By Pulkit Grover (Carnegie Mellon University)
Talk Abstract: Characterizing the scalp to brain and the brain to scalp transfer functions allows us to look at them as channels, providing new insights, fundamental limits, and practical strategies for high resolution sensing and stimulation of the brain.
Speaker Bio: Pulkit (Ph.D. UC Berkeley’10, B.Tech, M.Tech IIT Kanpur) is the Angel Jordan Professor at CMU. His current work involves thought and laboratory experiments to expand and develop a science of information for neural sensing, and stimulation, with increasing focus on identifying and eliminating racial biases these systems can have, and improving accessibility by examining limits of non-invasive systems. To bring these to practice, his lab works extensively with data scientists, system and device engineers, neuroscientists, and clinicians. Specifically, work of his lab is focused on a) fair and explainable AI at algorithm, theory, and hardware level; b) tools (theoretical, computational, and hardware) for understanding the healthy brain, and understanding, diagnosing, and treating disorders such as epilepsy, stroke, and traumatic brain injuries. Pulkit received the 2010 best student paper award at IEEE Conference on Decision and Control; the 2011 Eli Jury Dissertation Award from UC Berkeley; the 2012 Leonard G. Abraham best journal paper award (IEEE ComSoc); a 2014 NSF CAREER award; a 2018 inaugural award from the Chuck Noll Foundation for Brain Injury Research; the 2018 Spira Excellence in Teaching Award (CMU), and the 2019 best tutorial paper award (IEEE ComSoc). He’s the PI of the SharpFocus award, a multi-institution effort aimed at mm- and msec-scale noninvasive brain sensing and stimulation, and is a distinguished lecturer for the IEEE Information Theory Society for 2022-23. He co-founded Precision Neuroscopics, Inc., a startup for commercializing the first neural sensing EEG systems that work with Black hair, winning the first place at UpPrize 2022 for socially driven innovation.