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Calmon honored for research and teaching

EE professor awarded the James L. Massey Research & Teaching Award for Young Scholars

A man standing with his arms crossed.

Flavio P. Calmon. (Photo by Eliza Grinnell/Harvard SEAS)

Flavio P. Calmon, Associate Professor of Electrical Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), has received The James L. Massey Research & Teaching Award for Young Scholars from the IEEE Information Theory Society.

The award recognizes outstanding achievement in research and teaching by young scholars in the Information Theory community. 

Calmon, who joined SEAS in 2017, researches information theory, signal processing, and machine learning. His work applies information theory to analyze and design trustworthy and reliable learning systems.

He also investigates how information theory and machine learning can be applied for the social good, including topics such as privacy and fairness. Calmon’s research aims to characterize the limits of discrimination discovery and control in machine learning by combining legal and social science definitions of fairness with powerful mathematical tools from information theory, statistics, and optimization. This cross-disciplinary effort provides fundamental theory and design guidelines for data scientists and engineers who will create the next generation of responsible data-driven algorithms and applications.

IN 2019, Calmon received the NSF CAREER award and in 2020, Calmon received a commendation from the Harvard College's Dean of Undergraduate Education for "extraordinary teaching during extraordinary times." He has also received faculty awards from Google, IBM, and Amazon, the NSF-Amazon Fairness in AI award, the Harvard Data Science Initiative Bias2 award and the Harvard Lemann Brazil Research Fund Award. In 2022, he received the inaugural "Título de Honra ao Mérito" (Honor to the Merit Title) given to alumni from the Universidade de Brasília (Brazil).

Calmon received his Ph.D. in Electrical Engineering and Computer Science at MIT.
 

Topics: AI / Machine Learning, Awards

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