People

"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

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


Atif Riaz

sample-image I am a PhD candidate at the Artificial Intelligence Research Centre. My PhD work is in the domain of neuroimaging and martificial intelligence. I have explored different machine learning and deep learning methods in my work. I enjoy teaching and research.

Prior to joining City, University of London, I completed my MSc at the National University of Sciences and Technology (NUST), Pakistan.

Interests: Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), auto-encoders, Generative Adversarial Networks (GANs).

Fathemeh Najibi

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I am a PhD candidate at the Artificial 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 joining Ph.D., 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 as a graduate teaching assistant for different modules such as Mathematics in computing, Operating System, System Architecture, introduction to algorithms, Power System Design and Engineering Mathematics in the City University of London.


Benedikt Wagner

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I am a PhD Student at the Artificial Intelligence Research Centre. I also work as Graduate Teaching Assistant in the Computer Science Department, at City, University of London and as a freelance consultant in the area of Machine Learning and Data Science focussing on Explainable Artificial Intelligence.

My MSc thesis (2018) was entitled “Knowledge extraction from neural networks using tree-structured representations”.

Esther Mulwa

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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.


Sarah Scott

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I am a PhD student at the Artificial Research Centre, at City, University of London. My research focus is on encouraging concept learning in text-based AI through the use of exploration in text-based adventure games. I am supervised by Eduardo Alonso.

Before starting my PhD, I obtained a MSc in Data Science from City, University of London and a BSc in Economics from the University of Warwick. I also worked for 5 years in financial IT, supporting and developing pricing, risk and compression tools for the Rates and FX desks.

Nathan Olliverre

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I am a PhD student researching the effective use of computer vision and machine learning in Magnetic Resonance Spectroscopy imaging. 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


Pagination