Subhodip (Leo) Biswas
During his time at ARL, Leo served as a Journeyman Fellow at the Computational and Information Sciences division. His research focused on developing Bayesian optimization methods for problems with blackbox objectives and constraints. His work had wide-ranging applications, including uncertainty-aware optimization, AutoML, and general algorithmic configuration.
Leo’s contributions to the field were significant, culminating in an oral paper accepted at IEEE CEC 2021. His work on single-objective bound-constrained optimization was particularly noteworthy, ranking 2nd in its category.
Throughout his tenure, Leo demonstrated a keen ability to apply advanced machine learning techniques to complex real-world problems, furthering the field’s understanding and applications of AI in various domains.
For more information about Leo’s professional background and current work, please visit his LinkedIn profile.