Ruth Blackwell

Ruth Blackwell is a Post Doctoral Research Assistant in the Department of Electrical Engineering at Royal Holloway, University of London, working on the EPSRC-funded Petras PrivIoT project focused on privacy risks in IoT-enabled smart homes. Previously, she served as a Teaching Fellow in the Computer Science department where she taught courses, managed teaching assistants, and supervised undergraduate projects.

Her educational background includes:

• MSc in Data Science and Analytics (Distinction) from Royal Holloway, University of London (2019)
• PhD in Chemical Engineering/Computational Chemistry from Imperial College London (2009)
• MA in Natural Science - Chemistry from St. Hilda's College, Oxford University

Dr. Blackwell's research bridges data science, machine learning, and human-centered technology design with emphasis on privacy and security challenges in Internet of Things applications. Her interdisciplinary work spans computational chemistry simulations, epidemiological studies of bovine tuberculosis, and current investigations into user trust and risk perception among older adults adopting smart home technologies. She combines technical expertise in Kinetic Monte Carlo methods with practical data analysis experience from civil service and industry roles.

Her recent publication in the Journal of Risk Research examines privacy concerns and adoption barriers for IoT consumer products among elderly populations, revealing critical insights about trust formation and security expectations in domestic technology environments. This work exemplifies her focus on human factors in privacy-sensitive technological systems.

During her Teaching Fellow role, Dr. Blackwell supervised undergraduate projects on Advanced Web Development, Machine Learning Algorithms, and Human-Computer Interaction. She has secured significant research funding through EPSRC grants for both her doctoral work on chemical reaction simulations and her current IoT privacy research, demonstrating consistent success in competitive funding environments.

As a core member of the Petras PrivIoT project team, she collaborates across engineering and social science disciplines to develop privacy-preserving frameworks for demand-side management systems in smart homes, contributing to sustainable technology solutions aligned with UN development goals.