ISAS provides undergraduate and graduate students with opportunities to participate in interdisciplinary research involving artificial intelligence, data analytics, statistics, computational modeling, and physical AI.
Ways to Participate
- Faculty-mentored research projects
- Independent study and capstone projects
- Graduate and undergraduate research opportunity
- Workshops, seminars, and research presentations
Current Opportunities
Available research positions and project opportunities will be posted on this page. Opportunities may be paid, credit-bearing, or voluntary, depending on the project and available funding.
Express Your Interest
Students interested in participating should provide their academic program, research interests, relevant skills, and expected availability. Contact the faculty who you are interested in working with.
Past Student project
Project Title: Hybrid Scientific Machine Learning for Smart Building Thermal Modeling
Student: Graduate students Mit Pandya and Prince Chandra Singh developed a hybrid framework that combines physics-based thermal modeling, latent cloud-cover estimation, and Unscented Kalman Filtering to reconstruct unknown solar disturbances in smart buildings.
Faculty Mentor: Liang Kong
The project demonstrates the potential of Scientific Machine Learning to improve thermal-state estimation and support more energy-efficient building control. The research was published through CPESE 2026.