Pulkit Grover is an assistant professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University. He received his Ph.D. from the University of California, Berkeley in 2010. He focuses on interdisciplinary research directed towards developing a science of information for understanding/designing energy-efficient and stable decentralized systems (from low-power communication/computation systems, to large control, computational, and biological systems). He is the recipient of an NSF CAREER Award (2014), the best paper award at the International Symposium on Integrated Circuits (ISIC), the best student paper award at the IEEE Conference in Decision and Control (CDC) 2010, and the 2012 Leonard G. Abraham best paper award from the IEEE Communications Society for his work on energy-efficient communication. For his dissertation research, he received the 2011 Eli Jury Award from the Department of Electrical Engineering and Computer Sciences at UC Berkeley.
He was a co-editor of the IEEE Journal on Selected Areas in Communications (JSAC) special issues on "Energy Harvesting and Wirelessly Powered Communications" (2014-15).
Information Theory, Energy-Efficient Communication and Computing, and Neural Sensing
Novel Strategies for Sensing and Stimulating the Brain Noninvasively and Precisely
2010 Ph.D., Electrical Engineering and Computer Science, University of California Berkeley
2005 M.Tech, Electrical Engineering, Indian Institute of Technology, Kanpur
2003 B.Tech, Electrical Engineering, Indian Institute of Technology, Kanpur
IEEE Information Theory Society
Grover named distinguished lecturer
ECE’s Pulkit Grover was named the 2022-2023 Distinguished Lecturer for IEEE’s Information Theory Society. Grover plans to give talks in Asia, Africa, and various places in North and South America, supported by this program.
New grant to fund cardiac electrophysiology research
BME/MSE’s Tzahi Cohen-Karni was recently awarded a $3.1 NIH/NHLBI grant to further cardiac electrophysiology research. Over the next five years, Cohen-Karni will partner with Pitt’s Aditi Gurkar (co-PI), BME/MSE’s Adam Feinberg, MechE’s Carmel Majidi, and ECE’s Pulkit Grover to study the role of DNA damage in the cardiac unit using induced pluripotent stem cells.
BME/ECE faculty proposal selected for Facebook research grant
BME’s Jana Kainerstorfer and Sossena Wood and ECE’s Pulkit Grover have received a research ground from Facebook’s Engineering Approaches to Responsible Neural Interface Design program. Their research is focused on racially inclusive optical technology.
Finding silence in the brain
Alireza Chamanzar created an algorithm to locate regions of neural silence using an EEG, a widely accessible device that measures brain activity.
Engineering faculty awarded professorships
Engineering faculty Peter Adams, Elizabeth Dickey, Carlee Joe-Wong, Pulkit Grover, Alan McGaughey, Rahul Panat, and Douglas Weber were awarded professorship titles in February and March 2021.
Detecting and Stopping Brain Tsunamis with EEG Technology
A research team led by Carnegie Mellon University, in collaboration with clinicians at the University of Pittsburgh, is exploring how to detect and minimize brain damage.
College of Engineering announces Catalyst 2020 winners
The College of Engineering is pleased to announce that the College will fund three Catalyst proposals as winners of the Catalyst 2020 competition.
Managing necessary bias in AI
Some biases in AI might be necessary to satisfy critical business requirements, but how do we know if an AI recommendation is biased strictly for business necessities and not other reasons?
The power of EEG and student innovation
One group of CMU researchers has a wide variety of students exploring novel uses and implementation methods for an underutilized technology: EEG nodes.
Singularity Hub features ECE/BME joint DARPA project
Singularity Hub featured BME and ECE researchers’ project recently funded by DARPA, in which they are using ultrasound waves to pinpoint light interaction in targeted brain regions, then measuring brain waves through a wearable “hat.”
Wearable system to sense and stimulate the brain
A team of researchers from Carnegie Mellon is starting a project to design and implement a high-resolution, noninvasive neural interface that can be used as a wearable device.
Strength training deep neural networks
A team led by Pulkit Grover created more efficient deep neural networks called PolyDot coding to reduce errors and increase processing speed.