Assistant Professor of Business Administration
Nikos Trichakis is an assistant professor of business administration in the Technology and Operations Management Unit, teaching the Technology and Operations course in the MBA required curriculum and the Operations Management course in the doctoral curriculum.
In his research, Professor Trichakis investigates the interplay of fairness and efficiency in resource allocation problems and operations, together with the inherent tradeoffs that arise in balancing these objectives. He is interested in diverse industry applications ranging from health care to airlines to finance. His work has been published in Management Science and Operations Research.
Professor Trichakis received his Ph.D. in operations research from the Massachusetts Institute of Technology. He also holds MS degrees from Stanford University and Imperial College (UK), and a BS degree from Aristotle University (Greece), all in electrical and computer engineering. Before his doctoral studies, Professor Trichakis worked in software development at Sungard APT in London.
Fairness, Efficiency and Flexibility in Organ Allocation for Kidney Transplantation
We propose a scalable, data-driven method for designing national policies for the allocation of deceased donor kidneys to patients on a waiting list, in a fair and efficient way. We focus on policies that have the same form as the one currently used in the United States. In particular, we consider policies that are based on a point system, which ranks patients according to some priority criteria, e.g., waiting time, medical urgency, etc., or a combination thereof. Rather than making specific assumptions about fairness principles or priority criteria, our method offers the designer the flexibility to select his desired criteria and fairness constraints from a broad class of allowable constraints.
On the Efficiency-Fairness Trade-Off
How does one approach the problem of designing the "right" objective for a given resource allocation problem? The notion of what is right can be fairly nebulous; we consider two issues that we see as key: efficiency and fairness. We approach the problem of designing objectives that account for the natural tension between efficiency and fairness in the context of a framework that captures resource allocation problems of interest to managers.
The Price of Fairness
We study resource allocation problems that involve multiple self-interested parties and a central decision maker. We introduce and study the price of fairness, which is the relative system efficiency loss under a "fair" allocation assuming that a fully efficient allocation is one that maximizes the sum of player utilities. We focus on two notions of fairness, proportional fairness and max-min fairness. For these notions, we provide a tight characterization of the price of fairness for a broad family of problems.