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Wai Cheong Tam (Fed)
Mechanical Engineer
Dr. Andy Tam is a Mechanical Engineer in the Fire Fighting Technology Group of the Fire Research Division of the Engineering Laboratory at the National Institute of Standards and Technology (NIST). As the Leader of the AI-Enabled Smart Fire Fighting project, he and his team use AI and ML to develop data-driven solutions that enable real-time forecasting and provide actionable information to enhance safety and situational awareness.
Andy is an advisor/sponsor in the Research Associateship Programs of the U.S. National Research Council, and he actively recruits postdocs interested in artificial intelligence, fire hazard forecasting, physiological monitoring, building optimized recommendation systems, and/or early detection and mitigation of Li-ion battery thermal runaway. Research opportunities are also available through the SURF program for undergraduate students and the GMSE program for graduate students. The Foreign Guest Research Program (FGRP) offers opportunities for international students.
Before his tenure, Andy was an NRC Postdoctoral Research Associate at NIST after receiving his Ph.D. in Mechanical Engineering from the Hong Kong Polytechnic University, where he developed the neural network-based radiation solver (RADNNET-ZM) for heat transfer analysis in fire research with his thesis advisor, Professor Walter W. Yuen. His research interests are thermal radiation heat transfer, machine learning for interdisciplinary research studies on smart firefighting and firefighters’ health monitoring, and early thermal runaway detection technology for lithium-ion batteries.
Recently Funded Proposals
Augmented Intelligence in Semiconductor Manufacturing (Gregory Vogl, Peter Denno, Wai Cheong Tam, Christopher Lemieux, Van Sy Mai) ($4.9M) (FY25 - FY27)
Development of a Robust Sensing System to Detect Early Thermal Runaways in Lithium-ion Batteries
(Wai Cheong Tam, Anthony Putorti Jr., Qi Tong) ($150K) (FY25)
Supporting the Fire Service: Research Needs for Emerging Electrification Fire Risks (Hongqiang Fang, Juan Fung, Michelle Donnelly, Stanley Gilbert, David Butry, Wai Cheong Tam) ($114K) (FY25)
A Motion-Cancelling Physiological Monitoring Device for Safe Fire Fighting
(Wai Cheong Tam, Christopher Brown, Jun Wang) ($112.5K) (FY22)
True local temperature measurement for fire exposed surfaces using fiber optic sensor array (Chao Zhang, Tobias Herman, Wai Cheong Tam, Thomas Cleary) ($120K) (FY21)
A Neural Network Approach to Smart Firefighting for Residential Buildings in Realistic Fires (Wai Cheong Tam, Tom Cleary) ($150K) (FY20)
Committee roles
Scientific advisory committees (2024 – Present): Intl. Symposium on Lithium Battery Fire Safety
Program committee in AI (2024 – Present): 2025 AI in Fire Engineering Summit
Member-at-Large for Engineering Laboratory (2024 – Present): NIST AI Community of Interest
External advisory panel member (2024 – Present): SFPE Foundation Grand Challenges Initiative
Recent news
A Warning For When A Lithium-Ion Battery Is About To Explode
December 06, 2024
Interview with Mr. Ira Flatow from Science Friday.
AI Can ‘Hear’ When a Lithium Battery Is About to Catch Fire
November 14, 2024
About a minute before a battery is about to explode, built-up gases escape and make a small noise. Using machine learning, the NIST team developed a program that can identify that sound with 94% accuracy.
AI Can Accurately Predict Potentially Fatal Cardiac Events in Firefighters
July 11, 2023
There’s a lesser-known danger to the firefighters who brave smoke and flames: stress on their hearts. But an AI-based tool developed at NIST could help predict life-threatening cardiac events.
AI May Come to the Rescue of Future Firefighters
AUGUST 10, 2022
Flashover is one of the leading causes of firefighter deaths, but new research suggests that artificial intelligence (AI) could provide first responders with a much-needed heads-up.
NIST researchers have a breakthrough that could save the lives of firefighters
JULY 8, 2021
Interview with Mr. Tom Temin from Federal News Network
How AI Could Alert Firefighters of Imminent Danger
JUNE 1, 2021
Firefighting is a race against time. Exactly how much time? For firefighters, that part is often unclear. Building fires can turn from bad to deadly in an instant, and the warning signs are frequently difficult to discern amid the mayhem of an inferno.
Recent scholars and students in my team
- Mr. Md. Ismail Siddiqi Emon, Machine Learning Associate at NIST, 2024 – Present
- Dr. Hongqiang Fong, Research Scientist at NIST, 2023 – Present
- Dr. Qi Tong, Research Scientist at NIST, 2023 – 2024 (Currently a Fire Protection Engineer at Fire and Risk Alliance, USA)
- Mr. Linhao Fan, M.S. student at Zhengzhou University, CN, 2022 – Present (Currently a Ph.D. student at University of Science and Technology of China)
- Mr. Denglin Kang, M.S. student at the University of Southern California, USA, 2022 - Present
- Dr. Jiajia Li, Research Scientist at NIST, 2022 – 2023 (Currently a UX Researcher at Google Inc., USA)
- Mr. Michael Ngai, a volunteer student from Phillips Exeter Academy, 2021 - 2022
- Ms. Christina You, SURF student in Summer 2020 at NIST (Currently an ML engineer at META, USA)
- Dr. Jun Wang, PostDoc at NIST from 2019 - 2020 (Currently a Data scientist at Xiaomi, CN)
Awards
- Jack Watts Award by Fire Technology Journal, Springer (2025)
- People's Choice Poster Award - Preliminary Steps Towards A Wearable Device For Real-time Cardiac Monitoring Among Active Firefighters To Prevent Sudden Cardiac Events (2025)
- Best Oral Presentation Award - Development of a Robust Early-Stage Thermal Runaway Detection Model for Lithium-ion Batteries by Asia-Oceania Symposium on Fire Science and Technology Conference (2024)
- Ronald K. Mengel Award - Development of an Explainable Machine Learning Based Flashover Prediction Model by NFPA Suppression, Detection and Signaling Research and Applications Conference (2023)
- Sheldon Tieszen Award - An Explainable Machine Learning Based Flashover Prediction Model Using Dimension-Wise Class Activation Map by the 14th International Symposium on Fire Safety Science (2023)
- Honorable Mention - Alice Hamilton Award for Occupational Safety and Health by National Institute for Occupational Safety and Health (2021)
- Best Paper Award - Assessment of Radiation Solver of Fire Simulation Models Using RADNNET-ZM in the 11th Asia-Oceania Symposium on Fire Science and Technology (2019)