# Aaron Roth

Aaron Roth is an American computer scientist and the Henry Salvatori Professor of Computer and Cognitive Science at the University of Pennsylvania, known for research in algorithmic fairness, differential privacy, and algorithmic game theory.

Aaron Roth is an American computer scientist specializing in algorithm design, algorithmic fairness, differential privacy, and algorithmic game theory. He holds the Henry Salvatori Professorship of Computer and Cognitive Science at the University of Pennsylvania, where he has been a faculty member since 2011. Roth's work addresses how to build computational systems that are both socially responsible and privacy-preserving, topics that have gained prominence with the rise of [machine-learning](https://www.wikiprompt.org/wiki/machine-learning) and data-driven decision-making.

Roth is the son of Alvin E. Roth, a former Harvard University professor who received the Nobel Memorial Prize in Economic Sciences in 2012. He completed his bachelor's degree in computer science at Columbia University in 2006 and earned his PhD from [Carnegie Mellon University](https://www.wikiprompt.org/wiki/carnegie-mellon-university) under the supervision of Avrim Blum. After a postdoctoral year at Microsoft Research New England, he joined the University of Pennsylvania faculty in 2011 as the Raj and Neera Singh Assistant Professor of Computer Science. He was promoted to Class of 1940 Bicentennial Term Associate Professor in 2017.

## Research Contributions

Roth's research sits at the intersection of theoretical computer science and social policy. His work on differential privacy provides formal guarantees that individual data points cannot be inferred from aggregate statistics, a foundational concern for [artificial-intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) systems that process sensitive information. In algorithmic fairness, he investigates how to design decision-making algorithms - such as those used in hiring, lending, or criminal justice - that avoid discriminatory outcomes while maintaining accuracy and efficiency.

His contributions to algorithmic game theory explore how strategic agents interact with computational systems, particularly in settings where incentives and privacy constraints interact. This theoretical grounding has practical implications for platforms that rely on user data, including [large language models](https://www.wikiprompt.org/wiki/large-language-model) and other [generative AI](https://www.wikiprompt.org/wiki/generative-ai) systems that are trained on massive datasets.

## The Ethical Algorithm

In 2019, Roth co-authored the book *The Ethical Algorithm: The Science of Socially Aware Algorithm Design* with Michael Kearns, a professor at the University of Pennsylvania. The book explains, for a general audience, how concepts from computer science - including differential privacy, fairness constraints, and game-theoretic analysis - can be used to build algorithms that respect social values. It received a PROSE Award in the Computer and Information Sciences category, recognizing excellence in professional and scholarly publishing.

The book argues that ethical concerns in computing are not merely philosophical but can be addressed through rigorous mathematical and engineering techniques. It has been influential in framing discussions about responsible [artificial-intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) development, complementing technical work in areas such as [deep-learning](https://www.wikiprompt.org/wiki/deep-learning) and [neural networks](https://www.wikiprompt.org/wiki/neural-network).

## Awards and Recognition

Roth has received several major awards for his research. He was granted an NSF Career Award in 2013, which supports early-career faculty who serve as academic role models. In 2015, he received a Sloan Research Fellowship, awarded to outstanding researchers in the early stages of their careers. The following year, in 2016, he was honored with a Presidential Early Career Award for Scientists and Engineers (PECASE), the highest honor bestowed by the U.S. government on science and engineering professionals in the early stages of their research careers. In 2023, he received the Hans Sigrist Prize, which recognizes research that addresses significant societal questions.

## Teaching and Mentorship

As a professor at the University of Pennsylvania, Roth teaches courses on algorithms, data privacy, and the societal implications of computing. He has supervised numerous PhD students and postdoctoral researchers who have gone on to positions in academia and industry. His teaching emphasizes the importance of considering ethical dimensions in algorithm design, a perspective that has become increasingly relevant as [machine-learning](https://www.wikiprompt.org/wiki/machine-learning) systems are deployed across sectors such as healthcare, finance, and public administration.

Roth's work has been supported by grants from the National Science Foundation and other agencies, reflecting the broad interest in his research agenda. He frequently speaks at conferences and workshops on topics related to privacy and fairness, contributing to the ongoing policy debates about how to regulate [artificial-intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) technologies.

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Source: https://www.wikiprompt.org/wiki/aaron-roth
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Last updated: 2026-09-05T13:29:04.174908+00:00