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< Back Dr Kevin Denamganaï University of York iGGi Alum Available for post-PhD position After graduating as an Engineer from the Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA), France, with two double-degree diplomas, a MEng in Electrical Engineering and Information Science from the Osaka Prefecture University (OPU), Japan, and a MRes in Artificial Intelligence and Robotics from the Université de Cergy-Pontoise (UCP), France, Kevin Denamganaï spent a year accumulating experience as a Robotics & Machine Learning freelancer. He is now putting those skills at use in the IGGI PhD program, that, among other things, gives him the opportunity to reunite with video games. Indeed, it was thanks to a keen interest towards video game creation that he started learning programming around 12. His research interests are about everything psychology, neuroscience, AI, (deep) reinforcement/imitation learning, robotics, and natural/artificial language emergence and understanding as well as human-computer interfaces, challenging the question what are the necessary components of artificial agents to be able to converse with human-beings in an engaging manner and to be able to cooperate with them towards a pre-defined goal, e.g. clearing a level in a given video game. kevin.denamganai@york.ac.uk Email Mastodon https://kevindenamganai.netlify.app/ Other links Website LinkedIn BlueSky https://github.com/Near32/ Github Supervisor(s): Dr James Walker Featured Publication(s): ETHER: Aligning Emergent Communication for Hindsight Experience Replay Visual Referential Games Further the Emergence of Disentangled Representations Meta-Referential Games to Learn Compositional Learning Behaviours A comparison of self-play algorithms under a generalized framework On (Emergent) Systematic Generalisation and Compositionality in Visual Referential Games with Straight-Through Gumbel-Softmax Estimator ReferentialGym: A Nomenclature and Framework for Language Emergence & Grounding in (Visual) Referential Games A generalized framework for self-play training Coupled Kuramoto oscillator-based control laws for both formation and obstacle avoidance control of two-wheeled mobile robots Obstacle avoidance control law for two-wheeled mobile robots controlled by oscillators Themes Game AI - Previous Next

< Back Dr Ahmed M. A. Sayed Queen Mary University of London Supervisor Ahmed Sayed is a Lecturer (Assistant Professor) of Big Data and Distributed Systems at the School of EECS, QMUL and leads the Scalable Adaptive Yet Efficient Distributed (SAYED) Systems Lab. He has a PhD in Computer Science and Engineering from the Hong Kong University of Science and Technology. His research interests lie in the intersection of distributed systems, computer networks and machine learning. He is an investigator on several UK and international grants totalling nearly USD$1 million in funding. His work appears in top-tier conferences and journals including NeurIPS, AAAI, MLSys, ACM EuroSys, IEEE INFOCOM, IEEE ICDCS, and IEEE/ACM Transactions on Networking. He is interested in supervising students with a background in game AI, machine learning, distributed systems, and/or creative computing, Ahmed is interested in working with students at the intersection of artificial intelligence, machine learning, and creative computing. He aims to leverage AI/ML methods, game data and player research to design intelligent game agents by creating systems that enable game agents to learn better gaming strategies, thus enhancing the gaming experience. He is open to any research proposals in that space and currently is keen on exploring solutions that are based on leveraging the emerging distributed privacy-preserving ML ecosystems on large-scale game data. If you are interested in working with him on this, please reach out to him. ahmed.sayed@qmul.ac.uk Email Mastodon http://eecs.qmul.ac.uk/~ahmed/ Other links Website https://www.linkedin.com/in/ahmedmabdelmoniem/ LinkedIn BlueSky https://github.com/ahmedcs Github Themes Creative Computing Design & Development Game AI Game Data Player Research - Previous Next

< Back David Hull University of York iGGi Manager iGGi Admin I have worked at the University of York since October 1995, almost all of it in the Department of Computer Science. My various roles have included Laboratory and Facilities Manager, Technical Manager and, most recently, Project Manager. Outside work, I have been a change-ringer for almost 50 years, and am currently a member of the band that rings the bells weekly at York Minster. I am also an accredited teacher of bellringing. I do parkrun most weeks, alongside the occasional 10k and half marathon, like to watch cricket, and play the clarinet and piano. iggi-admin@york.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes - Previous Next

< Back Dr Oliver Scholten University of York iGGi Alum Oliver Scholten is working on understanding the use of cryptocurrency technologies for gambling and gaming. His work provides researchers with the tools and context needed to understand player behaviours in these technologically advanced domains. He is the creator of gamba - a python library designed to enable quick replication of existing player behaviour tracking studies. He has also published several peer reviewed articles, and had written evidence published by the UK House of Lords which describes the mechanics behind decentralised gambling applications. As a PhD student, his thesis focuses on decoding and analysing cryptocurrency gambling and cryptocurrency gaming transactions. These transactions offer a more granular insight for researchers into both gambling and gaming than has been historically possible, this work therefore lays the foundations for explorations across different schools of research, and more specifically, advanced player transaction analytics. Please note: Updating of profile text in progress oliver@gamba.dev Email Mastodon https://www.ojscholten.com Other links Website https://www.linkedin.com/in/ojscholten LinkedIn BlueSky https://github.com/ojscholten Github Featured Publication(s): On the Evaluation of Procedural Level Generation Systems On the Behavioural Profiling of Gamblers Using Cryptocurrency Transaction Data Inside the decentralised casino: A longitudinal study of actual cryptocurrency gambling transactions Decentralised Gambling Overview Decentralised Gambling: The York Combined Transaction Set Unconventional Exchange: Methods for Statistical Analysis of Virtual Goods Utilising VIPER for Parameter Space Exploration in Agent Based Wealth Distribution Models Ethereum Crypto-Games: Mechanics, Prevalence, and Gambling Similarities Themes Game Data - Previous Next

< Back Dr Jon Hook University of York Supervisor Jon Hook is a Senior Lecturer (equivalent to an Associate Professor) in Interactive Media in the Department of Theatre, Film, Television and Interactive Media at the University of York. His research is situated in the field of Human-Computer Interaction (HCI) and explores the design and development of new interactive media content forms and tools to support their creation. This research combines his deep interest in new forms of interactive technology and media with empirical, theoretical and methodological perspectives, in the human-centred design of novel interfaces and interaction techniques for a broad range of artistic and everyday creative practices. His current research is focused on the design and development of new forms of responsive and immersive media content, with a particular interest in data-driven storytelling. He was recently the principal investigator of the EPSRC funded Perspective Media: Personalised Video Storytelling for Data Engagement project. He also a co-investigator of the InnovateUK WEAVR: Pioneering Fully Integrated Cross-Reality Spectator Experiences in Esports and Beyond immersive experiences demonstrator and the Digital Creativity Labs – a £4m EPSRC, AHRC and InnovateUK funded research centre exploring impact-driven research in the creative industries. He was also previously Co-I of the AHRC Within the walls of York Gaol: Memory, Place and the Immersive Museum the AHRC Digital Creativity for Regional Museums: Immersive Experiences Smart Commissioning Toolkit. He is especially interested in supervising students who’d like to do HCI research that involves making and evaluating new interactive media experiences. Some example topic areas that he might be the right supervisor for include, but aren’t limited to: Games to support broader data engagement and literacy Data-driven storytelling in, and about, games The intersection between games and interactive documentary film Responsive and interactive video storytelling in games The space where theatre and games converge Cultural heritage engagement using games Research themes: Game Design Games with a Purpose E-Sports Player Experience jonathan.hook@york.ac.uk Email Mastodon https://www.jonhook.co.uk Other links Website https://www.linkedin.com/in/jonathan-hook-641b597/ LinkedIn BlueSky https://github.com/jonathanhook Github Themes Applied Games Esports Player Research - Previous Next

< Back Dr Charline Foch University of York iGGi Alum Charline first came to the UK in 2011 to study English and Film Studies at King’s College London, before going on to a MSc in Film, Exhibition and Curation at the University of Edinburgh. By chance, accident or fate, she stumbled into the games industry, working in an independent game studio in Berlin, where she touched upon customer support, community management, content writing and QA for a new MMORPG. This experience gave her the push to start a PhD in video games. In her spare time, she is an avid film viewer, volleyball player, and amateur artist. Charline’s research focuses on how people conceptualise failure, with an emphasis on its perceived positive, desirable effects on player experience. Throughout her PhD, she has conducted research among video games players to gain a better understanding of what they perceive as the purpose and value of failure in the games they play; and conducted research among video games developers to gain a better understanding of what processes, obstacles, and ideas go into the design and implementation of failure in their games. With a focus on single-player, more narrative-driven games, she has used this research to design a cards-based design toolkit to support game designers in approaching the question of fail states and player experience in the early stages of the game development process, helping them reflect on the intersection between failure, game mechanics, storytelling, and player experience when working on their games. Aside from her PhD, Charline has also worked with the Digital Creativity Labs on the PlayOn! project, a European project gathering 9 theatres across Europe working on immersive technologies (VR, AR, apps for audience participation...) and theatre productions. During her time at PlayOn!, she has worked on the connections between the games industry and the performance arts, investigating how technology, game design principles, and theatre can work together, and what barriers practitioners face when attempting to reconcile all sides in a single production through experimentation and collaboration. charline.foch@york.ac.uk Email https://mastodon.gamedev.place/@chafoch Mastodon https://charlinefoch.carrd.co Other links Website https://www.linkedin.com/in/charline-foch-97196663 LinkedIn BlueSky Github Supervisor: Dr Ben Kirman Featured Publication(s): “The game doesn't judge you”: game designers’ perspectives on implementing failure in video games “Slow down and look”: Desirable aspects of failure in video games, from the perspective of players. Themes Design & Development Player Research - Previous Next

< Back Dr Anne Hsu Queen Mary University of London Supervisor Anne Hsu’s research includes machine learning, artificial agents, natural language processing and learning, human decision making, interaction design, and well-being technology. Her interests include developing interactive systems that use machine learning and understanding of human psychology to improve human behaviour. She is particularly interested in supervising students with a machine learning, design, HCI, or behavioural sciences background on the following topics: understanding and designing for curiosity in games design for behaviour change motivational/educational games Research themes: Game AI Game Design Games with a Purpose Player Experience Gamification anne.hsu@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/anne-showen-hsu LinkedIn BlueSky Github Themes Applied Games Design & Development Esports Player Research - Previous Next

< Back Dr Paulo Rauber Queen Mary University of London Supervisor I am a lecturer in Artificial Intelligence at Queen Mary University of London. Before becoming a lecturer, I was a postdoctoral researcher in the Swiss AI lab working on reinforcement learning under the supervision of Jürgen Schmidhuber. I believe that intelligence should be defined as a measure of the ability of an agent to achieve goals in a wide range of environments, which makes reinforcement learning an excellent framework to study many challenges that intelligent agents are bound to face. p.rauber@qmul.ac.uk Email Mastodon https://paulorauber.com/ Other links Website LinkedIn BlueSky https://github.com/paulorauber Github Themes Game AI - Previous Next

< Back Dr Adrian Bors University of York Supervisor Adrian G. Bors is an Associate Professor at the University of York and has published more than 150 papers in international journals and conferences in the areas of his research interests. He is interested in supervising projects related to the application of novel artificial intelligence methods and computer vision in Game AI. One of the areas of interest is in the modelling of game characters (intelligent agent) continuously learning from their environments, able to transfer their knowledge from one stage to the next, while accumulating the information, like human/animal beings and enabling to continuously adapt to their environments. Another topic of interest is represented by conditional image and video generation for developing game environments. The conditional video/image generation will depend on certain factors that can be pre-established or be the result of self-learning by an (intelligent agent). Most existing games relying on no movement representation lack in representing realistic and continuous movement. In this direction of research, we will aim to generated video which would be consistent with realistic movement of game characters. Specific attention will be paid to modelling the interaction of the generated movement with the environment or other actors (game characters). In another direction of research, Adrian G. Bors will supervise projects in digital watermarking of 3D graphical characters. Codes will be invisible embedded and retrieved from the 3D graphics representations. The code embedded, like the DNA in human/animals, will enable the character to act in specific ways, defining behavioural traits in similarly looking graphics characters. adrian.bors@york.ac.uk Email https://www.researchgate.net/profile/Adrian-Bors Mastodon https://www-users.cs.york.ac.uk/adrian/ Other links Website https://www.linkedin.com/in/adrian-bors-32a3668/ LinkedIn BlueSky https://github.com/AdrianBors Github Themes Game AI - Previous Next

< Back Dr Mike Cook Supervisor Mike is a Senior Lecturer at King's College London where he leads research into automated game design, computational creativity, and the theory and practice of generative systems. mike@possibilityspace.org Email Mastodon https://www.possibilityspace.org/ Other links Website LinkedIn BlueSky Github Themes Creative Computing Design & Development Game AI - Previous Next

< Back Oliver Withington Queen Mary University of London iGGi PG Researcher Available for post-PhD position Oliver Withington is a AI and games researcher working on novel methods for evaluating content generation systems for games. Following a successful career in the healthcare technology industry he decided to combine his life long love of games and interest in AI research into a PhD with the iGGi CDT in 2020. He lives in London with his wife and two young daughters, and when he is not writing about, thinking about, or talking about games you can probably find him in either his local bouldering gym, or in the park either pursuing or being pursued by two small children. A description of Oliver's research: Oliver's primary motivation is to make the evaluation of novel content generators more standardised, robust and straightforward for both researchers and game designers. Currently his focus is on techniques for producing informative visualisations of the output spaces of content generators. His work has been published at many of the leading conferences in his field, and he has also taken his work and ideas to the game industry, most recently in the form of a talk at GDC 2025's AI Summit. owithington@hotmail.co.uk Email Mastodon http://owithington.co.uk Other links Website https://www.linkedin.com/in/oliver-withington-909052bb/ LinkedIn BlueSky https://github.com/KrellFace Github Supervisors: Dr Jeremy Gow Dr Laurissa Tokarchuk Featured Publication(s): Exploring Minecraft Settlement Generators with Generative Shift Analysis HarmonyMapper: Generating Emotionally Divers Chord Progressions for Games. The Right Variety: Improving Expressive Range Analysis with Metric Selection Methods Visualising Generative Spaces Using Convolutional Neural Network Embeddings Compressing and Comparing the Generative Spaces of Procedural Content Generators Illuminating Super Mario Bros: quality-diversity within platformer level generation Themes Creative Computing Design & Development Game AI Previous Next

< Back Dr Michelangelo Conserva Queen Mary University of London iGGi Alum Michelangelo Conserva is a second year PhD researcher studying principled exploration strategies in reinforcement learning. He is particularly interested in randomized exploration and, more generally, Bayesian methods for reinforcement learning. He holds a BSc in Statistics, Economics and Finance from Sapienza, University of Rome and an MSc in Computational Statistics and Machine learning from University College of London. A description of Michelangelo's research: As a PhD student at Queen Mary University of London, Michelangelo aims to leverage Bayesian models to develop principled algorithms for reinforcement learning in the context of function approximations. The main challenge lies in finding a balance between computational costs and optimality. Evaluating such balance requires careful evaluation, which is currently lacking in reinforcement learning. m.conserva@qmul.ac.uk Email Mastodon https://michelangeloconserva.github.io/ Other links Website https://www.linkedin.com/in/michelangeloconserva/ LinkedIn BlueSky https://github.com/MichelangeloConserva Github Supervisors: Prof. Simon Lucas Dr Paulo Rauber Featured Publication(s): What are you looking at? Team fight prediction through player camera Posterior Sampling for Deep Reinforcement Learning Hardness in Markov Decision Processes: Theory and Practice Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits The Graph Cut Kernel for Ranked Data Themes Game AI - Previous Next