Cohorts: 2014 | 2015 | 2016 | 2017 | 2018

Cohort 2018


Alessandro de Palma

I'm from Apulia, southern Italy, but in the last few years I spent time closer to the Alps than the Mediterranean. I got my Bachelor in Computer Engineering from Politecnico di Torino and a Master's in Computer Science from ETH Zurich. There, I first focused on distributed computing and later converged to machine learning. Willing to combine these two interests, I spent 6 months at MIT for my Master's thesis on distributed approximate Similarity Search and, after graduation, I worked on parallel Bayesian Optimization at IBM Research Zurich. My current interests lie at the intersection between optimization and machine learning and I am therefore very excited to join the AIMS CDT, where I will strengthen and extend my theoretical background in these areas. During my free time, I'll be printing analog photography, shooting many more photographs than I can print, and pretending I can play guitar.


Shaan Desai

I am from Lusaka, Zambia and graduated from Harvard College with a Bachelor’s in Physics and a Master’s in Computational Science. During college, I worked in the Kaxiras Group where I developed a deep interest in using machine learning techniques to solve physics problems, especially those relating to the discovery of novel materials for renewable technology. I am therefore excited to pursue this interest further through the AIMS DPhil and the generous support of the Rhodes Scholarship.


Bryn Elesedy

I grew up in North West England and graduated from Jesus College, Cambridge in 2015 with a master's in mathematics with astrophysics. Before coming to Oxford I worked as a quant in a hedge fund, where I was in a team designing and building systematic trading strategies. My work exposed me to ideas from programming, data science and statistics and following this I became interested in machine learning and later in AI more broadly. I am excited to start the AIMS programme and I hope that the experience will equip me to contribute to these fields.


Anna Gautier

Originally from Philadelphia, USA, I completed my BSc in Computer Science and my BA in Pure Mathematics at Washington University in Saint Louis. In 2017 I moved to the UK to work towards my MSc in Applicable Mathematics at The London School of Economics. My research interests include Artificial Intelligence and Multi-Agent Systems, particularly the fields of mechanism design and algorithmic game theory.


Saad Hamid

I was born in Rawalpindi, Pakistan, but grew up in London. I graduated from Balliol College, University of Oxford with a Master of Engineering (MEng) in 2018. It was the pursuit of this degree that led me to develop an interest in autonomous systems. My final year project focussed on Bayesian Quadrature, and I'm excited to continue working on probabilistic numerical methods and their application to machine learning during the AIMS CDT. Outside of engineering, I enjoy rowing, running, and travelling.


Prannay Kaul

I am from Sheffield, South Yorkshire and graduated in 2018 with an MEng in Engineering Science from Somerville College, Oxford. I spent my 4th year at Princeton University where my thesis focused on the experimental analysis of an integrated photonics circuit for wireless communications. At Princeton, my interest in machine learning began and I am excited to learn more about autonomous systems during my AIMS studies. I am an avid traveller and in my spare time I enjoy playing cricket and listening to political debates.


Andreas Kirsch

Originally from Romania, I grew up in Southern Germany. After studying Computer Science and Mathematics at the Technical University in Munich, I spent a couple of years in Zurich as a software engineer at Google/YouTube. I moved to London and worked as a performance research engineer at DeepMind for a year. I'm interested in Bayesian Deep Learning and ethics and safety in AI.


Vitaly Kurin

I'm from Russia where I studied economics (BA) in Moscow State Institute of International Relations, and applied mathematics and computer science (BSc) in Moscow State University. Then I got my Media Informatics master's degree from RWTH Aachen University in Germany writing my thesis on Learning from Demonstration. I'm particularly interested in how machine learning models (especially in reinforcement learning) can use any prior information we can provide: human demonstrations, knowledge databases, other models predictions. For more detail, please, visit


Alexander Mitchell

I graduated with a Masters in Engineering Science from the University of Oxford in 2018. My Master’s project was in the field of Model Predictive Control subject to probabilistic constraints. The consequent controllers rejected unknown disturbances and could adapt to system parameters which vary slowly over time. Both controllers used a scenario approach to approximate the probabilistic constraints with linear ones. My areas of interest are in control for legged robots, path planning and computer vision. Before university, I spent a gap year in industry in Cambridge, UK working for an engineering company in medical technologies. I am also a keen pilot.


Matthew Newton

I grew up in South West England and completed my MEng undergraduate degree at St. Catherine's College, Oxford in Engineering Science. My main academic interests lie in Machine Learning, Network Systems and Control Systems. These were first realised during a summer internship at the Oxford MAN Institute, where I investigated the relationships between unstructured financial data sets. I then went on to specialise in Information Engineering and Mathematics in my final year of university and for my Master's Project I investigated the stability of pipe flow by using a novel control theory perspective. Outside of academia I am heavily involved in athletics as a 400m runner, but also enjoy surfing, various outdoor pursuits and (trying) to keep up with technology.


Steffen Ridderbusch

After getting two undergraduate degrees, first in engineering and then in mathematics, and taking some parallel graduate-level classes at the university in my hometown, Paderborn, I had the opportunity to pursue an internship at an aerospace research center in the United States. Following this experience, I did my master’s in mathematical Modelling and Scientific Computing at Oxford, where I focused on statistical mechanics and swarm robotics. I took a year out between my master’s and PhD to learn some Spanish in Salamanca, intern at a company working on autonomous driving in Munich, and co-lead the Tech and HR teams of the pan-European movement. In the AIMS CDT, I will be focusing on multi-objective optimal control and how it can interface with other AI-relevant topics, like machine learning and formal verification.


Kaur Aare Saar

I am originally from Estonia where I also grew up before reading for the Engineering Tripos at the University of Cambridge. During the later years of my course I specialised in Information Engineering. My final project was about applying machine learning methods to self-optimise the performance of real life robots. AIMS CDT provides an excellent opportunity to combine my different areas of interest, including machine learning and robotics. I spend most of my free time on travelling and I enjoy recording and systematically analysing my travel patterns.


Thomas Steeples

I grew up in Leighton Buzzard, in Bedfordshire, and I first attended UCL where I attained my MSci in Mathematics. Following this, I completed my MSc in Computer Science at the University of Oxford, where I explored the notion of local equilibria in Boolean Games. I then worked at IBM as part of the Automation team before returning to Oxford for the AIMS CDT. My primary research interests lie in computational game theory, the foundations of artificial intelligence, and machine learning. In my spare time, I enjoy the work of David Lynch, I like playing chess and I have recently developed an interest in photography.


Filip Svoboda

I work on Deep Learning Efficiency under the supervision of Dr. Nicholas Lane and Dr. Niki Trigoni. The early applications of my work are in the resource constrained interference for embedded and wearable devices. My long-term aim is to develop and popularize my concept of Rational Automated Machine Learner – a learning paradigm whereby a wider set of resource costs and preference considerations can be consulted along with the model accuracy in the AutoML process. I have background in Statistics and Computer Science (MSc UCL), Econometrics (MPhil Oxford), and Economics (BSc Amsterdam). In my very early career, I was a research assistant at the Experimental Oncology Institute of the Slovak Academy of Sciences. For more detail, please, visit


Panagiotis Tigkas

I received my B.Sc. from the University of Ioannina, Greece and my M.Sc. in Machine Learning from the University of Bristol. During my M.Sc., I carried out research on sequence prediction models for interactive music improvisation. Prior to joining Oxford, I spent several years in the IT industry, during which I had the opportunity to work for Microsoft, Autodesk Research (Generative Design team), Brave Research (Privacy Preserving Machine Learning) and a startup I co-founded, Filisia Interfaces (Special Education and Rehabilitation HCI). I spend most of my free time making music and thinking about philosophy, nature and culture. For more information, see


Rhydian Windsor

I was born in Atlanta, GA in the US but grew up in the beautiful county of Shropshire in England. However, you can probably tell from my name my dad is a proud Welshman! For my undergraduate degree I studied Physics at the University of Manchester (MPhys), although in the last few years it I’ve became increasingly interested in machine learning and AI as a result of an internship I did and subsequently my Master’s project using machine learning for lung cancer imaging at the Christie Hospital in Manchester. I’m particularly interested in the use of intelligent systems in medicine and am thrilled to have my studies at the CDT funded by Cancer Research UK. When I’m not working, I’m usually playing sports (in particular rugby and running) with the occasional foray into baking.


Mandela Patrick

I am originally from Trinidad and Tobago, the twin-island republic in the Caribbean. Upon completing my high school studies in Trinidad, I enrolled as an undergraduate student at Harvard University where I received a Bachelor of Arts degree in Computer Science. At Harvard, I had the opportunity to pursue software engineering internships at Facebook, Goldman Sachs, Instagram and B12. Upon taking classes in both machine learning and artificial intelligence at Harvard, my interest in machine learning got piqued when I interned on the Instagram Machine Learning team, where I built out the core infrastructure to add support to multi-task multi-label neural network models to personalize experiences on Instagram Feed and Explore. I am excited to pursue this interest further through the AIMS program and the generous support of the Rhodes Scholarship.