Vassilis Digalakis Jr

Asst. Professor of Operations Management, HEC Paris

PhD in Operations Research, MIT


Email: vvdigalakis [at] gmail [dot] com  |  digalakis [at] hec [dot] fr

Research Interests: 

▪ Trustworthy  Machine Learning 

▪ Predictive and Prescriptive Analytics 

▪ Optimization 


â–ª Healthcare

▪ Sustainability 


Welcome! I am an Assistant Professor of Operations Management at the Information Systems and Operations Management Department at HEC Paris, with an affiliation with Hi! Paris, a center on data analytics and artificial intelligence for science, business, and society. I completed my Ph.D. in Operations Research at the Operations Research Center at MIT in 2023, advised by Prof. Dimitris Bertsimas. 

Research summary.   My research develops methodologies in trustworthy machine learning (ML), predictive and prescriptive analytics, aiming to facilitate the full pipeline of data-driven decision-making, primarily within healthcare and sustainability. In such high-stakes applications, the components of trustworthy analytics—interpretability and explainability, stability and robustness, fairness, and privacy—are often not just desirable but essential for the successful deployment of predictive and prescriptive models. Leveraging the rich modeling power of optimization paradigms such as mixed-integer, robust, and multi-objective optimization, I focus on developing models that incorporate trustworthiness considerations a priori and on understanding, evaluating, and navigating the trade-offs among the components of trustworthy analytics a posteriori. 

I have collaborated, among others, with OCP, the world's largest producer of phosphate and phosphate-based products, to develop an optimization framework that guides their $2Bn investment in solar panels and batteries; and with the Federal Emergency Management Agency to help them decide on locations for COVID-19 mass vaccination centers and state-level allocation policy. My research has been published in journals such as Operations Research and Manufacturing & Service Operations Management, and has received awards, including the 2023 M&SOM Practice-Based Research Competition Finalist and the 2021 INFORMS Pierskalla Award.

Towards Structurally Stable Machine Learning Models

In healthcare, can we ensure that ML models used for predicting patient mortality risk remain stable when retrained with new data?
In collaboration with a large hospital system in the US, we developed interpretable ML models (e.g., decision trees, which are known to be unstable) that are structurally stable upon retraining with new data.


Decarbonizing OCP (with D. Bertsimas, R. Cory-Wright). M&SOM, 2024.
In sustainability, can we find renewable energy capacity expansion strategies that are robust to the uncertainties posed by climate change?
In partnership with one of the world’s largest fertilizer producers, we created a robust optimization framework to guide their $2 billion investment in renewable energy, aiming to decarbonize their production pipeline.



Where to locate COVID-19 mass vaccination facilities? (with D. Bertsimas, A. Jacquillat, M. Li, A. Previero). Naval Research Logistics, 2021.

During public health crises, like the COVID-19 pandemic, can we distribute resources fairly among states and sub-populations to ensure equity?

Working with the Federal Emergency Management Agency (FEMA), we developed a fair optimization framework to determine locations for COVID-19 mass vaccination centers and state-level allocation policies.

Teaching.   I have taught and developed courses in sustainable operations management (Operations and Supply Chain Management, Instructor, HEC Paris), analytics and machine learning (Interpretability and Algorithmic Fairness, Lecturer, HEC Paris; Machine Learning under a Modern Optimization Lens, Teaching Assistant, MIT; The Analytics Edge, Teaching Assistant, MIT), optimization (Robust Modeling, Optimization, and Computation, Head Teaching Assistant, MIT), computing (Computing in Optimization and Statistics, Instructor, MIT), and introductory mathematics (Mathematics I, Teaching Assistant, TUC) at various levels (PhD, MSc, MBA, undergraduate) and backgrounds (data science, engineering, business, business law).

Early days.   My journey has also included the Alexa Entertainment Spoken Language Understanding team at Amazon Science, where I spent the 2021 summer as a Research Scientist Intern, and the Technical University of Crete, Greece, where I earned my Diploma in Electrical and Computer Engineering in 2018 (Valedictorian). I am originally from the beautiful city of Chania, Crete, Greece (see header image — surprised by the snow-capped White Mountains? We Cretans are known to be avid skiers). A long, long time ago, I played the drums in a prog-rock band.