Doctorands

"Warning, in music-words
devout and large,
that we are each other’s
harvest:
we are each other’s
business:
we are each other’s
magnitude and bond."

Gwendolyn Brooks, 1971

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Core Members

"The source of these problems of coordination and cooperation is not the nature of the individuals’ goals, or the instrumental character of rationality. Rather it is individualism about rationality, which holds the unit of activity exogenously fixed at the individual."
Hurley 2004

Alexander McCaffrey

sample-image I am a PhD student at the Artificial Intelligence Research Centre, at City, University of London. I am currently studying how to design artificial agents that use the Free Energy Principle to guide interactions with their environments, under the supervision of Michaël Garcia-Ortiz, Eduardo Alonso and Esther Mondragón. I am particularly interested in the integration of Deep Learning models with new Reinforcement Learning techniques, Evolutionary Game Theory and the relationship between Artificial Intelligence and Neuroscience.

Before joining the Artificial Intelligence Research Centre, I received an MSc in Artificial Intelligence from City, University of London, and a BSc in Economics from UCL. A common theme in both Artificial Intelligence and Economics is their tendency to incorporate insights for other disciplines, including psychology, biology, philosophy, and neuroscience. For me, being forced to take an interdisciplinary approach in both fields is what makes them interesting.

I worked as an academic tutor and was part of a team at HSBC responsible for collecting and analysing large amounts of data to deliver insights to management. Outside of research, I enjoy teaching, poker and am trying to become qualified diver.

   

Esther Mulwa

sample-image I am PhD student at the Artificial Intelligence Research Centre. I am currently working on integrating Associative Learning Models and Deep Neural Networks, under the supervision of Eduardo Alonso and Esther Mondragón.

Before joining the PhD Program, I received a MBA and MSc in Data Science from Strathmore Business School and City, University of London, respectively. I have a vast industrial experience spanning over six years in Information System management in both FMCG and Telecommunications sectors. I have worked with several software and products such as MATLAB, Python, Oracle and Workday for both modelling and system management.

I work as a graduate teaching assistant for modules such as Introduction to AI, and Programming and Mathematics for AI, in the Department of Computer Science, City, University of London. Aside from research, I enjoy taking part in in different sports such as hiking, cycling and have participated actively in several marathons that support different charities.

     


Fatemeh Najibi

sample-image I am a PhD candidate at the Artificial Intelligence Research Centre, at City, University of London. Currently, I am developing machine learning algortihms for forecasting renewable energy output, specifically on applications for Probabilistic Microgrids optimization, under the supervision of Eduardo Alonso and Dimitra Apostolopoulou.

Before starting my PhD, I was involved in both academia and industry. I worked as a researcher for Iran Power Transmission, Generation and Distribution Company (TAVANIR). I am experienced with different industrial software such as CYMDIST, DIgSILENT, ArcGIS, AutoCAD, NEPLAN, DIALux as well as academic software such as MATLAB and GAMS.

I am also a graduate teaching assistant for different modules such as Mathematics in Computing, Operating Systems, Systems Architecture, Introduction to Algorithms, Power System Design and Engineering Mathematics at City, University of London.

I have published in the International Journal of Electrical Power and Energy Systems, the Proceeding of 12th International UKACC Conference on Control (CONTROL2018), the Proceedings of the IEEE PowerTech 2021 Conference, Energy and Energy Conversion and Management.

   

sample-image I am a PhD candidate at the Artificial Intelligence Research Centre, CitAI at City, University of London, working on computer vision for medical image analysis under the supervision of Giacomo Tarroni and Aidan Slingsby. I work on algorithms to learn medical images representations without using labels (i.e. unsupervised and self-supervised) and with limited labels (semi-supervised) and applications of these algorithms for the detection and segmentation of anomalies and organs. I have a vested interest in problems related to unsupervised learning such as compression, image generation and transfer learning and, given that medical images are generally high-dimensional, I am also researching on data efficient sparse image representations such as point cloud or implicit fields learning.

Before starting my PhD I completed a MSc in Data Science in City, University of London and worked for more than 10 years in consulting supporting businesses on analytics and forecasting projects. In my free time I enjoy reading, cooking, travelling and scuba diving.

I have published my research on unsupervised anomaly detection in conference papers such as IEEE International Symposium on Biomedical Imaging (ISBI 2021) and Medical Image Computing and Computer Assisted Interventions (MICCAI 2021). I also achieved 2nd and 3rd positions in the Medical Out-of-Distribution Challenge held at MICCAI 2020.

 


Nathan Olliverre

sample-image I am a PhD student researching the effective use of computer vision and machine learning in Magnetic Resonance Spectroscopy imaging under the supervision of Eduardo Alonso and Carlos Reyes-Adasoro.

I have a vested interest in the generation of data through different means and have spent a large proportion of my time in various deep learning classification models. Outside of academia you can find me either at the gym or playing board games somewhere.

My thesis title is: Exploring the use of Computer Vision and Machine Learning in improving the non-invasive classification rate of brain tumours through Magnetic Resonance Spectroscopy.

I chaired for the British Machine Vision Association a One-Day Symposium entitled Generating data in computer vision and machine learning.

Henri Placek

sample-image I am a PhD student at the Artificial Intelligence Research Centre, at City, University of London. I am supervised by Michaël Garcia-Ortiz and Alex Ter-Sarkisov and Eduardo Alonso.

The focus of my research is learning object-centric latent representation from complex visual scenes. More specifically I aim to design an unsupervised model being able to find object representation and predict unseen images in first-person views using interaction with the environment.My other interest in AI is deep generative modelling, from VAEs, GANs to autoregressive or flow-based models.

Before joining the PhD Program, I received an MSc in Artificial Intelligence from City, University of London. I also graduated from Ecole Polytechnique Paris and ENSAE Paris, where I studied Mathematics, Statistics and Economics. In between I gained over 20 years’ experience in financial markets, from quantitative research to trading in derivatives instruments.

In my spare time I enjoy cooking specially baking, which requires a lot of running to burn off the excess calories.

 


Sami Saadaoui

sample-image I am an Industrial PhD student at the Artificial Intelligence Research Centre, CitAI, at City, University of London, working under the supervision of Eduardo Alonso and Alex Ter-Sarkisov. In collaboration with Ai-London and EIT Digital, I will be working on developing artificial intelligence solutions to enable the automatic configuration of efficient next best action advice in scenarios with different long-term financial planning goals and channel preferences in order to close the Advice Gap for Life, Pension & Investments (LP&I).

I have a master's degree in Computer Science Engineering of Distributed Computer Systems from Université du Littoral-Côte-d'Opale, France, and an Engineering degree (BSc+MSc) in Computer Science Parallel and Distributed Systems from Batna University, Algeria, with a solid professional experience in software development, architecture, and modern DevOps solutions.

I work as Head of AI R&D at Ai-London in different projects using different next generation technology stacks to enable Life, Savings and Investment providers to dramatically reduce their operational cost base and increase their strategic flexibility.

 

Daniela Stern-Gabsi

sample-image I am a PhD candidate at the Artificial Intelligence Research Centre, CitAI, at City, University of London. I have as supervisors Michaël Garcia-Ortiz and Alex Ter-Sarkisov.

My research focuses on Reinforcement Learning, mainly in Hierarchical Reinforcement Learning and Meta-Learning. I am interested in developing agents that learn to act successfully by understanding the compositional structure of tasks, learning both the components of the underlying task and the combination that is relevant for a new task. I aim to improve the agents learning speed and sample efficiency and their ability to generalize from one task to another.

I have more than 20 years of experience as a data scientist and software engineer, developing applications for decision-makers. I am currently in the final stages of obtaining an MSc in Artificial Intelligence from City, University of London. I obtained my BA in Computer Science from the Technion, Israel Institute of Technology.

I believe in simple solutions and in drawing inspiration and intuition from the human way of thinking. In my free time, I enjoy reading and travelling.

  


Pagination