6 minute read
New Fellows’ spotlight
Professor Sara Bernardini Professor of Artificial Intelligence at the Department of Computer Science; Tutorial Fellow in Computer Science at Mansfield
Before coming to Mansfield to take up the inaugural position of Tutorial Fellow in Computer Science, I previously held positions at Royal Holloway, King’s College, and University College London in the UK, as well as stints at MIT and NASA Ames in the US. I’ve also recently served as the Principal Research Scientist in AI and Data Science at the UK National Oceanography Centre and as a Senior Fellow at the Alan Turing Institute.
My research is in AI, specifically decision-making for intelligent autonomous systems such as ground robots, drones and underwater vehicles. I specialise in automated planning, which involves equipping artificial agents with the ability to synthesise plans to reach specific goals. My long-term objective is to provide the theoretical foundations for creating agents that can seamlessly support humans in undertaking sophisticated and temporally extended tasks, which, going beyond perception and pattern matching, require deliberation at the cognitive level.
At the heart of my research is the desire to combine theoretical and technical advancements in AI with the demands of the real world. Over the past few years, I’ve led several projects on intelligent autonomous systems for extreme environments, working closely with industry and stakeholders to ensure solutions address end-users’ practical problems. I’ve worked in several domains, such as space mission operations, nuclear decommissioning, mining, underwater missions, and offshore energy, leading several projects funded by Innovate UK, the Engineering & Physical Sciences Research Council (EPSRC), the Natural Environment Research Council (NERC), the Turing Institute, and the Leverhulme Trust.
Complementing my technical work, I’ve taken up several leadership roles in the AI scientific community. I was the Programme Chair of ICAPS 2024, the flagship International Conference on Automated Planning and Scheduling, and the Associate General Chair of AAAI-23 (run by the Association for the Advancement of Artificial Intelligence), where I started a new initiative, the Bridge Programme, to facilitate cross-fertilisation between AI and other disciplines. I led this initiative again at AAAI-24 and will do so at AAAI-25. I also act as Managing Guest Editor of the Artificial Intelligence Special Issue on ‘Risk-Aware Autonomous Systems’, and am a member of the AAAI Executive Council, where I lead the Partnership Committee, and the ICAPS Executive Council.
Dr Lyndsey Jenkins Associate Professor and Tutorial Fellow in History at Mansfield
I’m a historian of women and politics in Britain in the 19th and 20th centuries. My research to date has mostly focused on the women’s suffrage movement – especially the contribution of working-class women. More recently, I’ve been concentrating on the women who were elected to represent the Labour Party in Parliament between 1945 and 1979.
Usually, historians have seen this as a period in which women in the Labour Party did not necessarily pursue women’s interests, especially in comparison with the earlier and later decades of the 20th century. However, I’ve found that Labour women continued to champion many causes of interest to women, such as family planning, nationality rights, divorce reform and women’s pensions. They often worked hand in hand on these issues with progressive Conservative women, sharing a common understanding of the causes of and solutions to sex inequality. I’ve discovered too that Labour women were much more receptive to the rise of the women’s liberation movement than has been recognised. Labour women made common cause with activists interested in equal pay, abortion rights, and childcare provision – but were also open to new concerns being raised about sexual and domestic violence.
Presently, I’m considering how we might rethink women’s politics in the 1960s and 1970s to understand better how women who were committed to different kinds of politics – in established women’s lobby groups, emerging radical politics, and conventional party politics – could work collaboratively. I’m using the life and work of Joyce Butler as a case study here. She was MP for Wood Green between 1955 and 1959, and, among many campaigns, she was the driving force behind efforts to eradicate sex discrimination at work. In partnership with Haringey Archives and Museums Service, which holds many of her papers, I’m developing an exhibition which will mark the 50th anniversary of the Sex Discrimination Act in 2025 as well as Joyce Butler’s long career in Parliament and local government.
Dr Thomas Rainforth Associate Professor at the Department of Statistics; Tutorial Fellow in Statistics at Mansfield
My research covers a wide range of topics in and around machine learning and experimental design, with particular interest in Bayesian experimental design, deep learning, representation learning, generative models, Monte Carlo methods, active learning, and approximate inference.
I currently hold a European Research Council Starting Grant entitled ‘Data-Driven Algorithms for Data Acquisition’ (February 2024 to February 2029, funded by the UK Research and Innovation Horizon Guarantee Scheme), which funds my research and that of the Rainforth Machine Learning (RainML) group which I lead (https://rainml.uk/). The focus of the project is to develop new approaches to gathering data intelligently by combining techniques from machine learning, statistics, and information theory. In particular, it focuses on constructing adaptive data acquisition techniques that control the data-gathering process in a manner that maximises the information content of the collected data. By improving the underlying approaches to gathering data, it is hoped that the project will ultimately lead to better data being available across a wide range of scientific fields and industries, in turn allowing for improved models, AI systems, and data-driven decision making.
Following an undergraduate degree in Engineering at Cambridge and a brief stint in the Ferrari F1 team, I completed my DPhil in Probabilistic Programming and Machine Learning in 2017 at Wolfson College. I have stayed in Oxford since then, first taking up a postdoctoral position in the Department of Statistics, followed by a Junior Research Fellowship in Computer Science at Christ Church, and then a Senior Research Fellowship in Statistical Machine Learning back at the Department of Statistics.
