Using Open Data for Energy Efficiency
Course Leader – Healthcare Analytics & AI, Sheffield Hallam University
The talk will present a data architecture build on pillars of Natural Language Processing and Data Analytics to track most-deprived domestic and non-domestic buildings across Sheffield City Region. The analysis will benefit both Local Council and Energy providers in achieving greater energy efficiency crucial for tackling climate change.
Sehgal is a data science leader with years of experience in enabling digital transformation for UK Enterprises using big, small, and metadata. She is currently working as Senior Lecturer – Data Science and Course Leader – Healthcare Analytics and AI in the Department of Computing at Sheffield Hallam University (SHU).
Sehgal holds a Masters’ degree in Big Data Technology from Hong Kong University of Science & Technology, and has a Doctoral degree in Analytics. She holds second master’s degree in Statistics and an undergraduate degree in Mathematics from Delhi University. Prior to joining SHU, Sehgal has worked as Head of Data Science at Valuechain Ltd., UK. She was responsible for designing the AI strategy and roadmap for the Valuechain business.
Sehgal has successfully overseen the workflow of multiple data-driven funded projects by Innovate UK and EUREKA, with the aim to design and develop an intelligent collaborative ecosystem for supply chain mapping (manufacturer from food and health sector) and networking by integrating machine learning and NLP. Sehgal has worked on scads of big data projects related to Smart Cities, Education, Health and the Human Resource sector in association with the University of Huddersfield and Big Data Institute, HKUST.
She was awarded with “Best AI Model Presentation” from HKUST Fintech Forum, “Research Excellence Award” from OPJGU, and "Best Paper Award" from ICMI. She has presented her research work in various international conferences across London, Portugal, Beijing, Belfast, and Taiwan. Her research work has been published in Energy Systems (Springer), Energy Procedia (Elsevier), and Applied Soft Computing (Elsevier).
Cinema 4, Showroom Workstation
12 May 2022 @ 13:30
Free, donations welcomeBooking Link