Venkatesh Saligrama Elevated to IEEE Fellow

The IEEE is the world’s leading professional association for advancing technology for humanity. Through its 400,000 plus members in 160 countries, the association is a leading authority on a wide variety of areas ranging from aerospace systems, computers and telecommunications to biomedical engineering, electric power and consumer electronics. The IEEE Grade of Fellow is conferred by the IEEE Board of Directors upon a person with an outstanding record of accomplishments in any of the IEEE fields of interest. The total number selected in any one year cannot exceed one-tenth of one- percent of the total voting membership. IEEE Fellow is the highest grade of membership and is recognized by the technical community as a prestigious honor and an important career achievement.

Dr. Venkatesh Saligrama is a faculty member of the Information and Data Sciences (IDS) Group in the Department of Electrical and Computer Engineering at Boston University and directs the data science and machine learning laboratory. His recent work deals with machine learning that accounts for limited resources such as limited training data or limited annotations available for supervision, zero-shot learning, and cost-sensitive learning. Traditional Machine learning relies on supervision to train algorithms to accurately predict outcomes or behaviors, but when that data is limited/unavailable, or in general supervision and prediction is constrained in various ways, existing methods are unable guide algorithms towards making correct decisions. Dr. Saligrama’s work focuses on understanding such non-ideal scenarios to deal with learning and prediction in such resource-constrained environments.