Leann Thayaparan

Leann Thayaparan

Assistant Professor

About me

Hello! I am an Assistant Professor of Business Analytics and Operations Management at the Carey School of Business, Johns Hopkins University. My research focuses on the intersection of operations management, optimization and machine learning in the areas of sustainability and retail. I work on a variety of problems, focusing on consumer behavior as it relates to electric vehicles, pricing and COVID-19 forecasting. I recieved my Ph.D. in Operations Research from MIT ORC where I was advised by Professor Georgia Perakis.

Contact me: thayaparan@jhu.edu

My interests include:

  • Sustainable Operations
  • Operations Management
  • Optimization
  • Machine Learning

    • Publications

    *Names of authors in publications are listed by alphabetical order

    Honors

    • Finalist of the MSOM Student Paper Competition 2023
    • ORC Best Student Paper Award 2023
    • Honorary Mention of the POMS College of SCM Best Student Paper Competition 2023
    • Finalist of the Jeff McGill Student Paper Award 2022
    • Second Place in Service Science Best Student Paper Award 2021
    • ICSS Best Conference Paper Award 2021
    • Finalist of the Doing Good with Good OR Competition 2021
    • Finalist of the Public Sector Operations Research Best Paper Competition 2021
    • MIT Sloan School of Management Dean’s Fellowship for outstanding academic record, personal achievements and professional promise, 2018

    Teaching Experience

    15.730 Data, Models, and Decisions for Executive MBAs

    • EMBA tutor, Spring 2023
    • Material Development, Spring 2023
    • Teaching Assistant, Spring 2022, Rating: 6.6/7
    • Teaching Assistant, Spring 2021, Rating: 6.5/7

    15.089 Analytics Capstone for Masters of Business Analytics

    • Advisor to Masters’ Capstone Project in collaboration with Macy’s, Spring/Summer 2023, project title: I’m Just Browsing: Predicting the Value of Prospective Customers
    • Advisor to Masters’ Capstone Project in collaboration with Wayfair, Spring/Summer 2023, project title: Beyond the Match: Enhancing Product Matching with Model Calibration
    • Advisor to Masters’ Capstone Project in collaboration with General Motors, Spring/Summer 2022, project title: Personalized Marketing Strategies for OnStar Customers
    • Advisor to Masters’ Capstone Project in collaboration with General Motors, Spring/Summer 2022, project title: Enabling Electric Vehicle Adoption: Identifying Charging Station Malfunctions
    • Advisor to Masters’ Capstone Project in collaboration with General Motors, Spring/Summer 2021, project title: Electric Vehicle as an Energy Reservoir: Vehicle-to-Grid (V2G)

    Grants and Patents

    Grants

    • Co-wrote research proposal for industry collaborator General Motors. Received funding for three years of a doctoral student and a masters student
    • Co-wrote research proposal for industry collaborator Oracle Retail, submitted to the External Research Office, which reviews grants and makes funding decisions. Received funding for two years of a doctoral student

    Patents

    • US 20230096633 A1 - “Optimized tree ensemble based demand model” (L. Thayaparan, K. Panchamgam, S. Borjian, G. Perakis) Invention disclosure filed September 2021

    Collaborators

    General Motors

    • Sized capacity of electric vehicles to act as distributed battery storage for the electric grid using V2X
    • Estimated potential monetary and carbon emissions impact of the General Motors fleet engaging in V2X
    • Forecasted traffic congestion using real time driver data streams

    Oracle

    • Optimized markdowns on fashion data when demand forecasts are from a random forest

    Zara

    • Improved fast fashion forecasts for new products that do not have historical data

    CDC

    • Modeled COVID-19 cases and deaths up to four weeks out at national and state level for CDC aggregated forecasts

    MIT Quest for Intelligence

    • Estimated county-level true prevalence of COVID-19 cases to assist in MIT’s reopening strategy

    Professional Experience

    General Motors, February 2019 - August 2019
    Intern

    • Aggregated raw driver data into an intuitive and robust congestion score’ to track traffic flow in real time
    • Built an ensemble forecasting model to predict traffic congestion a day, hour and ten minutes in advance to help General Motors drivers avoid traffic flares

    Accenture / Morningstar, September 2018 - December 2018
    Project on financial impact of innovation in asset management

    • Analyzed 26 asset management firms investment in emerging technology based on 8 years of Factiva media data
    • Modeled relationship between investment in emerging technology and financial growth to find if innovative cultures affect performance; determined no predictive relationship

    McKinsey & Company, September 2016 - May 2018
    Senior Analytics Fellow

    • Helped companies expand their analytical toolkits by advising on development of data science capabilities
    • Designed and implemented new analytical hire training for McKinsey’s Operations Advanced Analytics practice

    Professional Service

    • Coordinator for the MIT ORC Seminar series (Fall 2022)
    • Coordinator for the ORC Student Seminar series (2021-2022)
    • President of the INFORMS student chapter at MIT (2019 - 2020)