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PhD Candidate in Computational Analysis & Modeling
Sabbir Alom Shuvo
Graduate Research Assistant & PhD Candidate
Computational Analysis & Modeling
Institution For Micromanufacturing (IFM)
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Objective
To advance interdisciplinary research in artificial intelligence, scientific machine learning, and computational modeling, with emphasis on advanced manufacturing, digital twins, environmental monitoring, and data-driven engineering for reliable, sustainable, and intelligent systems.
Research Interest and Interests
Additive Manufacturing and Process Modeling
Digital Twin Development
Machine Learning and Predictive Analytics
Reinforcement Learning for Network Control
Environmental Monitoring and Computer Vision
Intelligent Systems for Industrial Applications
Analysis
Advanced computational analysis of complex engineering systems through statistical learning, scientific machine learning, probabilistic modeling, and high-dimensional data interpretation.
Physics-Inspired & Scientific Machine Learning
Multivariate, Sensitivity & Uncertainty Analysis
Probabilistic & Generative Data Modeling
Inverse Problems, Parameter Estimation & Design Optimization
ProcessโStructureโProperty Relationship Analysis
Multimodal Numerical & Image-Based Data Fusion
About Me
Sabbir Alom Shuvo is a Ph.D. Candidate in Computational Analysis and Modeling at Louisiana Tech University. He currently works in the Additive Manufacturing, Materials, and Mechanics (AMยณ) Laboratory, with expertise in machine learning, data analysis, additive manufacturing, computer networks, and robotics. His research interests focus on applying advanced machine learning and computational modeling techniques to optimize manufacturing processes, develop intelligent network systems, and design data-driven solutions for complex engineering challenges.
Contact
Get in touch for collaboration opportunities.