Waterloo Engineering's Critical Machine Learning (ML) Lab is developing AI systems that are safer, more efficient and more equitable — with active applications in health care, aviation and climate action.
Dr. Sirisha Rambhatla, a professor in the Department of Management Science and Engineering, leads the lab's research. Her team works at the level of ML theory to predict and engineer it — so users can make safer, fairer decisions at lower computing costs and with less waste.
The lab's industry collaborations give its research immediate real-world relevance.
“Whether its predicting flight delays or aiding organ transplant assessments, the AI acts as a support that enables humans to make faster, better decisions in critical situations,” she says.
Climate impact is a core consideration throughout. A recent algorithm from the lab reduced large language model training time by 43 per cent while maintaining accuracy — a finding with significant implications for energy use and AI accessibility. "If we can do it faster, we can use far less energy in the process," said Rambhatla.
Graduate students, undergraduate researchers and co-op students are embedded in the lab's work alongside industry partners. Chang Liu, who recently completed a master's degree and received Waterloo's 2025 Alumni Gold Medal, worked on improving self-driving systems for winter weather conditions. "I know my contributions could help prevent accidents and save lives," Liu said.
Go to Working with industry to build trustworthy AI for real-world impact for the full story.