Nikos Trichakis

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Nikos Trichakis

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Nikolaos (Nikos) Trichakis is the J.C. Penney Professor of Management and a Professor of Operations Management at the MIT Sloan School of Management.

His research interests include optimization under uncertainty, data-driven optimization and analytics, with application in healthcare, supply chain management, and finance. Trichakis is also interested in the interplay of fairness and efficiency in resource allocation problems and operations, and the inherent tradeoffs that arise in balancing these objectives.

Before his doctoral studies, Trichakis worked in quantitative finance at SunGard APT in London. Prior to joining MIT, Trichakis was on the faculty of Harvard Business School.

He received his BS degree from Aristotle University (Greece), and MS degrees from Stanford University and Imperial College (UK), all in electrical and computer engineering. He holds a PhD in operations research from MIT.

Honors

INFORMS honors Trichakis with multiple awards, including one with Bertsimas

November 27, 2023

Trichakis and co-authors win first prize

Trichakis wins best paper award

Trichakis wins 2020 Koopman Prize

Trichakis honored for best working paper

Trichakis wins 2021 digital teaching award

Young Researchers Prize awarded to Trichakis

MIT authors win second prize

Publications

"Reshaping National Organ Allocation Policy."

Papalexopoulos, Theodore, James Alcorn, Dimitris Bertsimas, Rebecca Goff, Darren Stewart, and Nikolaos Trichakis. Operations Research Vol. 72, No. 4 (2024): 1475-1486.

"Dynamic Project Expediting: A Stochastic Shortest-Path Approach."

Bertazzi, Luca, Riccardo Mogre, and Nikolaos Trichakis. Management Science Vol. 70, No. 6 (2024): 3748-3768.

"Pareto Adaptive Robust Optimality via a Fourier-Motzkin Elimination Lens."

Bertsimas, Dimitris, Stefan C.M. ten Eikelder, Dick den Hertog, and Nikolaos Trichakis. Mathematical Programming Vol. 205, (2024): 485-538. arXiv Preprint.

"On the Impact of Mass Screening for SARS-CoV-2 Through Self-testing in Greece."

Gilmour, Samuel, Spyros Sapounas, Kimon Drakopoulos, Patrick Jaillet, Gkikas Magiorkinis, and Nikolaos Trichakis. Frontiers in Public Health Vol. 12, (2024).

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Researchers use data analytics for national lung transplant allocation

Dimitris Bertsimas and Nikolaos Trichakis modeled a points-based framework called continuous distribution (CD) based on AI and machine learning to aid in allocating lung transplants.

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Ideas Made to Matter

How an analytics-based predictive model can improve kidney transplant survival rates

Doctors need to trust their intuition, but a decision support tool can help them make hard choices.

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