Ahmet Alacaoglu
Continuous optimization for machine learning, reinforcement learning and other data science problems
Postdoctoral Associates
WID Postdocs expand the institute’s research portfolio and expertise, bringing new perspectives to bear on problems.
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Stephanie Colón-Santos
Analysis of complex chemical systems relevant to the origins of life.
Jinsu Gim
Injection molding, Polymer processing, Process monitoring and optimization
Sushrut Karmalkar
Designing efficient estimators which are robust to aggressive noise models
Julian Katz-Samuels
Developing adaptive learning algorithms that are data-efficient and scalable
Gavin Knight
Engineering organotypic 2D CNS tissues from human pluripotent stem cells
Jasper Lee
Designing practical, data-efficient algorithms with rigorous guarantees for statistical applications
Zhen Peng
Theoretical research on the emergence of life-like systems from chemical reaction networks
Tolulope Perrin-Stowe
Relationship between genomes and their environments to predict organisms' fitness correlations.
Saptarshi Pyne
Development of computational methods for inference and analysis of biological networks
Junha Shin
Bioinformatics based on networks and large-scale quantitative genomics.
Chaobing Song
Large scale and robust optimization in machine learning, min-max problems with game theory
Jayaraman Tharmalingam
Integrate computational and experimental models of host-pathogen interaction in bacterial infections