Syed Bahauddin Alam (NOT "Syed Alam"): h-index, Total Citations, and Citation Map
Syed Bahauddin Alam (NOT "Syed Alam")'s h-index is 24 (54 i10-index, 1,934+ total citations across 233+ publications) according to Google Scholar as of June 2026. Syed Bahauddin Alam (NOT "Syed Alam") is affiliated with Assistant Professor, University of Illinois Urbana-Champaign.
Syed Bahauddin Alam (NOT "Syed Alam") is a researcher affiliated with Assistant Professor, University of Illinois Urbana-Champaign, specializing in AI4Sci, AI for Energy, Digital Twins. Their work has been cited 1,934 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Syed Bahauddin Alam (NOT "Syed Alam")'s Citation Metrics
Bibliometric impact based on 233 indexed publications.
- H-Index
- 24
- i10-Index
- 54
- Total Citations
- 1,934
- Citing Countries
- 53
As of June 2026.
Syed Bahauddin Alam (NOT "Syed Alam") has an h-index of 24 and 1,934 total citations across 233 publications, with research cited by institutions in 53 countries.
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Explainable, interpretable, and trustworthy AI for an intelligent digital twin: A case study on remaining useful life
2024193
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
814 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced signal processing and digital twin technologies by developing non-linear down-sampling methods and extending them to explainable, generalizable AI for engineering systems.
The researcher developed a deep neural operator-driven digital twin framework for real-time nuclear energy system inference, establishing a foundational approach for virtual sensing and hybrid power prediction.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Syed Bahauddin Alam (NOT "Syed Alam")'s research
Syed Bahauddin Alam (NOT "Syed Alam") is a researcher in AI4Sci, AI for Energy and Digital Twins at Assistant Professor, University of Illinois Urbana-Champaign. Their work has been cited 1,934 times across 233 publications (h-index 24), according to Google Scholar.
Their most-cited work, “Explainable, interpretable, and trustworthy AI for an intelligent digital twin: A case study on remaining useful life” (2024), has accumulated 193 citations. Other influential works include “Developing an AI-Powered Zero-Trust Cybersecurity Framework for Malware Prevention in Nuclear Power Plants” (2023) with 99 citations and “Small Modular Reactor Core Design for Civil Marine Propulsion Using Micro-Heterogeneous Duplex Fuel. Part I: Assembly-level Analysis” (2019) with 83 citations.
Citations of Syed Bahauddin Alam (NOT "Syed Alam")'s research come primarily from United States, India and China, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
