Jad Salem

Research

My research is centered on the societal implications of decision-making, particularly automated decision-making. Decision-making processes such as those in the hiring pipeline, loan-granting, targeted advertising, dynamic pricing, and more, directly affect people's lives. As such, attention must be paid in order to avoid outcomes which are discriminatory or which reinforce societal inequalities. Since these decisions are often automated, I'm interested in algorithmic techniques for mitigating bias and producing fairer outcomes.

Papers

Using Algorithms to Tame Discrimination: A Path to Algorithmic Diversity, Equity, and Inclusion
Conditionally accepted to the UC Davis Law Review 2023
Joint with Swati Gupta and Deven Desai
Don't let Ricci v. DeStefano Hold You Back: A Bias-Aware Legal Solution to the Hiring Paradox
ACM Conference on Fairness, Accountability, and Transparency (FAccT 2022)
Joint with Swati Gupta and Deven Desai
Algorithmic Challenges in Ensuring Fairness at the Time of Decision
In submission to Operations Research
Extended abstract to appear in the Proceedings of the 18th Conference on Web and Internet Economics (WINE 2022)
Joint with Swati Gupta and Vijay Kamble
Secretary Problems with Biased Evaluations using Partial Ordinal Information
Received a Minor Revision from Management Science in August 2022
Extended abstract appeared in the Proceedings of the 16th Conference on Web and Internet Economics (WINE 2020)
Joint with Swati Gupta

Other Writing

Algorithmic Challenges in Ensuring Fairness at the Time of Decision
Forthcoming in OPTIMA (Mathematical Optimization Society Newsletter)
Co-written with Vijay Kamble
Temporal Notions of Algorithmic Fairness
Invited book chapter in Springer's Studies in Computational Intelligence
In preparation, co-written with Swati Gupta and Vijay Kamble