Md Abu Sayed

About Me

I am a Postdoctoral Research Scholar at the Center for Digital Cardiovascular Innovations, University of Miami Miller School of Medicine, working with Dr. Yiannis S. Chatzizisis. My research focuses on cardiovascular AI and multimodal clinical decision support systems, combining intracoronary imaging (HD-IVUS, OCT, and angiography) with biomechanical modeling for coronary interventions.

I received my Ph.D. in Computer Science and Engineering from the University of Nevada, Reno (May 2026). My doctoral work focused on autonomous multi-agent systems, developing the NavySim simulation engine (IEEE Transactions on Games), explainable feature attribution methods (CPFI/TFIS), and deep generative models (MTITP) for joint intent recognition and trajectory prediction.

Earlier, I served as a Lecturer in Computer Science and Engineering at The Millennium University, Bangladesh. I also actively contribute as a peer reviewer for journals and conferences including BMC Digital Health, PLOS ONE, Information Systems, and the IEEE Conference on Games.

NavySim 2.0 accepted for IEEE Transactions on Games

Our enhanced multi-vessel simulation engine has been accepted for publication in IEEE ToG.

Jun 24, 2026

Joining the University of Miami as a Postdoctoral Research Scholar

Starting a postdoc at the Center for Digital Cardiovascular Innovations, applying AI and computational modeling to cardiovascular care.

Jun 8, 2026

Feature-Aware Deep Learning for Maritime Intent Recognition

Presenting our feature-aware deep learning models for maritime intent recognition, achieving ~97% accuracy on seven maritime behaviors using only initial trajectory segments.

Nov 2, 2025

Presented two papers at IEEE CASE 2025

Presented work on early intent classification and proactive maritime threat prediction at the IEEE Conference on Automation Science and Engineering.

Aug 25, 2025

Early Intent Recognition for Maritime Domains

Two papers accepted and presented by coauthors on deep learning for maritime intent recognition—early classification of vessel intentions and proactive threat prediction using LSTMs and transformers with a sliding-window approach.

Aug 17, 2025

Feature-aware deep learning paper forthcoming at IEEE FMLDS 2025

Paper on feature-aware maritime intent recognition accepted for the IEEE International Conference on Future Machine Learning and Data Science.

Jan 15, 2025

ThreatMap presented at HMS 2024

Presented our maritime situational awareness framework at the International Conference on Harbor, Maritime and Multimodal Logistic Modeling & Simulation.

Sep 24, 2024

ThreatMap: Enhancing Security Awareness for Naval Agents

Presented ThreatMap, a framework that fuses sensor coverage, vulnerability fields, and CPA-based threat estimates for interpretable real-time maritime risk visualization.

Sep 18, 2024

NavySim presented at IEEE Conference on Games 2024

Presented our multi-vessel naval simulator at IEEE CoG in Yokohama, Japan.

Aug 28, 2024

NavySim: A Multi-Vessel Simulation Engine for Naval Domains

Presented NavySim, our Unity-based multi-vessel naval simulator with real-time threat heatmaps and HMM-based intent recognition for maritime training and research.

Aug 5, 2024