Agni Orfanoudaki

Operations Research Center
Massachusetts Institute of Technology

Contact: agniorf at mit.edu
CV: PDF

headshot
About me

I am a doctoral candidate in Operations Research at the Massachusetts Institute of Technology, advised by Prof. Dimitris Bertsimas. My primary research interests lie at the intersection of Optimization and Machine Learning, with applications to healthcare and in particular to personalized medicine. My vision is to improve clinical decision making with accurate and interpretable models that utilize state-of-the-art analytics methods. Prior to joining MIT, I worked as a Business Analyst in McKinsey&Company at Athens, Greece. I earned my BS in Management Science and Technology from the Athens University of Economics and Business where my focus was on Operations Research and Business Analytics.


Completed Articles
Working Papers
  • Personalized treatment for coronary artery disease patients: Impact of machine learning
    To be submitted, 2019
    with Prof. Dimitris Bertsimas, Rory B. Weiner.
  • Natural Language Processing from Radiology Reports for Ischemic Stroke Patients
    To be submitted, 2019
    with Prof. Dimitris Bertsimas, Meghan Hutch, Charlene Ong, Prof. Stelios Smirnakis, Rebecca Zhang.
  • Personalized Prediction of Hypertension: A Machine Learning Approach
    To be submitted, 2019
    with Prof. Dimitris Bertsimas, Antonin Dauvin.
Teaching Experience
  • The Analytics Edge, Executive MBA
    Teaching Assistant, Sloan School of Management, Spring 2019
  • The Analytics Edge, Executive MBA
    Teaching Assistant, Sloan School of Management, Spring 2018
  • Capstone Project, Master in Business Analytics
    Mentor for Nordstrom and GroupM, Sloan School of Management, Spring 2017
  • Analysis of Networks and Graphs, BSc. Management Science and Technology
    Teaching Assistant, Athens University of Economics and Business, Spring 2014
Talks and Conferences
  • Imputation of Clinical Covariates in Time Series, NeurIPS, December 2018
  • Personalized treatment for CAD patients: Impact of ML, American Heart Assocation Annual Meeting, November 2018
  • Non-linear Stroke Risk prediction using data from the Framingham Heart Study, Informs Annual Meeting, October 2018
  • Interpretable Clustering: An Optimal Trees Approach, Informs Annual Meeting, October 2018
  • Optimal Survival Trees, Athens University of Economics and Business, December 2017
  • Personalized treatment for CAD patients: Impact of machine learning, Informs Annual Meeting, October 2017
  • Personalized predictive and prescriptive models for CAD patients: An Optimal Trees Approach, Informs Healthcare, July 2017
Competitions and Awards
  • First Prize at Assistive Technology Hack 2019, MIT, March 2019
  • Winner of the Machine Learning Across Disciplines Challenge, MIT, February 2019
  • First Prize at EarthHack 2019, MIT, January 2019
  • Award for best academic performance, Athens University of Economics and Business, 2012-2016
  • Winner of McKinsey Challenge Competition, Athens, July 2015