Computer Science

Anna Allen is in the final stages of a PhD in computer science at the University of Cambridge. Originally from Tasmania, she holds a Master’s in Meteorology from the University of Melbourne and a BSc in Pure Mathematics and Theoretical Physics from the University of Tasmania. Her research applies machine learning to environmental sciences, with a particular focus on developing data-driven forecasting systems for both global weather and high-impact phenomena such as tropical cyclones, tornadoes, and wildfires. During her PhD, she worked part-time with the United Nations Environment Programme to develop an operational system for detecting large greenhouse gas emissions to inform mitigation strategies. 

As a Junior Research Fellow at King’s, she will work on developing end-to-end foundation models for Earth system observation and forecasting, spanning weather, ocean, and air quality prediction. This will include designing bespoke regional forecasting systems for low-resource areas by integrating intelligent sensor placement with AI forecasting models, with pilot projects already underway in the Arctic and planned for West Africa.

Umang is an Assistant Professor at the Cambridge Institute for Technology and Humanity (ITH) and its Centre for Human-Inspired Artificial Intelligence (CHIA). His research focuses on building trustworthy artificial intelligence (AI) systems for high-stakes deployment. He develops algorithms and tools that support effective human-AI interaction and manage the partnership between people and AI systems. Drawing on machine learning, cognitive science, philosophy, and law, Umang studies when and how AI systems can be trusted, integrated into human decision-making, and evaluated in ecologically valid settings. His group uses lab and field experiments to assess societal impacts of AI in various domains, with particular attention to healthcare, education, and national security, where human oversight of AI is essential.
 

Born and raised in Basking Ridge, New Jersey (USA), Umang earned his BS and MS at Carnegie Mellon University and his PhD in the Machine Learning Group at Cambridge. He was previously an Assistant Professor and Faculty Fellow at New York University’s Center for Data Science and a Senior Research Associate at The Alan Turing Institute. His work has been supported by the Responsible AI Institute, the Mozilla Foundation, and the Partnership on AI.
 

Tim's research interests include network protocol design and analysis and mathematical models of Internet routing. He also serves on the Turing Programme committee at King's.

Research: Machine Learning and Artificial Intelligence, Mobile Systems, Robotics and Automation, Systems and Networking

I am Professor of Emergent Harms in the Security Group at the Computer Laboratory, University of Cambridge, and Fellow of King’s College. I am also Director of the Cambridge Cybercrime Centre, an interdisciplinary initiative combining expertise from computer science, criminology, and law. Specialising in cybercrime, I bridge the gap between criminology and computer science. Generally, my research interests include understanding cybercrime offenders, cybercrime events, and the prevention and disruption of online crime. 

Research: Dr Moody's research focuses on distributed database systems, information retrieval, active applications and access control (including RBAC for wide-area), applications with federated management domains, also trust-based, access control systems). Object-based database systems, ODMG with SQL3, GDPR, provenance, Internet of Things, lightweight data tracking, M4IoT. His current interests are notably in GDPR and Provenance.  

Research

Developing new logical and structural techniques to transform the way we compute in future, including in quantum and classical computation, category theory.