Dr. Sarah Dean

Biography

Sarah Dean is an Assistant Professor in the Department of Computer Science at Cornell University, specializing in the interplay of optimization and machine learning for real-world systems. Her research emphasizes developing data-driven methods that enhance control and decision-making processes, with applications spanning robotics and recommendation systems. Dean's academic journey includes earning a PhD in Electrical Engineering and Computer Sciences from the University of California, Berkeley, where she was a founding member of the Graduates Engaged for Extended Scholarship in Computing Engineering (GEESE). She has held internships at relevant institutions and has co-organized several workshops on machine learning and recommendation ecosystems. Dean’s publications include significant contributions to conferences like NeuRIPS, ICML, and CDC, tackling topics such as learning dynamics, bandit algorithms, and user-centered recommendation systems. In her teaching role at Cornell, she has developed courses related to machine learning, mentoring numerous students at both the Master's and PhD levels. Her work has received recognition including the NSF CAREER award and she is actively involved in interdisciplinary collaborations.

Research Interests

Experience