Van-Dinh Nguyen

Dr. Dinh Nguyen is currently an Assistant Professor in Networks and Distributed Systems with the School of Computer Science and Statistics, Trinity College Dublin, Ireland. Prior to this position, he was an Assistant Professor at the College of Engineering and Computer Science, VinUniversity (2022-2025), a Research Associate with the Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg (2019-2022), a Postdoc Researcher and a Lecturer with Soongsil University (2018-2019), a Postdoctoral Visiting Scholar with the University of Technology Sydney, AUS (July-August 2018) and a Ph.D. Visiting Scholar with Queen"s University Belfast, U.K. (June-July 2015 and August 2016). Dr. Nguyen received the four best conference paper awards, IEEE Communications Letters Exemplary Editor Awards 2019 and 2021, IEEE Open Journal of the Communications Society Exemplary Editor Award 2021 and 2023, IEEE Transaction on Communications Exemplary Reviewer Award 2018 and IEEE GLOBECOM Student Travel Grant Award 2017. He has authored or co-authored some 90 papers published in international journals and conference proceedings. He has served as a reviewer for many top-tier international journals on wireless communications, and has also been a Technical Programme Committee Member for several flag-ship international conferences in the related fields. He is currently a Senior Editor of IEEE COMMUNICATIONS LETTERS, and was an Associate Editor of the IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY and IEEE SYSTEMS JOURNAL.

Investigating Gradient Interference and Negative Transfer in Multi-Task Deep Learning

Van-Dinh Nguyen (email | all projects)

Summary Multi-task learning (MTL) enables a single neural network to learn several related tasks simultaneously, such as image segmentation, attribute prediction, and object classification. Although MTL often improves efficiency and generalization, competing objectives from different tasks can produce conflicting gradients during training, resulting in negative transfer and degraded performance. Recent studies suggest that gradient interference … Read more

Continual Learning for Robust UAV Object Detection in Dynamic Environments

Van-Dinh Nguyen (email | all projects)

Summary: Autonomous UAVs are increasingly deployed in diverse environments such as urban areas, forests, construction sites, and agricultural fields. However, object detection models are typically trained offline using fixed datasets and often experience significant performance degradation when operating in unseen environments. Retraining the model from scratch whenever new data becomes available is computationally expensive and … Read more

Scalable AI Approach for Wi-Fi-Based Human Pose Estimation Using Compressed CSI Data

Van-Dinh Nguyen (email | all projects)

As the need for privacy-aware sensing grows, Wi-Fi-based human pose estimation is emerging as a viable alternative to vision-based systems. However, transmitting and processing large volumes of channel state information (CSI) poses a significant challenge, particularly for edge devices with limited resources. This project proposes a scalable AI-driven framework that compresses CSI data using vector … Read more