Rate My Professor Maomao Hu

Dr. Hu's research focuses on building decarbonization technologies for energy efficiency, flexibility, and climate resilience; grid-interactive smart buildings and communities; modeling, optimization, and model-based optimal control of building and urban energy systems; physics-based modeling and control of HVAC&R systems; data analytics and machine learning for buildings; uncertainty quantification for building energy systems; and occupant behavior in buildings. Her notable publications include 'Empirical exploration of zone-by-zone energy flexibility: a non-intrusive load disaggregation approach for commercial buildings' (Energy and Buildings, 2023), 'Impacts of building load dispersion level on its load forecasting accuracy: Data or algorithms? Importance of reliability and interpretability in machine learning' (Energy and Buildings, 2023), 'Classification and characterization of intra-day load curves of PV and non-PV households using interpretable feature extraction and feature-based clustering' (Sustainable Cities and Society, 2021), 'Neighborhood-level coordination and negotiation techniques for managing demand-side flexibility in residential microgrids' (Renewable and Sustainable Energy Reviews, 2021), and 'Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model' (Applied Energy, 2017). She received the Best Student Paper Award (1st place) at the 5th International High-Performance Buildings Conference at Purdue University in 2018. Dr. Hu currently serves as Deputy Program Director for the MSc in Building Performance and Sustainability and sits on the organizing committees for ASim 2026, Indoor Air 2026, and ACM BuildSys 2026.