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kazi0001/README.md

Dr. Kazi Monzure Khoda is an Assistant Professor in the Department of Chemistry and Chemical Engineering at Florida Institute of Technology. His research lies at the intersection of process systems engineering, machine learning, agentic AI, and blockchain, with a focus on building sustainable, autonomous, and cyber-resilient engineering systems.

Before joining Florida Tech, Dr. Khoda served as an Assistant Professor in the Karen M. Swindler Department of Chemical and Biological Engineering at South Dakota Mines, where he led the Process Optimization, Design Integration, and Informatics (PRODIGI) research group. He also held prior positions as an Assistant Research Scientist at the Texas A&M Energy Institute and as a Postdoctoral Fellow at Qatar University.

He has co-authored more than 35 peer-reviewed journal articles and has presented his work at numerous international conferences. In addition to his academic work, Dr. Khoda is a certified blockchain developer through IBM and HarvardX. He is passionate about harnessing artificial intelligence and machine learning to advance Industry 4.0 applications and next-generation chemical engineering systems.

GitHub: https://github.com/kazi0001

RESEARCH INTERESTS

Foundations (Process Systems Engineering, Machine Learning, Agentic AI, Blockchain) # Sustainable process design, integration, optimization, and control # Hybrid mechanistic/data-driven modeling and digital twins # Agentic AI and large language models for autonomous decision-making in engineering systems # Blockchain-secured cyber-physical systems with data privacy, security, and resilience against cyber-attacks # Game-theoretic frameworks for fair and trusted decentralized supply chains

Applications (Energy and the Environment, Supply Chain Management, Materials & Process Design, Process Safety) # Autonomous flowsheet optimization for sustainable and multi-objective process design # Sustainable hydrogen infrastructure for equitable low-carbon development # Carbon capture, utilization, and storage (CCUS) in clean energy transitions # Smart additive manufacturing and advanced material-process co-design # AI- and LLM-enabled process safety, anomaly detection, and autonomous control in industrial systems

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  1. GreenH2_maritime_industry_decarbonization GreenH2_maritime_industry_decarbonization Public

    Practicality of Green H2 Economy for Industry and Maritime Sector Decarbonization through Multi-objective Optimization and RNN-LSTM Model Analysis

    Python 1

  2. Optimum_design_composite_targetted_crashworthiness Optimum_design_composite_targetted_crashworthiness Public

    Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques

    Python 3

  3. Smart_manufacturing_composite_materials Smart_manufacturing_composite_materials Public

    Data-driven modeling to predict the load vs. displacement curves of targeted composite materials for industry 4.0 and smart manufacturing

    Python 3

  4. GreenH2_cost_analysis_industrial_decarbonization GreenH2_cost_analysis_industrial_decarbonization Public

    Green hydrogen for industrial sector decarbonization: Costs and impacts on hydrogen economy in Qatar

    GAMS 1

  5. Predictive_ANN_varying_filler_content Predictive_ANN_varying_filler_content Public

    Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves

    Python 3

  6. Safer_flare_management_iSDT Safer_flare_management_iSDT Public

    Application of i-SDT for safer flare management operation

    MATLAB