Syed Bahauddin Alam

For More Information

• Illinois Experts profile
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Education

• Bangladesh University of Engineering and Technology (BUET), B.Sc. in Electrical and Electronics Engineering, 2011
• University of Cambridge, MPhil in Nuclear Energy, 2013
• University of Cambridge, PhD in Nuclear Engineering, 2018

Biography

Dr. Syed Bahauddin Alam (Syed Alam) is an Assistant Professor of Nuclear, Plasma & Radiological Engineering department at the University of Illinois Urbana-Champaign. 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 has also been selected/invited as one of ~100 Selected Leaders by the Simons Foundation (with Princeton University and New York University) to explore the transformative potential of AI, particularly foundation models in accelerating scientific research. He has also been featured in the Illinois Grainger "Top of Mind" in 2024 and 2025. For his seminar contribution in AI and Digital Twins for Nuclear Power Systems, Dr. Alam received the 2025 Dean's Award for Excellence in Research, assistant professor level, from the Grainger College of Engineering, University of Illinois Urbana-Champaign. For his research on AI and digital twins, he was one of the top three finalists 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. Dr. Alam has been named as 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). 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, Tech Xplore, LeBigData (France), EYE Magazine, Innovant.fr (France), Interesting Engineering, Innovant.fr (France), Scienze Notizie (Italy), Enerzine.com (France) and so on and 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

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)

• S.B. Alam, et. al. AI for Secure Digital Ecosystems, In Prep., Publisher: Springer Nature, 2025.
• K. Kobayashi, S.B. Alam, et. al. Securing Industrial Control Systems: Advanced Strategies and Technologies, Publisher: Springer Nature, In press, 2025.

Chapters in Books

• 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.
• 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. “Data- Driven Multiscale Modeling and Robust Optimization of Composite Structure with Uncertainty Quantification”, “Springer Handbook of Smart Energy Systems”, Jan 2023.
• 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.
• 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.
• 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.
• 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, 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.
• 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.
• 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.

Selected Articles in Journals

• 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.
• 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.
• 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.
• 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.
• 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.
• 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. Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life", "Engineering Applications of Artificial Intelligence", Volume 129, March 2024.
• 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.
• 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, 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.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.
• 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.

Invited Lectures

• Policy Recommendations for Bangladesh Rooppur Nuclear Power Plant, Korea Advanced Institute of Science and Technology, Korea
• Feasibility of Fueling Future US Naval Reactors with Low Enriched Uranium (LEU), Princeton University (remotely), USA
• University of Illinois Urbana-Champaign, Nuclear, Plasma Demystifying Digital Twin (DT)-Enabling Technologies for Nuclear Systems: An International Collaborative Effort, University of Illinois Urbana-Champaign, USA
• Digital Twin for Online Monitoring Strategies, 2024, University of Michigan, USA
• Digital Twin for Complex Engineering Systems, Illinois Society of Professional Engineers, 2023, USA
• Uncertainty-Aware, Intelligent, & Trustworthy Digital Twin-Enabling Technologies for Complex Nuclear Systems, Argonne National Laboratory, 2023, USA
• The Components of Trustworthy & Explainable Digital Twin (DT)-Enabling Technologies for Nuclear Systems, University of Ontario Institute of Technology, 2023, Canada
• Explainable Digital Twin for Nuclear Systems, Purdue University, 2024, USA
• Explainable Digital Twin for Real-Time Monitoring for Nuclear Components, University of Wisconsin-Madison, 2024, USA
• Foundation Models for Science conference, Simons Foundation, 2025, USA
• Technical Evaluation and Optimization of Nuclear-Renewable Hybrid Energy Systems, International Atomic Energy Agency (IAEA), 2025, UK

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 ANS Annual Meeting
• 2023 Panel Chair for ANS 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)

Teaching Honors

• Outstanding Teaching Award in recognition of notable contributions to teaching and commitment to the students by Missouri S&T (2022)
• Outstanding Teaching Award in recognition of notable contributions to teaching and commitment to the students by Missouri S&T (2021)
• Learning Enhancement Across Disciplines (LEAD) Award in recognition of the "Exceptional Extra effort to Help Students Enhance their Success," Missouri S&T (2020-2022)

Research Honors

• Named as 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).
• Invited as one of ~100 leaders by the Simons Foundation to present on advancing scientific discovery through AI and foundation models. (2025)
• Illinois Innovation Award (Finalist) for the work “Digital Twin for Real-Time Monitoring of Nuclear Operations and Maintenance” (2024)
• Featured as Top of Mind: A legacy of innovation at Grainger Engineering for exciting discoveries at Illinois Grainger Engineering (2024)
• Expert National Committee Member of the National Academies of Sciences, Engineering, and Medicine (NASEM) on "AI Foundation Models for Scientific Discovery and Innovation." (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 (Awarded out of 30 Graduate Fellows from 16 countries) (2017)
• Most Exemplary Graduate Fellow Award on "Nuclear Nonproliferation Fellowship 2017" by Korea Advanced Institute of Science & Tech (KAIST) (2017)
• Cambridge Philosophical Society "Research Studentships Award" (For a Promising Piece of Doctoral research) (2017)
• Best Student Poster Award at the 2016 International Congress on Advances in Nuclear Power Plants (ICAPP 2016) in San Francisco, CA, USA (2016)
• Cambridge W G Collins Endowment Fund (2016)
• Best Student Paper Award in recognition of the "Exceptional Quality of the Paper" at the 2016 International Congress on Advances in Nuclear Power Plants (ICAPP 2016) in San Francisco, CA, USA (2016)
• Best Technical Poster Award by "American Nuclear Society" at the 16th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-16) in Chicago, IL, USA (2015)
• Outstanding Research Award in Undergraduate Project Workshop, BUET (2011)
• International Rotary Vocational Excellence Award (2011)

Recent Courses Taught

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