Michael Bassik

We study how endocytic pathogens such as bacterial toxins, viruses, and protein aggregates enter the cell, disrupt homeostasis, and cause apoptosis. More broadly, we would like to understand how diverse stresses induced by biological, chemical, and therapeutic agents signal to the cell death machinery.
To do this, we use basic cell biology and biochemistry, as well as novel ultra-complex shRNA libraries we have developed, which have allowed the first systematic genetic interaction maps in mammalian cells. A complementary interest is the development of technologies for screening and measuring genetic interactions, with the ultimate goal of finding synergistic drug targets for endocytic pathogens and other diseases such as cancer and Alzheimer’s.

Akshay Chaudhari

Akshay’s primary research interest lies at the intersection of artificial intelligence and medical imaging. His group develops new techniques for accelerated MRI acquisition and downstream image analysis, extracting prognostic insights from already-acquired CT imaging. To enable these goals, his group develops new multi-modal deep learning algorithms for healthcare that leverage computer vision, natural language, and medical records, with a large emphasis on data-efficiency and model robustness.

Research Areas: 

  • Machine Learning
  • Medical Imaging
  • Informatics
  • Computer Vision