Syed Bahauddin Alam

For More Information

• Illinois Experts profile
• Google Scholar
• Illinois profile
• Personal Website

Education

• Bangladesh University of Engineering and Technology (BUET), B.Sc., Electrical and Electronics Engineering, 2011
• University of Cambridge, M.Phil., Nuclear Energy, 2013
• University of Cambridge, Ph.D., Nuclear Engineering, 2018

Biography

Dr. Syed Bahauddin Alam (Not "Syed Alam") is an Assistant Professor of the Nuclear, Plasma & Radiological Engineering department at the University of Illinois Urbana-Champaign (UIUC). 

• He has been appointed as one of 11 National Committee Members on Foundation Models for Scientific Discovery and Innovation: Opportunities Across the Department of Energy at the National Academies of Sciences, Engineering, and Medicine (NASEM).  
• He was named a National AI leader and expert in UIUC's official institutional response to the White House Request for Information on the U.S. National Artificial Intelligence (AI) Action Plan (2025). 
• He has been named to the American Nuclear Society's Nuclear News "40 Under 40" List (2025) that "shines a spotlight on the exceptional young professionals driving the nuclear sector forward as the nuclear community faces a dramatic generational shift."
• He received the 2025 HPCwire Editors' Choice Award in Energy (for the first time for Grainger UIUC), which recognizes the most significant breakthroughs and the best and brightest minds in supercomputing/HPC.
• He has also been selected/invited as one of ~100 Selected Leaders by the Simons Foundation (Flatiron Institute) to bring leaders and enablers of Foundation Models (FM) for Science together from across the globe. 
• For his contribution to AI and Digital Twins research for Nuclear Power Systems, Dr. Alam received the Dean's Award for Excellence in Research from the UIUC Grainger College of Engineering in 2025. 
• For his research on AI and digital twins, he was a finalist for the Illinois Innovation Award 2024 for excellence in cutting-edge innovation or translational research that addresses real-world problems and has the potential to make a significant impact. 
• He has also been featured in the Illinois Grainger "Top of Mind" in 2024 and 2025. 
• Dr. Alam has been featured in Bloomberg News, one of the world's most influential and widely respected sources for business, energy, and technology reporting, to provide expert commentary on "AI+Nuclear Energy" and "Nuclear-Powered Data Center." 
• His work has also been featured in Illinois Alumni Magazine, which serves as a repository of inspiring stories that capture the spirit of Illinois. 
• His Nature Portfolio-published research on AI-powered digital twins for nuclear systems attracted extensive national and international media coverage featured by over twenty global major news outlets, including American Association for the Advancement of Science (AAAS/Science Magazine/EurekAlert), Microsoft Network, Ground News, Nuclear Engineering International, Quantum Zeitgeist, LeBigData (France), EYE Magazine,  Interesting Engineering, Innovant.fr (France), Scienze Notizie (Italy), Enerzine.com (France) and so on. The research also ranked in the top 5% of all research outputs scored by Nature Altmetric globally.

Academic Positions

• 2023-Present, Assistant Professor, University of Illinois Urbana-Champaign, Nuclear, Plasma, and Radiological Engineering (100% FTE)
• 2023-Present, Assistant Professor, University of Illinois Urbana-Champaign, National Center for Supercomputing Applications (0% FTE)
• 2020-2023, Assistant Professor, Missouri University of Science and Technology, Nuclear Engineering and Radiation Science

Professional Highlights

• Recipient of the 2025 HPCwire Editors’ Choice Award in Energy, honor the most significant breakthroughs and the best and brightest minds in supercomputing worldwide; first award of its kind for Grainger Engineering at UIUC.
• Selected for the American Nuclear Society (ANS) Nuclear News “40 Under 40” List  (2025), recognizing exceptional young professionals driving innovation and leadership in the nuclear sector during a generational transition.
• Named a National AI Leader and Expert in the University of Illinois Urbana-Champaign official institutional response to the White House Request for Information on the U.S. National Artificial Intelligence (AI) Action Plan  (2025).
• Appointed as one of 11 National Committee Members, National Academies of Sciences, Engineering, and Medicine (NASEM), serving on the committee “Foundation Models for Scientific Discovery and Innovation: Opportunities Across the U.S. Department of Energy,” advising DOE on national strategy for foundation models in scientific research (2025).

Research Interests

• Multiscale Modeling with Uncertainty Quantification and Robust Optimization
• Cybersecurity for Real-Time Threat Monitoring of Advanced Reactors
• Sensors, Instrumentation and Control for Nuclear Systems
• Artificial Intelligence and Digital Twins for Nuclear Energy

Books Authored or Co-Authored (Original Editions)

• Mohammad Ashiqur Rahman, Syed Bahauddin Alam, Kishor Datta Gupta, Roy George, Sunzida Siddique, Kazuma Kobayashi. Securing Industrial Control Systems: Advanced Strategies and Technologies, Publisher: Springer Nature, In press, 2025.

Chapters in Books

• A. Khan, S. Omar, N. Mustahry, R. Verma, D. Kumar, S.B. Alam. “Digital Twin and Artificial Intelligence Incorporated With Surrogate Modeling for Hybrid and Sustainable Energy Systems”, “Handbook of Smart Energy Systems”, Nov 2022
• K. Kobayashi, M. Bonney, D. Kumar, K. Paaren, S.B. Alam. “Digital Twin for Multi-criteria Decision-Making Framework to Accelerate Fuel Qualification for Accident-Tolerant Fuel Concepts”, “Springer Handbook of Smart Energy Systems”, Nov 2022
• K. Kobayashi, M. Bonney, D. Kumar, K. Paaren, S.B. Alam. “Practical Applications of Gaussian Process with Uncertainty Quantification and Sensitivity Analysis for Digital Twin for Advanced Nuclear Fuel”, “Springer Handbook of Smart Energy Systems”, Nov 2022
• S. Hassan, A. Khan, R. Verma, D. Kumar, K. Kobayashi, S. Usman, S.B. Alam. “Machine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications”, "Handbook of Smart Energy Systems", October 2022
• K. Kobayashi, S. Usman, C. Castano, A. Alajo, D. Kumar, S.B. Alam. “Data- Driven Multiscale Modeling and Robust Optimization of Composite Structure with Uncertainty Quantification”, “Springer Handbook of Smart Energy Systems”, Jan 2023
• M. Rahman, A. Khan, R. Verma, D. Kumar, K. Kobayashi, S.B. Alam. “Leveraging Industry 4.0: Deep Learning, Surrogate Model, and Transfer Learning with Uncertainty Quantification Incorporated into Digital Twin for Nuclear System”, “Handbook of Smart Energy Systems”, Nov 2022
• J. Fox, J. Eagen, A. Alajo, S.B. Alam. “Using Artificial Intelligence for Nuclear Nonproliferation and Commercial Nuclear Applications”, in Book: “Handbook of Smart Energy Systems”, Nov 2022
• D. Kumar, F. Ahmed, S. Usman, A. Alajo, S.B. Alam. “Recent Advances in Uncertainty Quantification Methods for Industrial Applications.” “AI Assurance: Towards Valid, Explainable, Fair, and Ethical AI”, Elsevier, 2022
• K. Kobayashi, D. Kumar, K. Paaren, S. Usman, S.B. Alam. “Uncertainty Quantification and Sensitivity analysis for Digital Twin Enabling Technology: Application for BISON Fuel Performance Code”, “Handbook of Smart Energy Systems”, Jan 2023
• R. Verma, K. Kobayashi, D. Kumar, S.B. Alam. “Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification”, “ Handbook of Smart Energy Systems”, Jan 2023
• K. Kobayashi, S. Usman, C. Castano, A. Alajo, D. Kumar, S.B. Alam. “Surrogate Modeling-Driven Physics-Informed Multi-fidelity Kriging: Path forward to Digital Twin Enabling Simulation for Accident Tolerant Fuels”, “Springer Handbook of Smart Energy Systems”, March 2023

Selected Articles in Journals

• B. Almutairi, S.B. Alam, C. S. Goodwin, S. Usman and T. Akyurek. "Experimental Evaluation of the Deadtime Phenomenon for GM Detector: Deadtime Dependence on Operating Voltages." Nature Scientific Reports, Volume 10, November 2020
• B. Almutairi, S.B. Alam, C. S. Goodwin and S. Usman. "Simultaneous experimental evaluation of pulse shape and deadtime phenomenon of GM detector.", Nature Scientific Reports, Volume 11, February 2021
• D. Kumar, M. Marchi, S.B. Alam; C. Kavka; Y. Koutsawa; G. Rauchs; S. Belouettar. "Multi-Criteria Decision Making Under Uncertainties in Composite Materials Selection and Design." Composite Structures, September 2021
• B. Almutairi, S. Jaradat, D. Kumar, C. S. Goodwin, S. Usman, A. Alajo, S.B. Alam. Weight Loss and Burst Testing Investigations of Sintered Silicon Carbide Under Oxidizing Environments for Next Generation Accident Tolerant Fuels for SMR Applications, Materials Today Communications, Vol 30, March 2022
• D. Kumar, S.B. Alam (joint first author with D. Kumar), T. Ridwan, C. Goodwin. "Quantitative Risk Assessment of A High Power Density Small Modular Reactor (SMR) Core Using Uncertainty And Sensitivity Analyses", Energy, Vol 227, 2022
• K. Kobayashi, S.B. Alam. Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life", "Engineering Applications of Artificial Intelligence", Volume 129, March 2024
• K. Kobayashi, J. Daniell, S.B. Alam. "Improved generalization with deep neural operators for engineering systems: Path towards digital twin.", "Engineering Applications of Artificial Intelligence", Volume 131, May 2024
• K. Kobayashi, S.B. Alam. Deep neural operator-driven real-time inference to enable digital twin solutions for nuclear energy systems.", "Nature Scientific Reports", Volume 14, 2024
• R. Hossain, K. Kobayashi, S.B. Alam. "Sensor Degradation in Nuclear Reactor Pressure Vessels: The Overlooked Factor in Remaining Useful Life Prediction," Nature npj Materials Degradation, 2024
• J. Daniell, K. Kobayashi, S.B. Alam. "Digital Twin-Centered Hybrid Data-Driven Multi-Stage Deep Learning Framework for Enhanced Nuclear Reactor Power Prediction," Energy and AI, 2024
• K. Kobayashi, D. Kumar, S.B. Alam. "AI-driven non-intrusive uncertainty quantification of advanced nuclear fuels for digital twin-enabling technology," Progress in Nuclear Energy, Volume 172, July 2024
• R. Hossain, K. Kobayashi, S.B. Alam. "Virtual Sensing-Enabled Digital Twin Framework for Real-Time Monitoring of Nuclear Systems Leveraging Deep Neural Operators," Nature npj Materials Degradation, 2025

Articles in Conference Proceedings

• K. Kobayashi, S.B. Alam. "Virtual Sensing and Model Adaptation for Real-Time Monitoring in Nuclear Systems", Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies, USA, June 2025
• K. Kobayashi, S.B. Alam. "Recurrent Neural Operator for Time-Series Nuclear System Monitoring", Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies, USA, June 2025
• K. Kobayashi, C. Godbole, V. Agarwal, V. Yadav, S.B. Alam. "Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components", Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies, USA, June 2025
• M. Alam, S. Talukder, S. Roy, K. Kobayashi, S.B. Alam. "Quantum-Safe Authentication Scheme for Advanced Reactor Devices using Homomorphic Encryption", Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies, USA, June 2025
• M. Alam, S. Talukder, S. Roy, K. Kobayashi, S.B. Alam. "Leveraging Large Language Models for Security Assessment in the Network of Devices in Nuclear Power Plants", Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies, USA, June 2025
• M. Alam, S. Talukder, S. Roy, K. Kobayashi, S.B. Alam. "A Privacy-Aware Cyber Attack Detection Framework for Advanced Reactors Using Data Fusion and Quantum Deep Learning", Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies, USA, June 2025
• S. Puppala, S. Talukder, S. Roy, K. Kobayashi, S.B. Alam. "Secure Anomaly Detection in Advanced Reactor through Quantum Federated Learning with Advanced Cryptography", Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies, USA, June 2025
• J.C. Tonday Rodriguez, D. Perry, M.A. Rahman, S.B. Alam. “An Intelligent Hierarchical Framework for Efficient Fault Detection and Diagnosis in Nuclear Power Plants,” Proceedings of the Sixth Workshop on CPS & IoT Security and Privacy, 2024, pp. 80–92.

Invited Lectures

• Policy Recommendations for Bangladesh Rooppur Nuclear Power Plant
• Feasibility of Fueling Future US Naval Reactors with Low Enriched Uranium (LEU)
• University of Illinois Urbana-Champaign, Nuclear, Plasma Demystifying Digital Twin (DT)-Enabling Technologies for Nuclear Systems: An International Collaborative Effort
• Digital Twin for Online Monitoring Strategies
• Explainable Digital Twin for Nuclear Systems
• Explainable Digital Twin for Real-Time Monitoring for Nuclear Components
• Foundation Models for Science Conference
• Technical Evaluation and Optimization of Nuclear-Renewable Hybrid Energy Systems

Journal Editorships

• Guest Editor of the journal Sustainability for the Special Issue of Sustainable Ecological Utilization in Marine Environment
• Review Editor of Frontiers in Energy Research
• Guest Editor of the Journal of Nuclear Engineering for the Special Issue of Intelligent, Explainable, and Trustworthy AI for Advanced Nuclear Systems
• Editor of the Journal Computers for the Special Issue of Uncertainty Aware Artificial Intelligence
• Guest Advisor of the journal Nuclear Science and Engineering on "Scientific Machine Learning for Nuclear Engineering Problems"
• Associate Editor of a Special Section of the journal IEEE Access on "Digital Twins for Energy-related Applications"
• Editorial Board member, Scientific Reports (Nature Portfolio)

Conferences Organized or Chaired

• 2025 Instrumentation & Controls Technical Co-Chair at 2025 Nuclear Plant Instrumentation and Control & Human-Machine Interface Technology (NPIC&HMIT)
• 2023 Session Chair for 18th International Probabilistic Safety Assessment and Analysis (PSA 2023)
• 2023 Panel Chair for American Nuclear Society Annual Meeting
• 2023 Panel Chair for American Nuclear Society Winter Meeting
• 2021 Program Committee Member of International Congress on Advances in Nuclear Power Plants (ICAPP 2021)
• 2017 Session Chair for International Congress on Advances in Nuclear Power Plants (ICAPP 2017)

Service to Federal and State Government

• National Academies of Science, Reviewer Panel, 2025
• Independent Academic Panelist, U.S. Department of Energy (DOE) Office of Nuclear Energy Consolidated Innovative Nuclear Research, 2024 (Machine learning, digital twins, structural health monitoring, and sensor development)
• U.S. Department Of Energy (DOE) Small Business Innovation Research Proposal, 2023
• U.S. Department of Defense (DoD) Science, Mathematics, and Research for Transformation (SMART) Scholarship, 2023
• U.S. Department of Energy (DOE) Office of Nuclear Energy Consolidated Innovative Nuclear Research (Machine Learning and Artificial Intelligence), 2023
• U.S. Nuclear Regulatory Commission (NRC) Research and Development Grant, 2023 (Machine Learning and Artificial Intelligence track)
• U.S. Department Of Energy (DOE) Small Business Innovation Research Proposal, 2024 Maryland Industrial Partnerships Program, 2023
• U.S. Department of Defense (DoD) Science, Mathematics, and Research for Transformation (SMART) Scholarship, 2022
• U.S. Nuclear Regulatory Commission (NRC) Research and Development Grant 2022 (Machine Learning and Artificial Intelligence track), 2022

Teaching Honors

• Outstanding Teaching Award (awarded for continued excellence in teaching and student engagement), Missouri University of Science and Technology (2022)
• Nominated for Faculty Achievement Award (recognition for extraordinary commitment and sustained excellence in teaching and research), Missouri S&T Nuclear Engineering Department  (2021)
• Outstanding Teaching Award (awarded for notable contributions to teaching and strong commitment to student learning), Missouri University of Science and Technology (2021)
• Learning Enhancement Across Disciplines (LEAD) Award (recognizes exceptional extra effort to enhance student success across disciplines), Missouri University of Science and Technology (2020-2022)

Research Honors

• American Nuclear Society (ANS) Nuclear News “40 Under 40” (national honor recognizing exceptional young professionals driving innovation and leadership in the nuclear sector during a generational transition) (2025)
• HPCwire Editors’ Choice Award (Energy) — honors the most significant breakthroughs and the best and brightest minds in AI/supercomputing worldwide (sole global award in its category, marking the first recognition of The Grainger College of Engineering (UIUC) in HPCwire’s Energy distinction) (2025)
• Featured in Illinois Alumni Magazine (institutional recognition of research leadership and national impact) (2025)
• Named a National AI Leader and Expert in UIUC’s official institutional response to the White House Request for Information on the U.S. National Artificial Intelligence (AI) Action Plan (2025)(selected to represent institutional expertise shaping national AI policy). (2025)
• One of 100 Selected Global Leaders, Simons Foundation (Flatiron Institute)(invited to shape the future of AI and foundation models for scientific discovery worldwide) (2025)
• Illinois Innovation Award (Finalist) for “Digital Twin for Real-Time Monitoring of Nuclear Operations and Maintenance” (recognizes high-impact translational research with commercialization potential) (2024)
• Expert National Committee Member of the National Academies of Sciences, Engineering, and Medicine (NASEM) on “Foundation Models for Scientific Discovery and Innovation,” advising the U.S. Department of Energy on national strategy for foundation models in scientific discovery. (2025)
• 2025 Dean's Award for Excellence in Research (recognizes outstanding research among the UIUC College of Engineering faculties) (2025)
• Nuclear Nonproliferation Education & Research Center (NEREC) Scholarship (selected from ~30 fellows across 16 countries) countries) (2017)
• Most Exemplary Graduate Fellow Award, Nuclear Nonproliferation Fellowship, KAIST (highest distinction among fellowship recipients)  (2017)
• Cambridge Philosophical Society Research Studentships Award (awarded for a promising and high-impact doctoral research program) (2017)
• Best Student Poster Award, ICAPP 2016, San Francisco, CA (recognizes excellence in research communication and technical innovation) (2016)
• Cambridge W. G. Collins Endowment Fund Award (supports outstanding graduate research at the University of Cambridge) (2016)
• American Nuclear Society Student Travel Scholarship (competitive international award supporting dissemination of high-quality nuclear research) (2016)
• Cambridge St. Edmund’s College Tutorial Award (repeat recognition for sustained academic excellence) (2016)
• Best Student Paper Award, International Congress on Advances in Nuclear Power Plants (ICAPP 2016), San Francisco, CA (awarded for exceptional quality and originality of research contribution) (2016)
• Cambridge St. Edmund’s College Tutorial Award (recognizes excellence in scholarship and academic contribution at Cambridge) (2015)
• Cambridge Ford of Britain Trust Award (competitive fellowship supporting high-achieving scholars at the University of Cambridge)  (2015)
• Best Technical Poster Award, American Nuclear Society (ANS), 16th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-16), Chicago, IL (recognizes outstanding technical contribution in nuclear thermal-hydraulics research)  (2015)
• Outstanding Research Award, Undergraduate Project Workshop, Bangladesh University of Engineering and Technology (BUET) (top research distinction among graduating undergraduate projects)  (2011)
• International Rotary Vocational Excellence Award (recognizes exceptional professional and societal impact at an early career stage) (2011)

Public Service Honors

• Recognized Subject Matter Expert, Energy Tech (featured for expert perspectives on the intersection of AI, energy infrastructure, and national energy strategy).  (2025)
• Recognized Subject Matter Expert, Bloomberg (featured for expert commentary on AI-driven electricity demand, power infrastructure stress, and energy systems resilience). (2025)

Recent Courses Taught

• NPRE 200 - Mathematics for NPRE
• NPRE 247 - Modeling Nuclear Energy System