Computing Science Faculty

Dr. Anthony Aighobahi is an Assistant Teaching Professor in the Computer Science Department at TRU, who takes pleasure in teaching a diverse range of courses in Computer Science. He also enjoys researching and specializes in communication networks, cybersecurity, and the Internet of Things. His recent projects include exploring innovative approaches to enhance connectivity and optimize network performance, as well as developing advanced techniques to secure data transmission on the Internet of Things. He has numerous publications in renowned journals and speaks at conferences and workshops.

Dr. Ajay Dhruv is an Assistant Teaching Professor in Computing Science at TRU, bringing over a decade of rich experience from both academia and corporate sectors. He holds international recognition, including the prestigious Bayer Scholarship, and his expertise spans statistical machine learning, deep learning, hyperparameter tuning, generative AI, fine-tuning large language models, recommender systems, and computer vision. Dr. Dhruv's impactful contributions extend beyond research to encompass authorship, corporate training, editorial roles, and mentorship.

Grounded in cross-disciplinary collaboration and community engagement, Dr. Jackson's research has spanned several fields including criminology, political science, gerontology, and public health. Originally working on computational simulations based on domain expert knowledge, he has shifted to applications of artificial intelligence and machine learning to social issues and gaming.

Vijal Jain is an Assistant Teaching Professor in Computing Science at TRU, with over a decade of experience. Her research focuses on cybersecurity, ethical hacking, remote sensing, computer vision, and machine learning. With a robust publication record, Vijal's work has earned esteemed awards, underscoring her commitment to excellence in academia.

Dr. Jaspreet Kaur is an Assistant Teaching Professor in the Department of Computing Science at Thompson Rivers University. Her research interests focus on disaster management through the utilization of Wireless Sensor Networks and the integration of the Internet of Things to develop innovative solutions that enhance early warning, response, and recovery in disaster situations. Apart from her research, she has expertise in teaching various Computer Science courses and is dedicated to empowering students in their academic journeys.

Ghazanfar Latif is an experienced professional with 12+ years in higher education, covering teaching, research, innovation, curriculum development and academic administration. Since 2017, he has published 110+ research articles, holds an h-index of 28 with 2,510 citations and secured 13 U.S. patents in AI, Assistive Technologies, Medical Imaging, Computer Vision, LLMs, IoT, Robotics and Deep Learning. He became an IEEE Senior Member in 2025. He serves as Editor of Inspire Intelligence Journal and remains co-editor for multiple special issues in Diagnostics (IF 3.0, Q1) and Algorithms (IF 2.3, Q2) Journals. He is also an editorial board member of Discover Artificial Intelligence (Springer Nature). He has chaired AHTBE 2025 and co-organized three IEEE international conferences (2020, 2022 and 2024).

My research interests include, but are not limited to implement Artificial Intelligence (AI), Quantum Machine Learning (QML), Blockchain technologies, and Quantum-Safe protocols to develop efficient and secure Electric vehicle (EV) systems and Peer-to-peer (P2P) marketplace. I am also interested in exploring how these emerging technologies can advance precision agriculture. I aim to bridge theory with real-world practice to inspire students to understand how advanced computational and intelligent systems can shape cybersecure and industries, strengthen communities, and impact everyday life.

Quan Nguyen is an Assistant Professor of Computer Science at Thompson Rivers University. His research explores the impact of generative AI on the learning experiences in computer science education. Before joining TRU, he was a Postdoctoral Teaching Fellow at UBC's Master of Data Science, where he developed and taught courses on statistical inference, machine learning, and technical communication. Previously, Quan was a Research Fellow in Learning Analytics at the University of Michigan, his research has earned competitive grants and best paper awards at conferences such as LAK18 and HCI International 17. He holds a PhD in Learning Analytics from The Open University, UK.

Dr. Nisha Puthiyedth, is an Assistant Professor at the Department of Computing Science at TRU. Her research specializes in developing computational methods for analyzing biological data, particularly focusing on feature selection methodologies. Teaching is a significant aspect of her career, and she is dedicated to imparting knowledge across various Computer Science courses. She earned her M.Sc. degree from the University of East London, UK, and her Ph.D. degree from the University of Newcastle, Australia.

Dr. Musfiq Rahman is an Associate Professor in the Department of Computing Science at Thompson Rivers University. His research interests are mainly in the areas of security and resource management in emerging wireless networks. Teaching is one of Musfiq's primary passions, and he enjoys teaching a variety of courses in Computer Science.

Dr. Mridula Sharma is a Computer Science professor with more than 25 years of teaching experience. She has been teaching in the TRU Computing Science department for the last 10 years and has been teaching online at Open Learning for seven years. She now works as a senior Open Learning Faculty Member, as well.

Dr. Yan Song is an Assistant Professor in the Department of Computing Science at Thompson Rivers University. Her research focuses on applying machine learning techniques to multimedia data, particularly in content analysis and understanding of images and videos. Before joining the Department, she worked as a postdoctoral fellow in the Faculty of Sciences. She earned her PhD from the University of Chinese Academy of Sciences and worked as an Associate Professor at Nanjing University of Science and Technology. In 2024, she completed her MSc in Data Science at TRU. Dr. Song has publications in top-tier journals and conferences like IEEE Trans. on CSVT, IEEE Trans. on NNLS, and ICME. For the full publication, please refer to: https://scholar.google.com/citations?hl=en&user=OIfvArQAAAAJ&view_op=list_works&sortby=pubdate

Dr. Sukhchandan is an Assistant Teaching Professor in the Department of Computing Science at TRU. She brings extensive industry and academic experience, with a focus on data analytics, machine learning, cloud computing and Internet of Things (IoT) applications. Her work emphasizes bridging the gap between theoretical knowledge and real-world implementation through applied research and experiential learning. Her work focuses on integrating intelligent technologies into practical solutions for data-driven decision-making and smart environments.