My office at the Technion:

423, Cooper building, dept. IE&M

Hello, and welcome to my homepage!

I am Fedor Sandomirskiy, a postdoctoral researcher at Technion Game Theory group and a member of Mechanism Design for Data Science group. I am also affiliated with the Game Theory Lab at HSE in St.Petersburg, which I was heading prior to joining Technion.

I am looking for a postdoc/visiting position starting in the autumn of 2020.

My research is on game theory and its applications to economic design.

I am especially interested in

  • mechanisms for fair and efficient allocation of resources

  • strategic use of information and information design.

I enjoy problems whose practical applications required deep math. On the economic side, I am using both classical microeconomic approach together with the novel ideas of algorithmic game theory, and, on the math side, I like the interplay of convex analysis, probability, and functional analysis.

My research statement tells more about my research and CV about my experience. Check also my papers and slides.

News:
 

September 2019: A short note "A polynomial-time algorithm for computing a Pareto optimal and almost proportional allocation"

with Haris Aziz and Herve Moulin

In this note, we show that Pareto-optimal and almost-fair (Proportional up to 1 item) allocations of a mixture of indivisible goods and bads always exist and can be computed in a strongly-polynomial time.

The technique is based on the trading-cycle algorithm for finding divisible Pareto-improvements from the recent working paper "Fair division with minimal sharing" with Erel Segal-Halevi and on an extension of Barman-Krishnamurthy rounding.

August 2019: New working paper "Fair division with minimal sharing"

with Erel Segal-Halevi

Siblings who inherited several apartments would not be satisfied by an allocation resulting in an apartment with 50% probability or envy-free up to one apartment. We suggest a new approach to fair division of valuable items, which bridges the modern "divisible" and "indivisible" literature: sharing minimization. The problem of sharing-minimization among fair Pareto-optimal allocations turns out to be algorithmically-tractable for almost all instances.

July 2019: New working paper "Algorithms for competitive division of chores"

with Simina Branzei

This is the first explicit algorithm for computing market equilibria of "non-convex" exchange economies that have disconnected equilibrium set. We avoid the "black-box" of Cell-Enumeration technique, used in the literature, by the novel approach based on enumeration of all the faces of the Pareto frontier via a simple 2-agent reduction.

The results are applied to approximately fair division of indivisible chores.

May 2019: Tutorial

"Appeal and challenges of competitive approach to fair resource allocation"

Vasilis Gkatzelis and I created a tutorial at the “De Aequa Divisione” workshop at LUISS (Rome). Slides are available on the web-page of the workshop.

May 2019: New working paper "Protecting the Protected Group: Circumventing Harmful Fairness" with Omer Ben-Porat and Moshe Tennenholtz

Fairness constraints used for Fair Machine Learning may harm the protected group because the "price of fairness" is reallocated to this group by self-interested decision makers (e.g., a bank giving loans).

March 2019: New working paper "A simple online fair division problem"

with Herve Moulin and Anna Bogomolnaia

We propose a new family of allocation rules that, using minimal statistical information about the environment,  achieve fairness and welfare guarantees. These are the first results on dynamic resource allocation that combine both fairness and efficiency design objectives.