Prabuddha Chakraborty

Email: prabuddha@maine.edu

Prabuddha Chakraborty is an Assistant Professor at the University of Maine. His research interest lies in the intersecting areas of Artificial Intelligence, Internet-of-Things, and system security. He received his PhD in Electrical and Computer Engineering from the University of Florida. He has worked within the Security Software Team at Texas Instruments and the FPGA acceleration R&D team at Xilinx. His research effort has so far led to many peer-reviewed journal and conference articles published or accepted in prestigious venues such as Nature Scientific Reports, IEEE Internet of Things Journal, Neural Computing and Applications, IEEE Transactions on Information Forensics and Security, International Test Conference, and Design Automation Conference. He has more than 15 US patents & copyrights filed/granted for different technologies he has developed. He is a recipient of the Certificate of Outstanding Merit from the Herbert Wertheim College of Engineering at the University of Florida in 2021, for his academic and research excellence. He has also received several awards/honors for his research contributions including the TTTC’s E. J. McCluskey Best Doctoral Thesis 2022 Award, Best Hardware Demo Award (at IEEE HOST 2019) and the Top Picks in Hardware and Embedded Security award 2021 (by IEEE HSTTC).

Research Interests:

System Security:
- Hardware Security (Trojans, Obfuscation, Side-Channel)
- Hardware Software Co-Security (Software Analysis, Timing Side-Channel)
- Applied Artificial Intelligence for Security
Edge Intelligence and Internet-of-Things (IoT):
- Applied Artificial Intelligence for efficient data storage @ edge/IoT
- Optimal IoT system design generation for efficiency & security
- Image Processing & Computer Vision for IoT systems
- Intelligent Transport Systems

Awards & Honors

ASCC, University of Maine, Director's Award (Outstanding Faculty): For outstanding research performance in collaboration with ASCC.
TTTC’s E. J. McCluskey Best Doctoral Thesis 2022 Award (1st place): For the most impactful doctoral student work in the field of electronic test technology.

https://www.ieee-tttc.org/tttcs-e-j-mccluskey-doctoral-thesis-award/

Innovation of the Year Award, UF Innovate | Tech Licensing, University of Florida, 2022: For the SAVIOR framework which enables remote charging of electric vehicle batteries, replenishing them on-the-go with the help of drones & mobile charging stations.
DAC Young Fellow, 2021: I was accepted in the DAC Young Fellows Program 2021.
Top Picks (Winner) in Hardware and Embedded Security 2021, IEEE HSTTC: Our work "SAIL: Machine Learning Guided Structural Analysis Attack on Hardware Obfuscation", was a winner of the Top Picks in Hardware and Embedded Security 2021. Awarded by the IEEE Hardware Security and Trust Technical Committee (IEEE HSTTC).
IEEE Spectrum Website Article: Featured our work related to on-the-go electric vehicle charging for near-perpetual motion and environmental sustainability.

https://spectrum.ieee.org/will-electric-cars-on-the-highway-emulate-airtoair-refueling

Certificate of Outstanding Achievement: Awarded by the Herbert Wertheim College of Engineering, University of Florida in 2021. Awarded for outstanding academic and research excellence.
Best Hardware Demo (1st): 2019 IEEE International Symp. on Hardware Oriented Security and Trust. Awarded for the presentation of a CAD framework for machine learning based IP trust verification.
Best Poster (1st, Hardware Obfuscation): 2019 FICS Annual Conference on Cybersecurity. Awarded for the presentation of a machine learning guided attack on hardware obfuscation.
Best Technical Demo (1st): 2019 FICS Annual Conference on Cybersecurity. Awarded for the demonstration of a CAD framework for machine learning based IP trust verification.
Best Hardware Demo (2nd): 2019 Warren B. Nelms Annual IoT Conference 2019. Awarded for the demonstration of a smart home with a first-responder drone network for security and safety hazards.

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