Assistant Research Scientist
Center for Cyber-security Innovation (CCI) Lab,
College of Business Administration,
Texas A&M University - Central Texas
Email: mohammad.nadim@tamuct.edu
I am an Assistant Research Scientist at Texas A&M University - Central Texas. I earned my Ph.D. and M.Sc. in Electrical Engineering from The University of Texas at San Antonio (UTSA) and B.Sc. in Electrical and Electronics Engineering from Bangladesh University of Engineering and Technology (BUET). Additionally, I have been a program committee member for the ACM SaT-CPS and have reviewed for IEEE conferences. Find my latest CV here.
My primary research interests include Artificial Intelligence, Cyber Security, Adversarial Learning, Virtual Reality and Human-Computer Interaction. I am particularly interested in applying artificial intelligence in cyber domain to address different challenges in computer security and develop trustworthy-explainable security solutions. At Texas A&M University - Central Texas, I work for Center for Cybersecurity Innovation (CCI) Lab, where we undertake multidisciplinary research in cyber security, trustworthy-explainable security solutions, and virtual and augmented reality. My research has been published at prestigious top-tier journal and conferences such as the IEEE Access, IEEE Virtual Reality (VRW), Ad Hoc Networks, ICEET, and CSCloud/EdgeCom. My Google scholar profile here: Mohammad Nadim
Paper published: A literature review on sinkhole attack detection for Internet of Things at Ad Hoc Networks Journal.
Paper published: A Case Study of 3rd Party Hardware: The Weakest Link in Google’s Trustworthy Artificial Intelligence Implementation at IEEE Access Journal.
Paper published: Buenas: Giving Everyone a Seat at the Study Group Table at 2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW).
Paper published: A Comparative Assessment of Unsupervised Keyword Extraction Tools at IEEE Access Journal.
Paper published: San Antonio Research Partnership Portal: Evaluating keyword extraction tools to automate matchmaking for community research partnership at Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2023.
Paper published: A Review on Learning-based Detection Approaches of the Kernel-level Rootkit at 7th International Conference on Engineering and Emerging Technologies (ICEET), 2021.
Paper published: Characteristic Features of the Kernel level Rootkit for Learning based Detection Model Training at Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2021.
Paper published: Kernel-Level Rootkits Features to Train Learning Models Against Namespace Attacks on Containers at 7th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud), 2020.