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We welcomed our first cohort in September 2019 and we are continuing to grow. Here are some of their profiles.
2019/20 Cohort
Felix Biggs, supervised by Benjamin Guedj
Samuel Cohen, supervised by Marc Deisenroth
Augustine Mavor-Parker, supervised by Lewis Griffin
Luca Morreale, supervised by Niloy Mitra
Jas Semrl, supervised by Robin Hirsch
Dan Stoddart, supervised by Iasonas Kokkinos
Jingwen Wang, supervised by Lourdes Agapito
Changmin Yu, supervised by Neil Burgess
Jakob Zeitler, supervised by Ricardo Silva
2020/21 Cohort
Reuben Adams, supervised by Benjamin Guedj
Yue Feng, supervised by Emine Yilmaz
Dennis Hadjivelichkov, supervised by Dimitrios Kanoulas
Alex Hawkins-Hooker, supervised by David Jones
Jean Kaddour, supervised by Ricardo Silva
Oscar Key, supervised by Francois-Xavier Briol
Robert Kirk, supervised by Tim Rocktaschel
Robert is interested in reinforcement learning, natural language processing, meta learning and all the intersections thereof. He wants to understand how we can learn how to learn reinforcment learning policies, and how using information stored in natural language can increase the generalisation and sample efficiency of reinforcement learning algorithms. He's supervised by Tim Rocktäschel and Edward Grefenstette as part of the UCL DARK Lab.
Linqing Liu, supervised by Pontus Stenetorp
Yicheng Luo, supevised by Marc Deisenroth
Mirgahney Mohamed, supervised by Lourdes Agapito
Mirgahney H. Mohamed is a PhD student at University College London working on 3D computer vision and uncertainty estimation. He obtained his master's degree in Machine Intelligence from AMMI - African Master in Machine Intelligence at AIMS, and undergrad in Statistics and Computer Science from University of Khartoum Faculty of Mathematical Science."
Antonin Schrab, supervised by Benjamin Guedj
Antonin is interested in designing new algorithms from theoretical results such as generalization bounds. He works on PAC-Bayes and kernel methods with Benjamin Guedj and Arthur Gretton. His research interests include PAC-Bayesian-motivated algorithms for training generative models, generalization bounds for deep neural networks and kernel-based aggregated testing procedures. Prior to starting his PhD, he completed the MSc Machine Learning at UCL and obtained his Master of Mathematics from the University of Oxford.
Oliver Slumbers, supervised by Jun Wang
Yuchen Zhu, supervised by Matt Kusner
Sicelukwanda Zwane, supervised by Marc Deisenroth
