Sandhya Patidar

Sandhya Patidar is an Associate Professor at the School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University. She holds editorial roles in journals like Geosciences and Frontiers in Environmental Engineering, and is a member of the Royal Academy of Engineering. Her research focuses on interdisciplinary applications of data science (mathematical/statistical/machine learning) to energy, water, climate change, and environmental impact assessment. She has led projects funded by grants like EP/F038240/1 and EP/K013513/1, and developed novel methodologies in stochastic processes, complex networks, and bifurcation analysis.

Education & Early Career: Previously affiliated with Shri RGP Gujarati Professional Institute (2001–2004), DAVV Indore, and RGPV Bhopal. Holds expertise in programming (Python, R, MATLAB) and has over 70 peer-reviewed publications. Three outputs won best paper awards, including recognition at climate change and low-energy architecture conferences.

Research Interests: Machine learning applications in energy systems, flood risk modeling, and climate change adaptation. Specializes in techniques like Hidden Markov Modeling, time series analysis, and deep learning frameworks for energy demand forecasting and hydrological prediction.

Key Contributions: Developed a physics-aware machine learning framework for hydrological models, error correction models for reservoir levels, and AI-driven heat pump usage classification. Pioneered methodologies linking climatic trends to energy demand via stochastic modeling and covariance approaches.

Awards:

• Robert Alfred Carr Prize (2022)
• Sir David Wallace Prize (2008)
• Best Paper Awards (2011, 2019)

Advising & Grants: Supervises interdisciplinary PhD projects on data analytics in climate-energy-water nexus. Collaborates on initiatives like the CEDRI project for community energy demand reduction in India. Actively engages in grant-funded research on flood inundation modeling and probabilistic climate projections.

Labs & Teams: Part of the Institute for Infrastructure & Environment, leading cross-disciplinary teams in energy performance assessments, resilience planning, and environmental risk management.