Secure Sensing and Learning (SSL) Research Lab
Our Group
Principal Investigator
Diksha is interested in designing secure and privacy preserving machine learning, computer vision, and natural language processing models. Her research spans applications of these models to wearable devices, biometrics, attack-averse authentication, and side channel attack formulation.
Postdoctoral Research Fellow
Dr. Judith Nkechinyere Njoku’s research focuses on machine learning, artificial intelligence, computer vision, and digital twin technologies. Her work spans autonomous vehicle perception, smart infrastructure monitoring, battery management systems, and AI-enabled solutions for resilient rural and industrial applications.
PhD Candidate, CS
Mohamad's research focuses on optimizing Multimodal Large Language Models (MLLMs) to enhance their reasoning capabilities. His work involves accelerating LLMs through advanced techniques such as pruning, ensuring performance is maintained or improved. He has hands-on experience with foundational models, having previously interned at Numenta Inc., and is currently developing innovative approaches like Mixture of Depth (MoD), Mixture of Experts (MoE) for resamplers, and attention pruning to push the boundaries of MLLM efficiency and scalability.
PhD Candidate, CS
Paul is interested in Machine Learning and its applications in Cybersecurity. He is exploring active authentication models for mixed reality systems.
PhD Candidate, CS
Soudabeh is actively delving into the realm of utilizing users' brain signals for identity verification and their applications in brain-controlled computer interfaces. In her ongoing endeavors, she is pioneering the development of innovative authentication systems that harness the distinctive neural responses of individuals. Her research seamlessly combines principles from neuroscience with advanced computational techniques, with the ultimate goal of establishing enhanced security and convenience in human-computer interactions.
PhD Student, CS
Michael’s research interest lies in applying machine learning (ML) to enhance cybersecurity, with a particular focus on side-channel attacks. He explores the development of ML models that can detect and mitigate these vulnerabilities, aiming to improve system security in both traditional and emerging environments, such as augmented reality (AR) and virtual reality (VR). His work seeks to advance the resilience of cyber-physical systems and immersive technologies against complex and evolving cybersecurity threats.
MS Student, CS
Selma's research focuses on the security and privacy of Virtual Reality (VR) and Augmented Reality (AR) systems. She explores potential side-channel information that could compromise user data or system integrity within these immersive technologies. Her work aims to design more secure authentication mechanisms to ensure safe user interactions in VR/AR environments. Through her research, Selma seeks to contribute to the advancement of secure and trustworthy immersive technologies.
MS Student, AI
Sudipa's research interests focus on EEG-based user authentication for AR/VR environments, with an emphasis on privacy-preserving biometric systems. Their work explores secure and continuous authentication methods using brain-signal patterns while addressing challenges related to sensitive neural data protection, user privacy, and trustworthy deployment in immersive technologies.
MS Student, AI
Bamidele’s research explores gait-based biometrics as a natural and unobtrusive way to recognize users through the way they walk. His work emphasizes practical authentication systems that remain reliable beyond controlled settings, studying how gait patterns change across days, sessions, devices, and real-world conditions. By combining longitudinal analysis with deployment-focused evaluation, his research aims to make gait biometrics more robust, usable, and trustworthy for everyday security applications.
Undergradaute Researcher
Zach research focuses on developing and testing methods for user authentication using EEG brainwave biometrics. His work involves working with an array of different algorithms, hardware, and response extraction protocols founded in neuroscience. The ultimate goal of his research is to make brainwave biometric authentication a viable alternative to other biometrics, like fingerprint and facial ID.
Undergradaute Researcher
Shruthika is an undergraduate researcher at the Secure Sensing and Learning Research Lab. She is particularly interested in the intersection of biology and technology, exploring how biological signals can be utilized for security and authentication. Her current research focuses on using EEG-measured brain signals to develop authentication mechanisms for VR/AR devices. She is currently an undergraduate student studying biomedical engineering at Purdue University.
Undergradaute Researcher
This position is open for undergraduate research opportunities. If you are interested in joining the Secure Sensing and Learning Research Lab, please reach out to Dr. Diksha Shukla for more information.
SSL Research Lab Alumni
PhD Researcher (Graduated - Spring 2025) → Now Assistant Professor at Boise State University
MS in CS Student (Graduated - Spring 2025) → Now Critical Infrastructure Cyber Analyst at Idaho National Laboratory
Undergraduate Researcher (Graduated - Spring 2024) → TBA
Undergraduate Researcher (Graduated - Spring 2022) → Now Software Engineering at Northrop Grumman
Ashlyn Lindsay
REU Student, Summer 2022, Undergraduate Student → Laramie County Community College
Austin Youngren
REU Student, Summer 2022, Undergraduate Student → Front Range Community College
Jacob Karen
REU Student, Summer 2021, Undergraduate Student → William & Mary
Christine Wang
REU Student, Summer 2021, Undergraduate Student → William & Mary
Julia Ding
Athena by WiSTEM Student (Talaria), Summer 2021