About Syed Alam
Syed Alam
Prof, ast
Nuclear Eng &Radiation Science
222 Fulton Hall
Biography
Dr. Syed Alam (Syed Bahauddin Alam) is an Assistant Professor of Nuclear Engineering and Radiation Science at the Missouri University of Science and Technology. He is currently leading MARTIANS (Machine Learning and ARTIficial Intelligence for Advancing Nuclear Systems) Laboratory [Link: https://sbahauddin.tech/].
Dr. Syed Alam received Ph.D. in Nuclear Engineering from the University of Cambridge. He also completed his MPhil in Nuclear Energy from the University of Cambridge. He received his B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology (BUET). He worked in different parts of the world. He was a Postdoc Researcher at French Atomic Energy Commission (France). He worked as a MeV Fellow at Argonne National Laboratory (USA) and a Nonproliferation Fellow at the Korea Advanced Institute of Science and Technology (South Korea). He is also currently a Visiting Researcher at the Rhode Island Nuclear Science Center (USA).
The overarching Research Theme of Dr. Alam's MARTIANS Lab is "Hybrid Data+Physics-Driven & Explainable Machine Learning and Multiscale Modeling with Surrogate-Modeling-Based Uncertainty Quantification and Robust Optimization for Nuclear Engineering Problems." Dr. Alam's research interests and expertise broadly lie in the intersection of nuclear engineering, explainable machine learning, mechanics & materials - focusing on data-driven analysis that warrants frequent excursions among the boundaries of applied mathematics and data science.
Dr. Alam received several Awards and Honors for his research and teaching. He received the Outstanding Teaching Award by Missouri S&T in 2021. He was awarded the Most Exemplary Graduate Fellow Award on "Nuclear Nonproliferation Fellowship 2017" by the Korea Advanced Institute of Science & Tech (KAIST). He was also the winner of the ANS Best Student Paper Award in recognition of the "Exceptional Quality of the Paper" (ICAPP 2016), Nominated for the Young generation/Student Award for the Outstanding Paper (ICAPP 2017), and ANS Best Technical Poster Award (NURETH-16). For the continuation of an exceptionally promising piece of research beyond the usual standard of the PhD, he was also awarded the Cambridge Philosophical Society "Research Studentships Award" (2017) during his Ph.D. at Cambridge University.
Research
Expertise areas
Multiscale modeling, Artificial Intelligence, Machine learning, Digital Twin, Robotics for Nuclear Applications; Surrogate Modeling, Uncertainty Quantification, Robust Optimization
Current research projects
- Explainable, Intelligent, & Trustworthy Digital Twin-Enabling Framework for Nuclear Systems
- Digital Twin Framework Development for Risk-Informed Decision-Making
- Human-Robot Interaction with Digital Twin for Manufacturing Bending Operation
- Multi-Stage Deep Learning Framework Development with AI Assurance for Reactor Digital Twin
- Multi-Scale Modeling and Robust Optimization of Accident Tolerant Fuel with Uncertainty Quantification for Risk-Informed Decision-Making
Research interests
-Thrust 1: Multiscale & Multiphysics modeling of Nuclear Systems
-Thrust 2: Digital Twin & Explainable Artificial Intelligence (AI) for Nuclear Systems
-Thrust 3: System Decision-Making, Reliability & Uncertainty Quantification
-Thrust 4: Robotics for Nuclear Applications
Research grants
- Trustworthy Machine Learning (ML) and Artificial Intelligence (AI)-based Framework Development for Hybrid and Sustainable Energy Systems Kummer Ignition Grant 2022
- Kummer Innovation and Entrepreneurship Fellowship 2022 The fall 2022 Kummer Innovation and
Entrepreneurship Doctoral Fellows are innovative-
minded students to pursue doctoral degrees at S&T
to strengthen applied research, technological
innovation, and economic development. - Machine Learning & Artificial Intelligence-based Framework Development for Nuclear-Renewable Hybrid Energy Systems IAEA Coordinated Research Project: Technical
Evaluation and Optimization of Nuclear-
Renewable Hybrid Energy Systems (I32012)
Awards and recognition
Awards
- Outstanding Teaching Award 2021-2022
- Outstanding Teaching Award 2020-2021
- Kummer Ignition Grant 2022
- Best Student Paper Award in recognition of the "Exceptional Quality of the Paper" 2016 International Congress on Advances in Nuclear Power Plants
(ICAPP 2016) in CA, USA, 2016. - Nominated for the Young generation/Student award for the outstanding paper 2017 International Congress on Advances in Nuclear Power Plants
(ICAPP 2017) in Kyoto, Japan 2017 - Best Student Poster Award 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 16th International Topical Meeting on Nuclear Reactor Thermal
Hydraulics (NURETH-16) in Chicago, IL, USA, 2015 - Cambridge Philosophical Society "Research Studentships Award" 2017 for continuation of an exceptionally promising piece of research beyond
the usual standard of the PhD - U.S. Department of Energy (DOE) MeV Fellowship, 2018
- Department of Energy (DOE) MeV Fellowship, 2019
- Most Exemplary Graduate Fellow Award on "Nuclear Nonproliferation Fellowship 2017" Korea Advanced Institute of Science & Tech (KAIST), 2017
- The Charles Wallace Trust Doctoral Bursary, 2017
- Cambridge St. Edmund's College Tutorial Award, 2016
- W G Collins Endowment Fund, 2016
- Ford of Britain Trust, 2015
- Cambridge St. Edmund's College Tutorial Award 2015
- Rotary Vocational Excellence Award, 2011
- 1st Prize in Undergraduate Project Workshop (Computer Group), BUET, 2011
- IET Travel Award, 2016
- Cambridge Philosophical Society Travel Grant, 2017