Nikos Trichakis


Nikos Trichakis


Nikolaos (Nikos) Trichakis is the Zenon Zannetos (1955) Career Development Professor and an Associate 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.


Young Researchers Prize awarded to Trichakis

Trichakis wins best paper award

Trichakis honored for best working paper

MIT authors win second prize


"Dynamic Pricing under Debt: Spiraling Distortions and Efficiency Losses."

Besbes, Omar, Dan A. Iancu, and Nikos Trichakis. Management Science. Forthcoming.

"Is Operating Flexibility Harmful Under Debt?"

Iancu, Dan A., Nikos Trichakis, and Gerry Tsoukalas. Management Science Vol. 63, No. 6 (2017): 1730-1776.

"Fairness and Eciency in Multiportfolio Optimization."

Iancu, Dan A., and Nikolaos Trichakis. Operations Research Vol. 62, No. 6 (2014): 1285-1301.

"Pareto Efficiency in Robust Optimization."

Iancu, Dan A., and Nikolaos Trichakis. Management Science Vol. 60, No. 1 (2014): 130 - 147.

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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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MIT Sloan professors design model to improve decision-making process for kidney transplantation

MIT Sloan Profs. Dimitris Bertsimas and Prof. Nikos Trichakis created a data-based model to improve the kidney transplant decision-making process.

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