WID Postdocs expand the institute’s research portfolio and expertise, bringing new perspectives to bear on problems.
Continuous optimization for machine learning, reinforcement learning and other data science problems
Algorithm and theory development in interactive machine learning
Developing optimization algorithms that are both computationally and statistically efficient
Injection molding, Polymer processing, Process monitoring and optimization
A CRISPR/Cas9 based therapeutic strategy for Alzheimer's disease
Causal inference relating to education policy
Designing efficient estimators which are robust to aggressive noise models
Engineering organotypic 2D CNS tissues from human pluripotent stem cells
Inference and decision-making with missing or unobserved information.
Designing practical, data-efficient algorithms with rigorous guarantees for statistical applications
To understand the activation mechanism of p300/CBP protein acetyltransferase by acyl-CoA metabolism.
Effects of community interactions on microbial physiology
Theoretical research on the emergence of life-like systems from chemical reaction networks
Relationship between genomes and their environments to predict organisms' fitness correlations.
Development of computational methods for inference and analysis of biological networks
I work to determine antibiotic resistance in bacteria by analyzing images and genomes using AI.
Bioinformatics based on networks and large-scale quantitative genomics.
Integrate computational and experimental models of host-pathogen interaction in bacterial infections
Mass spectrometry-based metabolomics workflows for antibiotic discovery