Manik is a 6th year MD/PhD student writing novel machine learning algorithms to identify pathogenic disease mechanisms from large patient-derived datasets as a member of the Krishnaswamy Lab. In his most recent work, Manik developed and applied multiscale PHATE, an unsupervised machine learning tool that learns the structure of data across granularities, to 54 million cells extracted from 163 patients admitted to Yale-New Haven Hospital with COVID19. Through this analysis he identified cell types and subtypes associated with disease mortality. In another work, Manik developed and applied CATCH to single-cell data produced from the retina of patients with age-related macular degeneration. Through this work, Manik identified a pathogenic signaling axis between microglia and astrocytes in advanced disease helping identify novel targets for therapeutic intervention. As an MSTP student, Manik is funded via an Individual NRSA Fellowship from the National Institute on Allergy and Infectious Disease (MD-PhD F30 grant) and Yale's MD-PhD Medical Scientist Training Program (T32 grant). He spends his time outside of lab taking care of patients in the hospital and playing cricket. He was a neurobiology major in undergrad and wrote his thesis on the genetic architecture of multiple sclerosis.