Wow, the world is different. I was supposed to attend the 10th NSF/TCPP Workshop on Parallel and Distributed Computing Education (EduPar-20) in conjunction with the 34th IEEE International Parallel & Distributed Processing Symposium in beautiful New Orleans, LA but then the COVID-19 pandemic happened, and IPDPS went virtual. The EduPar'20 team did a fantastic job transitioning the conference to a virtual format, and I really enjoyed attending.
I was delighted to learn at the end of the conference that my paper, “PDCUnplugged: A Free Repository of Unplugged Parallel & Distributed Computing Activities” won the Best Paper award!
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I’m in a state of shock… I was just notified today that I just won the ASEE Engineering Research Council’s Curtis W. Mcgraw Research Award in the non-PhD granting program category! I will be receiving the award at the ASEE ERC’s annual business meeting in March.
This award means a lot to me. I was selected as a McGraw-Hill national merit scholar my senior year of high school. It’s amazing to receive an award as an associate professor that is named after one of the founders of McGraw-Hill, a company I credit with giving me one of the most valuable scholarships I received as an undergrad.
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Since 2014, I have been one of the advisors of an interdiscplinary capstone team that works on building out an emulated power grid. Our goal is to try and publish with the students every year, but this is the first year that a student-led paper won Best Paper!
My student, Spencer Drakontaidis presented the paper “Investigating a Raspberry Pi Cluster for Detecting Anomalies in the Smart Grid”, at the IEEE MIT Undergraduate Research Technology Conference (URTC'17).
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Yay! The paper that Dr. Aaron St. Leger and I wrote entitled, “Leveraging Single Board Computers for Anomaly Detection in the Smart Grid” won the Best Paper Award in the Information Security track at the at the 8th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON’17) . Dr. St. Leger and I have been working together since 2014, and this paper shows the application of a single board computer (specifically, the Raspberry Pi) for real-time anomaly detection of synchrophasor data, and proposes a distributed architecture for detecting anomalous behavior in Wide Area Monitoring Systems (WAMS) for the smart grid.
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