Md Abu Sayed

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Md Abu Sayed

Ph.D. Candidate | Gen AI | Naval Security | Simulation | Robotic Vision

About Me

Welcome to the personal website of Md Abu Sayed, a passionate Ph.D. student in Computer Science and Engineering at the University of Nevada, Reno (UNR). His research focuses on the cutting-edge domain of Robotic Vision, with a particular emphasis on activity and intent recognition in a group of agents operating in Naval Space. This innovative work is a collaborative effort between the Robotics Research Lab and Computer Vision Lab at UNR.

Before embarking on his Ph.D. journey, Sayed was a Lecturer in the Department of Computer Science and Engineering at The Millennium University, Bangladesh. He earned his Bachelor’s degree in Computer Science and Engineering from Khulna University, Bangladesh, in January 2019. His undergraduate thesis explored an automated method to segment retinal blood vessels from color fundus photographs, showcasing his early dedication to impactful research.

Beyond academia, Sayed is deeply committed to community engagement has been steadfast throughout his academic journey. As Vice President of the International Students Club at UNR, he organized significant events like the Night of All Nations, showcasing the diversity of 32 countries. As Treasurer of the Bangladeshi Student Association, he managed funds and organized cultural events. Noteably, as a Council Member of the Graduate Student Association, he represented the College of Engineering and contribute to committees, ensuring the needs and interests of graduate students are met.

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Interests

Generative AI
Intent Recognition
Simulation and AI
Robotic Vision
Medical Image Analysis
Temporal Data Analysis

Education

Ph.D. in Computer Science & Engineering
University of Nevada, Reno
M.Sc. in Computer Science & Engineering
University of Nevada, Reno
B.Sc. in Computer Science & Engineering
Khulna University, Bangladesh

📚 My Research

My research focuses on intelligent systems that perceive, predict, and adapt in dynamic environments, with applications spanning maritime security, simulation and medical imaging. I began my work in medical image analysis, developing machine learning, deep learning and graph-based methods for retinal vessel segmentation and breast cancer detection. These projects sparked my interest in computer vision and AI for supporting critical, human-centered decision-making. As a Ph.D. student at the University of Nevada, Reno, I currently focus on maritime intent recognition and threat prediction, developing frameworks that can be deployed to ships and algorithms that combine HMMs, LSTMs, and transformers to model vessel behavior in uncertain and adversarial environments. My work has led to multiple publications in top IEEE conferences and journals and international presentations.

Looking ahead, I aim to bridge my expertise in medical imaging, computer vision, and simulation-driven AI to create trustworthy, interpretable, and adaptable intelligent systems. I am particularly interested in exploring cross-domain AI, where methods developed for one field can be applied to others, including healthcare, maritime security, and beyond. My broader goal is to develop AI systems that not only achieve high performance but also enhance human decision-making, awareness, and trust, combining scientific innovation with real-world impact.

Please reach out to collaborate 😃

Featured Publications