benefits of a continuous distribution model and its implications for national policy development", with D. Bertsimas, T. Papalexopoulos, N. Trichakis and P. Vagefi, accepted by Transplantation. ”Optimal Nonlinear Trees for Predictions”, with D. Bertsimas and J. Dunn, working paper.

"Optimal Predictive Clustering", with D.Bertsimas and M. Sobiesk, working paper.

Honors and Awards 2016 Outstanding Graduate Award, Peking University 2015 Canon Scholarship, Peking University 2014 Champion of KPMG Accounting Case Competition 2013 May Fourth Scholarship, Peking University 2012 Gold Medal in 2012 Chinese Mathematical Olympiad(CMO), China Skills and Activities

Programming: Python,Julia,C/C++,Matlab,R Optimization/Machine learning: Gurobi ,Tensorflow, Pytorch, Sklearn, Mosek Interests: Go(5 Duan), Swimming, Table Tennis


Holly Wiberg


14 Chandler St. #3 Somerville, MA 02144

781-686-6849

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, May 2022. GPA: 5.0/5.0 Research Interests: Machine Learning and Optimization in Medicine Advisor: Dimitris Bertsimas Cornell University, College of Engineering, Ithaca, NY

BS in Operations Research and Engineering, May 2016. Summa Cum Laud; Cumulative GPA 4.17/4.3, Major GPA 4.24/4.3 University of Edinburgh, Edinburgh, Scotland Semester Abroad, May 2015. Coursework in Mathematics and Statistics

Work Experience 2016-2017 athenahealth, Watertown, MA Member of Technical Staff, Data Science

Served as an analytics liaison for a major product release. Built self-serve reporting tools to provide key stakeholders with high visibility into provider performance and migration progress for the project, enabling targeted support for clients and facilitating smooth completion of the migration.

2015 athenahealth, Watertown, MA (Summer) Intern, Data Engineering

Developed a metric to quantify the productivity of healthcare providers, and established benchmarks for productivity based on identified key drivers. Delivered recommendations for application of the metric in both internal reporting and client-facing evaluation.


Research Assistant Advisor: Dimitris Bertsimas Leveraging clinical and genomic data to develop better treatment response predictions and recommendations using optimization and machine learning techniques, particularly in oncology. Developing interpretable machine learning methods that allow for greater model transparency with a focus on clinical applications.

2015-2016 Cornell University, Ithaca, NY

Research Assistant Supervisor: Davis Shmoys, Shane Henderson

Collaborated with doctoral students in design of a simulation optimization model to improve the allocation of docks and bikes across stations in a New York City bike-sharing system using gradient-like heuristic methods. Improved model runtime and constructed a fluid model starting solution based on historical data.

2013, 2014 Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Supervisor: Dimitris Bertsimas Developed a mixed-integer optimization model to generate better partitions for classification and regression tasks, using optimization heuristics to improve solve time and find the local optimum. Implemented an evaluation framework to benchmark it against existing methods.

Teaching Experience 2019 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for 15.727 The Analytics Edge

TA for an Executive MBA course. Led recitations and weekly office hours. Advised student teams on final projects and technical topics.

2016 Cornell University, Ithaca, NY Teaching Assistant for ENGR 1101: Engineering Applications of Operations Research

TA for an introductory undergraduate OR course. Led lab sessions and weekly office hours. Graded homework and exams.

Publications

”Interpretable Clustering: An Optimization Approach”, with Dimitris Bertsimas and Agni Orfanoudaki. Under review for Machine Learning, January 2019.

"Prediction of cervical spine injury in young pediatric patients: an optimal trees artificial intelligence approach", with Dimitris Bertsimas, Peter Masiakos, and Konstantinos Mylonas, Journal of Pediatric Surgery, March 2019.

"Simulation Optimization for a Large-Scale Bike-Sharing System", with Nanjing Jian, Daniel Freund, and Shane Henderson, 2016 Winter Simulation Conference in Washington, D.C., December 2016.

Honors and Awards 2019 National Science Foundation Graduate Student Research Fellowship 2017 Henry Gabbay Fellowship, MIT Sloan School of Management 2016 Byron W. Saunders Prize, Cornell University 2015 Omega Rho Honor Society, Cornell University ORIE Department 2014 Tau Beta Pi, Cornell University


Programming: Julia, R, Python, SQL MIT INFORMS Chapter President, 2017. Graduate Student Council Representative, 2017.

Citizenship Citizen of the United States of America

Cynthia Zeng


70 Pacific Street Cambridge, MA 02139

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2024. Advisor: Professor Dimitris Bertsimas Imperial College London, London, UK

Bachelor’s of Science in Mathematics, October 2014 - July 2017 First-class honours

Work Experience 2019 SoftBank Investment Advisors, Shanghai, China (5 months) Financial Analyst

FinTech industry landscape analysis, preliminary company due diligence research, project manager and white paper author of a confidential internal project related to privacy computing.

2018 MIT Media Lab, Boston, MA (Summer) Research Intern

Computational social science model to study urban planning.

2018-2019 BlackRock Inc., London, UK (1 Year) Analyst

Data scientist of an algorithmic fund, generating mid/long-horizon trading strategies. Completed 9-month rotation in fundamental research. Group leader and winner of BlackRock Hackathon EMEA.


Research Assistant Advisor: Professor Dimitris Bertsimas Algorithm development for hurricane prediction.

2018 Summer Massachusetts Institute of Technology, Cambridge, MA Research Intern Advisor: Professor Danielle Wood Multi-agent system to simulate the coupling effect of urban expansion and sea level rise to mangrove ecosystems in Rio de Janeiro. Paper presented at the IEEE Aerospace Conference 2019.

2016-2017 Imperial College London, London, UK

Undergraduate Thesis Supervisor: Professor Henrik Jensen and Professor Jonathan Haskel Agent-based modelling approach to study opinion formation to explore the danger of populism, alternative poll forecast model. Theoretical model using statistical mechanics and computational simulation in Python.


Programming: Python, Julia, PyTorch, Matlab Languages: English (fluent), Mandarin (fluent), Italian (intermediate) Qualifications: CFA I GRE: Quantitative 169, Verbal 158, Analytical Writing 5.0 Interests: yoga, tennis, volleyball, traveling

Citizenship Citizen of Canada

Kevin Zhang


550 Memorial Drive Apt 22F-2 Cambridge, MA 02139

816-588-2869

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Advisor: Prof. Carolina Osorio Yale University, New Haven, CT

BS cum laude in Mathematics and Statistics, with distinction in both majors, May 2012. GPA: 3.83/4.00, Department GPA: 3.94/4.00

Work Experience 2012-2014 Analytics Operations Engineering, Inc. (acquired by McKinsey & Company), Boston, MA Operations Research Analyst

Worked on teams of two to six consultants to solve operations problems, improve productivity, lower costs, and increase capacity through mathematical modeling, programming, and data-driven decision analysis. Projects included: guiding marketing strategy across print, email, and web channels for a $12B+ retail company; forecasting customer demand and inventory shipments to reduce safety stock levels at a Canadian food distribution company; implementing an inventory allocation tool in newly opened stores for a retail clothing chain; building a prescriptive model for customer repayment behavior for a nationwide loan provider.

2011 Federal Reserve Bank, Kansas City, MO (Summer) Economic Research Intern

Conducted an independent research project on the properties of peer-to-peer (P2P) payment services markets. Developed a game theoretic model for P2P markets based on recent research on network goods and social networks, and investigated sensitivity to market share and pricing through simulation experiments.

2010 National Security Agency, Fort Meade, MD (Summer) Intern, Director’s Summer Program

Collaborated with two fellow interns, with support from three agency researchers, on a 10-week long project. Developed methods to attack a sophisticated cryptographic system through application of linear algebra, abstract algebra, and statistics. Published a technical paper for internal use and briefed the Deputy Director of NSA on summer work.


Research Assistant Advisor: Prof. Carolina Osorio

Working on large-scale stochastic optimization problems as applied to real-time calibration of traffic simulators. Developing computationally efficient methods for online calibration that incorporate network-specific structural information into Kalman filtering algorithms.

2012 Yale University, New Haven, CT

Senior Project – Statistics Department Supervisor: Prof. Jing Zhang Conducted a genome-wide association study of type 2 diabetes using a block-based Bayesian model and applied our method to a case-control dataset from the Wellcome Trust Case Control Consortium.

2009 Yale University, New Haven, CT

Summer Research Supervisor: Prof. Hisham Sati Worked with four undergraduates to develop a consistent representational system for the action of Lie groups on hypermatrices and to investigate the invariance properties of hypermatrices.

Teaching Experience 2018 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Transportation Systems Analysis: Performance and Optimization

(1.200/11.544) Led weekly one-hour TA sessions, held office hours, and developed problem sets and quizzes for first-year graduate level course. Same topics as previous year. Overall student rating: 6.8/7.0.

2017 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Transportation Systems Analysis: Performance and Optimization

(1.200/11.544) Led weekly one-hour TA sessions, held office hours, and developed problem sets and quizzes for first-year graduate level course. Same topics as previous year. Overall student rating: 6.9/7.0.

2016 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Transportation Systems Analysis: Performance and Optimization

(1.200/11.544) Led weekly one-hour TA sessions, held office hours, and developed problem sets and quizzes for first-year graduate level course. Topics include: traffic flow analysis, deterministic and probabilistic delay models, linear and integer optimization methods, queueing networks, and stochastic simulation. Overall student rating: 6.6/7.0.

Presentations

“A network-specific metamodel approach for real-time demand calibration of traffic simulators”, with C. Osorio, presented at INFORMS 2019, Seattle, WA.

“Enhancing the computational efficiency of online calibration techniques for traffic simulators”, with C. Osorio, presented at INFORMS 2016, Nashville, TN.

“Combining data-driven and model-driven approaches for traffic simulator calibration problems”, with C. Osorio, presented at INFORMS 2015, Philadelphia, PA.

Honors and Awards 2012 Second Prize at the International Mathematics Competition for University Students 2010 Benjamin F. Barge Prize for solution of original problems in mathematics 2009 Charles M. Runk Prize for demonstrating excellence in a competitive examination in mathematics 2009 Dean’s Research Fellowship in the Sciences Skills and Activities

Programming: R, Matlab, Python, SQL, Java, VBA, C, MATSim Languages: English (native), Chinese (conversational) Seminar Co-Coordinator, Operations Research Center IAP Seminar, January 2019

Citizenship Citizen of the United States of America

Operations Research Center...Research focusing on making methodological and algorithmic...

Documents

Transcript of Operations Research Center...Research focusing on making methodological and algorithmic...