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 personalized medicine for cardiovascular diseases. 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
  • Personalized treatment for coronary artery disease patients: Impact of machine learning
    Under review in Management Science, 2018
    with Prof. Dimitris Bertsimas, Rory B. Weiner.
  • Optimal Survival Curves
    Under review in Statistics in Medicine, 2018
    with Prof. Dimitris Bertsimas, Jack W. Dunn, Emma L. Gibson.
  • Development and Validation of a Novel, Non-Linear Stroke Risk Assessment Tool.
    Under review in Stroke, 2018
    with Alberts Mark, Prof. Dimitris Bertsimas, Christian Cadisch, Emma Chesley, Amre Nouh.
Working Papers
Teaching Experience
  • The Analytics Edge, Executive MBA
    Teaching Assistant, Sloan School of Management, Spring 2019
  • Personalized Medicine: A Machine Learning Approach, Harvard Medical School
    Teaching Assistant, Harvard - MIT Health Science and Technology program, 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
  • 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