Maitreyee Dey

Dr. Maitreyee Dey serves as a Visiting Fellow in Mechanical Engineering and Design and works as a Post-doctoral research fellow at London South Bank University's Department of Electrical and Electronics Engineering. She concurrently holds the position of Data Mining Lead at Neuville Grid Data Management Limited, where she contributes to significant energy research projects.

Her research expertise spans machine learning/artificial intelligence and low carbon technologies, with additional interests in pattern recognition, big data analysis, deep learning, image processing, energy optimization in smart buildings, renewable energy technology, and Computer-aided Diagnosis for smart health applications. Her work directly contributes to UN Sustainable Development Goals related to clean energy and sustainable communities.

Analysis of her recent publications reveals a strong research trajectory focusing on two primary domains: power grid analysis using machine learning techniques and microwave-based medical imaging for breast cancer detection. Her work demonstrates sophisticated applications of neural networks and data mining methods to solve complex problems in both energy systems and medical diagnostics.

• Best Paper Award at the CUE conference, Elsevier (2020)
• Endorsement by the Royal Academy of Engineering

Dr. Dey serves as an Editorial board member for MDPI journals and as an Adhoc reviewer for high-impact publications including IEEE transactions and Nature Scientific Data. She is actively involved in the Access to Innovation (A2i) and Low Carbon London (LCLDN) projects funded by the EU commission through its regional development Fund, working in collaboration between London South Bank University and Neuville Grid Data Management Limited.

Her professional affiliations include active membership in IEEE, CIGRE NGN, and the Energy Institute, demonstrating her engagement with key professional organizations in her fields of expertise.