David is the Director of UCL's Centre for Artifical Intelligence. David has broad research interests related to the application of probabilistic modelling and reasoning
Marc is a Deputy Director of UCL's Centre for Artifical Intelligence. Marc's research interests include data-efficient machine learning, probabilistic modeling, reinforcement learning and Gaussian processes
Pontus is a Deputy Director of UCL's Centre for Artifical Intelligence. He leads UCL’s Natural Language Processing group (https://nlp.cs.ucl.ac.uk/) and his research interests lie primarily in the intersection between human language and machine learning, with applications such as machine reading comprehension and information extraction..
Peter's research interests include evolutionary computation, agent-based modelling, spiking neural systems, and other bio-inspired systems applied to diverse applications including design, music, and teamwork.
Carlo's research focuses on foundational aspects of machine learning within the framework of statistical learning theory. He is particularly interested in understanding how the notion of “structure” (being it in the form of prior knowledge or structural constraints) can be used to make machine learning algorithms learn faster and better. He investigates these questions within the settings of structured prediction, multi-task, and meta-learning, with applications to computer vision and humanoid robotics.
Ingemar's research is in the application of Artificial Intelligence, machine learning, and statistical natural language processing to large data sets of digital footprints, e.g. Web query logs and Twitter, to infer information about the health of both individuals and populations. At a population level, we have estimated prevalence and virulence of a disease, and effectiveness of national public health interventions (vaccines and changes to law). Our software and algorithms for estimating the prevalence of influenza have been adopted by Public Health England as part of its influenza surveillance programme.
Suran’s current research and start-up interests include AI-driven drug discovery, haptics for ‘automated skill acquisition’, and machine vision for body-mapping and skin-mapping.
He did his PhD in machine learning at UCL and along with fellow students co-founded Searchspace, a company that detects ‘unusual patterns’ in financial transactions (e.g. insider-dealing), which was acquired by Warburg Pincus in 2005. He is the co-editor of two books, ‘Intelligent Systems for Finance and Business’ and ‘Intelligent Hybrid Systems’. He also co-founded the Centre for Fashion Enterprise, an initiative that finances and nurtures luxury fashion designers in London and has produced feature films and several television series. Suran has been featured in Ad Age’s Creativity 50 and was made an officer of the Order of the British Empire (OBE) in 2005.
Ed is interested in teaching machines to learn to reason efficiently and effectively, with a focus on topics including grounded language learning, meta-learning, reinforcement learning, and program synthesis.
Benjamin has broad interests in statistical learning theory and machine learning, with a focus on PAC-Bayes learning, computational statistics, generalisation bounds for deep learning, data-efficient machine learning.
Mark's research interests are Machine Learning Theory with a focus on online learning, matrix completion and semi-supervised learning.
Tony's research interests are in machine reasoning including for argumentation, persuasion, and commonsense reasoning.
Iasonas' research interests are Computer vision and deep learning, in particular shape modeling, unsupervised learning and multi-task learning
Matt’s work aims to design simple machine learning models tailored to the constraints of the problem at hand, particularly in causal inference, private learning, and chemical design.
Niloy's research interests are Geometry processing, data-driven shape analysis, neural rendering and geometric deep learning
Dean is a Principal Teaching Fellow and Director for the UCL Industry Exchange Network's undergraduate projects (Cycle 1) programme. He is interested in the application of AI in projects for his students (450+) and AI in Education. This includes AI topics for hackathons and large team projects that explore the state of the art in applied AI. He has led, supervised and deployed numerous real world industry AI related systems for charities and healthcare as well as larger organisations such as the NHS, IBM and Microsoft.
Brooks is interested in interpretable and explainable models in machine learning, and works on approximate Bayesian inference, deep generative models, and probabilistic programming.
Massimiliano has broad research interests in the areas of machine learning theory and algorithms, with a focus on statistical learning theory, multitask learning and algorithmic fairness.
Sebastian works on teaching machines how to read and reason, in the intersection of Natural Language Processing (NLP) and Machine Learning.
Tim's focus is on reinforcement learning agents that quickly adapt and systematically generalize to new environments through intrinsic reward, neural-symbolic models, and transfer of domain knowledge from external resources like natural language texts and knowledge bases.
John's interests range from statistical learning theory through applications of machine learning methods in diverse domains to reinforcement learning and artificial intelligence more generally.
Dan is a Professor of Robot Vision and Director of the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS). His work has focused on the development of algorithms for understanding surgical video in a variety of surgical specialisations and more recently to linking such AI capabilities to hardware robotics.
Jun's research interests are Multiagent learning, recommender systems and information retrieval
Emine is interested in applications of AI, machine learning and natural language processing to various problems such as conversational system design and evaluation, personalization, recommendation, inferring users' interests&needs, fake news detection, measuring and correcting bias in machine learning algorithms and the broad area of information access and retrieval.
Shi's research interests are Online Social Networks, Cyber Security, Network Science, Internet Routing and Cloud Computing, with a particular focus on bot/fraud detection and information diffusion in online social media.
The AI Centre is also host to the UKRI Centre for Doctoral Training in Foundational Artificial intelligence,