I am a 5th year PhD Candidate at the Electrical and Computer Engineering Dept. of Carnegie Mellon University. My research primarily revolves around the theory and practice of incentive-compatibility and trust in user-centric resource allocation in wireless networks.
I’ve worked on pricing optimizations for cellular dataplans, auction mechanisms for 5G and reinforcement learning for budget-driven bidding. Lately, I’ve been intrigued by trust and scalability issues that emerge in decentralized wireless networks, and have proposed robust mechanisms for making cryptocurrency payments in large-scale blockchain-based marketplaces and for enabling subscription-less connectivity between devices and last-mile networks using blockchains. I’m also interested in understanding the mechanics of pricing crypto-tokens (i.e. tokenomics) and am collaborating with blockchain-based IoT service provider Nodle in this effort.
Apart from my main line of research, I’ve been involved in projects around mining contextual information from IoT data for security and other applications; of highlight, I recently showed that almost 100% lane-level localization accuracy can be achieved with just 5 meters of accelerometer driving data, using deep LSTM networks.
I am co-advised by Prof. Patrick Tague and Prof. Carlee Joe-Wong, and am a member of the MEWS and LIONS research groups. My research has been supported by various NSF and DARPA grants. I recently proposed my thesis entitled Incentivizing User-centric Resource Allocation in Wireless Networks in Real time, with Prof. Patrick Tague, Prof. Carlee Joe-Wong, Prof. Aron Laszka and Dr. Anand Raman as my committee.
I did my undergraduate studies at the ECE dept. of Rutgers University, New Brunswick campus. I finished the Honors program in 3 years and graduated Summa Cum Laude in 2013. During this time, I also conducted an year of undergraduate research at WINLAB, and was recognized as a James Slade Scholar upon graduation.