Lab Members

After graduating magna cum laude from Princeton University, Dr. Hafler earned his MD/PhD from Harvard Medical School and completed a postdoctoral fellowship funded by the Howard Hughes Medical Institute in Connie Cepko's laboratory at Harvard.  He completed an ophthalmology residency at Yale School of Medicine/Yale-New Haven Hospital and a fellowship in retina at Mass. Eye and Ear as a Heed Fellow where he specialized in Inherited Retinal Degenerations.  Following his fellowship, he received a K08 Clinical Scientist Development Award from the NIH and joined the faculty at Harvard Medical School where he served on Mass. Eye and Ear’s Retina Service and in the Emergency and Trauma Eye Care Department.  He has a laboratory in the Department of Ophthalmology in the Yale School of Medicine where he recently generated the first single-cell human retinal transcriptomic atlas and identified the cell types driving macular degeneration. He recently received the American Society for Clinical Investigation Young Physician Scientist Award, the Thome Memorial Foundation Award for AMD Research, and was named the William R. Orthwein, Jr. ’38 Yale Scholar. He studies macular degeneration and glaucoma using single-cell transcriptomics to identify novel therapeutic approaches.

I am a neuropathologist and researcher in neuroimmunology. My background is in electrophysiology and biomedical engineering of neural interface and neural information processing systems. My interests are in diseases of the central nervous system, including motor system diseases and cancer. I am working on advancing the techniques of computational pathology in order to better understand and diagnose diseases. My research involves the application of machine learning, image analysis, and statistics to histology and genomic data with the goal of better characterizing and classifying tumors. I am developing software to analyze histologic images taken from the kinds of slides produced in the routine clinical evaluation of tissue.  By using statistical and machine learning techniques, these algorithms look for patterns in cell placement and morphology that correspond to the tissue genetic profiles. I believe this simultaneous genotypic and phenotypic characterization of tumors will provide a deeper understanding of neurobiology, neuropathology, and caner immunology, and identify key elements of CNS microenvironments whose interactions advance our explanations and predictions of pathologic processes affecting the brain, retina, spinal cord, and peripheral nervous system.