Pulkit Grover is an assistant professor in the Department of Electical and Computer Engineering at Carnegie Mellon University. He recieved 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
Engineering Research Accelerator
Catalyst 2020 winners announced
The College of Engineering has announced the winners of the Catalyst 2020 competition. Their proposals will be funded by the College of Engineering.
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 researchers in ECE 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.
Electrical and Computer Engineering
Pulkit Grover improves EEG brain imaging
ECE’s Pulkit Grover researched how to resolve greater imaging clarity from EEG scans on epileptic patients to reduce the need to invasive scans.
Grover and former Steeler Merrill Hoge interviewed by KDKA
ECE's Pulkit Grover spoke with KDKA's Sunday Business Page with Jon Delano on his recent grant from the Chuck Noll Foundation for Brain Injury Research to use a newly modified high-density electroencephalogram (EEG) to identify early markers for worsening brain injuries.
The 2018 CIT Dean’s Early Career Fellows
Eight young CMU faculty receive awards for their outstanding contributions to the university.
Grover and Kelly receive Chuck Noll Foundation award
ECE's Pulkit Grover and Shawn Kelly, as part of a research team, received funding from the Chuck Noll Foundation to conduct research on preventative care to monitor and treat brain tsunamis.
Innovation in brain imaging
Grover and his team have been focused on improving the resolution of EEG neural imaging technology, a portable and non-invasive brain imaging system. Their research goes against the trend in the field of neuroscience.