About
Hi! I'm Jimmy Dani, a PhD student in the Department of Computer Science at Texas A&M University. I'm advised by Dr. Nitesh Saxena in Security and Privacy In Emerging Computing and Networking System (SPIES) research lab. I am broadly interested in building privacy engineering tools using machine learning and artificial intelligence.
My interests in applying Deep Learning and Artificial Intelligence for real world problems have given me a sense of purpose as I have acquired more skills over the years. More I work in this field, more I appreciate its ability to handle problems, such as secure authentication, computational biology, and machine vision, with such elegance.
I completed my MS in Computer Science from Texas A&M University - Corpus Christi. My master’s thesis was in the area of precision agriculture, where I had an opportunity to help automate plant phenotyping using data analytics and artificial intelligence.
Publications
TripletPower: Deep-Learning Side-Channel Attacks over Few Traces
2023
Chenggang Wang, Jimmy Dani, Shane Reilly, Austen Brownfield, Boyang Wang, John M Emmert. 2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)
Link: IEEE digital library
Adaptive Fingerprinting: Website Fingerprinting Over Encrypted Traffic
2021
Chenggang Wang, Jimmy Dani, Xiang Li, Xiaodong Jia, and Boyang Wang. 2021. Adaptive Fingerprinting: Website Fingerprinting over Few Encrypted Traffic. In Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy (CODASPY '21). Association for Computing Machinery, New York, NY, USA, 149–160. DOI:https://doi.org/10.1145/3422337.3447835
Link: ACM digital library
HiddenText: Cross-Trace Website Fingerprinting Over Encrypted Traffic
2021
J. Dani and B. Wang, "HiddenText: Cross-Trace Website Fingerprinting over Encrypted Traffic," 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI), 2021, pp. 274-281, doi: 10.1109/IRI51335.2021.00044.
Link: IEEE digital library
Detecting Plant Phenotypes From 3D Point Cloud Data (Master's Thesis)
2019
J. Dani, "Detecting Plant Phenotypes from 3D Point Cloud Data." Order No. 22589583, Texas A&M University - Corpus Christi, Ann Arbor, 2019.
Link: ProQuest
Education
Doctor of Philosophy in Computer Science (Transferred-In)
January 2022 - Present
Texas A&M University, College Station, TX, USA
Doctor of Philosophy in Computer Science (Transferred-Out)
August 2019 - December 2021
University of Cincinnati, Cincinnati, OH, USA
Master of Science in Computer Science
August 2017 - August 2019
Texas A&M University - Corpus Christi, Corpus Christi, TX, USA
Thesis title: Detecting Plant Phenotypes From 3D Point Cloud Data
Bachelor of Technology in Information Technology
July 2013 - April 2017
Charotar University of Science & Technology, Gujarat, India
Internships
Apollo Tyres Limited, India
Software Engineering Intern (January - May 2017)
Role: Developed a Java-based web service for providing rating methodology for new Tyres and confirming the efficiency of Tyres.
Hewlett-Packard, India
Embedded Systems & Robotics Intern (June - July 2015)
Role: Developed a Gesture Controlled Car that could be controlled using simple hand gesture based on tilt movements of the hand.
Appointments
Graduate Research Assistant
January 2022 - Present
Texas A&M University, College Station, TX, USA
Graduate Assistant
December 2020 - December 2021
University of Cincinnati, Cincinnati, OH, USA
Graduate Research Assistant
January 2020 - December 2020
University of Cincinnati, Cincinnati, OH, USA
Graduate Research Assistant
December 2017 - August 2019
Texas A&M University - Corpus Christi
Graduate Assistant
August 2017 - December 2017
Texas A&M University - Corpus Christi