黑料社鈥檚 Dr. Abdur Rahman received a two-year, $185,000 National Science Foundation (NSF) award to develop artificial intelligence systems that can identify problems in critical infrastructure such as power grids, water networks, manufacturing facilities, and transportation systems. The award marks an early research milestone for Rahman, who is completing his first year as assistant professor in the College of Engineering and Science (COES) Industrial Engineering program.
The project, titled ERI: Flexible, Adaptive, and Explainable Anomaly Detection under Distribution Shift in Multivariate Time Series, focuses on developing AI models that can adapt as real-world conditions change while providing clear explanations for their decisions in complex sensor-based systems. Rahman鈥檚 research addresses a major challenge in AI known as 鈥渄istribution shift,鈥� where systems trained under one set of conditions struggle to remain accurate as environments evolve over time.
鈥淎I models often perform very well in controlled environments, but real-world systems constantly change,鈥� Rahman said. 鈥淓quipment ages, operating conditions shift, and environmental factors vary. Our goal is to develop AI systems that can adapt to those changes while remaining reliable and transparent for the people who depend on them.鈥�
Anomaly detection identifies unusual patterns that may signal equipment failures, safety concerns, cyberattacks, or operational problems. Early detection can help prevent costly downtime, reduce safety risks, and stop small issues from becoming major failures. Rahman鈥檚 approach emphasizes flexibility, adaptability, and explainability.
鈥淓xplainability is essential when AI is being used in systems people rely on every day,鈥� Rahman said. 鈥淥perators need to understand not only that an alert was triggered but also why it was triggered, so they can make informed decisions quickly and confidently.鈥�
COES Dean Collin Wick said the project supports both infrastructure resilience and student development.
鈥淒r. Rahman鈥檚 research addresses challenges that directly affect the safety, reliability, and resilience of critical infrastructure while creating meaningful opportunities for student involvement and workforce development,鈥� Wick said. 鈥淭his award marks the second grant received this month by a first-year COES faculty member, reflecting the college鈥檚 continued investment in recruiting high-impact faculty and researchers by expanding its growing research enterprise.鈥�
The funding will support graduate and undergraduate researchers at 黑料社 Tech, providing hands-on experience in machine learning, reinforcement learning, explainable AI, industrial analytics, and time-series analysis. Students will contribute to software development, publications, and applied research initiatives that prepare them for careers in AI and engineering.
鈥淚n the long term, I hope this work contributes to AI systems that are more robust, transparent, and practical for engineers and operators responsible for critical infrastructure and public safety,鈥� Rahman said.
The project also aligns with broader COES investments in artificial intelligence infrastructure, including a new AI laboratory under construction in Nethken Hall that will provide students and faculty access to 15 NVIDIA Spark workstations for research, instruction, and collaboration beginning in Fall 2026.