Columbia University

Abhi Adhikari

Ph.D. Student

Electrical Engineering
Columbia University

Email: aa4832[at]columbia.edu

Abhi Adhikari received a B.S. in Computer Engineering (Magna Cum Laude) from Drexel University in 2021. His research interests are in software-defined/cognitive radio, 5G/6G networks, mmWave, and radar.

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Education

Columbia University

  • M.S./Ph.D. Student, Electrical Engineering Fall 2021 – Present
    • Research Interests: Wireless and Mobile Networking
    • Advisor: Prof. Gil Zussman

Drexel University

  • B.S. Computer Engineering, Graduated 2021
  • Final GPA:3.85, Magna Cum Laude

Awards & Honors

  • Drexel University Dean’s List (2021)
  • IEEE-HKN (2020)
  • Tau Beta Pi (2020)
  • Pennsylvania NASA Space Grant Scholarship (2017, 2018)

Publications

Patents

  • Adhikari, Abhishek 2019. “System and method for controlling, sharing, release and management of digital data between smart mobile device(s) and external device(s) using a connector pad.” U.S. Patent 10,348,691 filed May 14, 2018, and issued July 9, 2019.
  • Adhikari, Abhishek 2018. “System and method for making a quick connection between a smart mobile device and external audio speakers and video monitors using a connector pad.” U.S. Patent 9,998,848 filed November 13, 2015, and issued June 12, 2018.

Industry Experience

  • Lockheed Martin Advanced Technologies Laboratories (ATL)
    • Senior Capstone Project – Team Lead, September 2020 – June 2021
      • Designed a software-defined mmWave radar testbed to enable rapid prototyping of multi-target tracking (MTT) algorithms for future autonomous vehicles.
      • Built and tested a Joint Probabilistic Data Association tracking filter with real-world software-defined radio (SDR) Radar MTT data collected by testbed.
      • Leveraged a channel emulator and ray-tracing software for modeling the RF signature of the Ben Franklin Bridge to perform MTT in a complex radar environment.
    • Applied Research Co-Op, May 2020 – September 2020
      • Created a GNU Radio Out-Of-Tree Module to wrap a C++ radar algorithm (CA-CFAR) into a Python interface for use with SDR.
      • Wrote a C++ benchmarking tool to characterize radar algorithm performance
      • Enabled real-time I/Q collection from SDR through SoapySDR, SDRAngel, and UHD.
      • Presented work to Lockheed ATL Chief Technology Officer in Quarterly Performance Review.