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Research Interests
Research Interests
Bridging the gap between...
Seeking novelty and feasibility
Emphasizing creativity, scalability, and productivity
Making this field of engineering attractive
We continuously engage in fundamental research in applied mathematics and physics, not only to deepen theoretical understanding but also to enable long-term innovation through simple and practical solutions in simulation, data analysis, and real-world applications.
Research Topics
Research Topics
Leveraging AI, physics-based modeling, real-time simulation, and measurement analysis to improve the energy efficiency of renewable energy systems and enhance occupant comfort through intelligent HVAC operations in buildings, cities, and other built environments.
"Towards Sustainable Buildings and Society through Smart Technologies in Engineering and Computer Science"
Keywords: AIx for HVAC, Multi-modal Sensing, Renewable Energy
HVAC simulation and plus
Understanding of system principles and behavior through simulations
Renewable energy, energy conversion, and storage: Ground-source HP, BIPVT, VRF, Hybrid systems
Computer-aided HVAC systems engineering: TRNSYS, EnergyPlus, Dymola
Urban energy simulation, data, and audit
✍️ Physics and system principles
Digital twinning
Industrial AIx: HVAC and renewable energy systems
RC network modeling for model predictive control
RL-based optimal control and system diagnostic methods
Smart energy audits: Data and simulation, Learning based M&V
🖥️ AI and IT skills
InfraRed thermography
U-value field test, thermal bridge and condensation evaluation
Moisture and airflow coupled thermography analysis
Model order reduction for digital twins
Active and passive approach for diagnostic applications
📹 NDT instrumentation
More research topics
Advanced Controls
MARL – Multi-agent Reinforcement Learning
Extremum-Seeking Control at UCSD
Multi-modal sensing and MultiPhysics
Modeling of heat, air, moisture (HAM), and pressure-driven multiphysics phenomena in buildings
Multi-modal sensing and multiphysics simulations (e.g., Dymola) for edge-based control and diagnostics
Applied Mathematics and Physics for Complex Systems
Data-driven feature extraction from dynamic systems using dimensionality reduction and sparse sensing
Application of robust theoretical frameworks to complex system behaviors, with an emphasis on model-free approaches
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