About

I am Sabbir Alom Shuvo, a computer scientist and researcher pursuing my Ph.D. in Computational Analysis and Modeling at Louisiana Tech University, USA. My academic and professional journey bridges machine learning, additive manufacturing, and intelligent systems, where I strive to integrate physics-informed modeling with modern data-driven intelligence. Currently, I work as a Graduate Research Assistant in the Additive Manufacturing, Mechanics, and Materials (AM³) Laboratory at the Institute for Micromanufacturing (IfM), focusing on ultrasonic vibration–assisted additive friction stir deposition and digital-twin modeling for laser powder bed fusion. My research explores how artificial intelligence can deepen understanding of manufacturing phenomena and enable real-time process optimization.

Alongside my engineering work, I also serve as a Graduate Teaching Assistant in the Department of Chemistry, supporting undergraduate laboratory instruction in General Chemistry. I previously worked in the Statistics and Machine Learning Lab, where I contributed to projects involving predictive modeling, reinforcement learning, and statistical data analysis. My cross-disciplinary involvement reflects my belief that computational intelligence can bridge domains—from environmental sensing to advanced manufacturing—to improve both industry and society.

Before beginning my graduate studies in the United States, I earned my Bachelor of Science in Computer Science and Engineering from Daffodil International University, Bangladesh (CGPA 3.82 / 4.00), where I laid the groundwork for my interests in programming, automation, and robotics. My early projects included developing web platforms such as E-Shoppy, a full-stack e-commerce site, and Birth Registration System (BRSBD), a government-service prototype enabling digital birth registration and identity verification through Laravel and MySQL. I also built Hello Dr., a smart health prediction system, and Tingu-the-Avoider, an obstacle-avoiding robot, blending embedded systems and software logic to create intelligent, real-world tools. These formative experiences gave me hands-on exposure to problem-solving that now underpins my research in intelligent systems.

In 2022, I briefly trained as a Salesforce Development Trainee at Inovi Solutions, gaining experience in data management, process automation, debugging, and interface configuration. This industry training helped me appreciate the intersection between enterprise systems and research-grade data workflows.

My publication record spans both applied machine learning and engineering innovation. My most recent works include “Enhanced Smoke Detection Using Advanced Machine Learning Techniques: Integrating YOLO and KDE” (under review in IEEE Transactions on Image Processing), and “Web Technologies Security in the AI Era: A Survey of CDN-Enhanced Defenses” (accepted at the 2025 IEEE Asia-Pacific Conference on Wireless and Mobile). I have also co-authored journal papers on machine learning in business intelligence and biological data analysis, reflecting my interdisciplinary research outlook.

Beyond research, I actively contribute to the academic community as a reviewer for the IEEE Internet of Things Journal and for the ASME IMECE 2025 Conference. At Louisiana Tech, I have been entrusted with leadership responsibilities as General Secretary of the College of Engineering and Science Graduate Student Council and Treasurer of the Students’ Association of Bangladesh, roles through which I represent students, coordinate initiatives, and promote cultural and academic engagement.

Over time, my technical expertise has expanded across multiple areas: Python, PyTorch, TensorFlow, R, C, C#, Java, and PHP; web frameworks such as Laravel, VueJS, and Bootstrap; and data-science ecosystems involving scikit-learn, TorchRL, and Hugging Face. My skill set also spans robotics and embedded systems, statistical modeling, and network security tools like Wireshark and Burp Suite.

I have been honored with several academic scholarships, including the Entergy Corporation LP&L Endowed Scholarship and multiple Doctoral Tuition Scholarships from the Louisiana Tech College of Engineering and Science, in recognition of my academic excellence and research contributions.

My personal and professional philosophy is guided by curiosity, resilience, and a desire to merge science with societal progress. Whether I am modeling micro-scale heat transfer in metallic alloys, building AI-based smoke-detection pipelines for environmental safety, or developing reinforcement-learning frameworks for resilient networks, my goal remains constant: to create intelligent systems that make technology more adaptive, interpretable, and impactful.

Originally from Dhaka, Bangladesh, I now live in Ruston, Louisiana, where I continue my Ph.D. research surrounded by a vibrant scientific community. Beyond academia, I find fulfillment in mentoring younger students, collaborating across disciplines, and contributing to the growing dialogue between artificial intelligence, materials science, and sustainable engineering.