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< Back Dr Nathan John Queen Mary University of London iGGi Alum After graduating with a MEng in Computer Science from the University of Bristol, Nathan joined the games industry as a programmer, working for Climax Studios, Gaming Corps and Freejam, before moving to a career as a general software engineer, while still developing indie games on the side. His experiences across a range of industries sparked a passion for testing, and left him wondering if there were was to improve the automated testing in game development. Borne from an experiment Nathan had performed training AIs to play his indie game WarpBall, in which he found the agents solved for exploits in the authored AI rather than playing the game well, his research project proposes a novel method for improving the quality of behaviour of human authored agents by pitting them against trained agents and observing what bad behaviours/exploits the trained agents reveal. Authored agents refer to AI agents whose actions are explicitly designed by programmers using traditional techniques such as Utility functions, Behaviour Trees and state machines; trained agents refer to agents whose behaviour is learned by playing many games against the authored agents. Email n.m.john-mcdougall@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Jeremy Gow Dr Laurissa Tokarchuk Themes Design & Development Game AI - Previous Next

< Back Dr Jen Beeston University of York iGGi Alum + Supervisor Jen is currently working as a Lecturer in HCI in the Department of Computer Science (University of York) whilst writing up her PhD. She has a multidisciplinary background, from studying subjects such as environmental science and media production and having worked in various jobs such as grassland research, flood risk management, and plasterboard quality. She feels extraordinarily fortunate to have been able to do research into her lifelong hobby of playing digital games. In particular, Jen feels it is important that everyone has the opportunity to enjoy gaming should they wish. As such, her research has been aimed at exploring the experiences of people with disabilities in playing games, beyond how various technologies can support play. Jen’s research is focused particularly on the social experiences of players with disabilities in-game and within the broader gaming community. She has worked alongside the charity AbleGamers with the aims of investigating these player’s experiences of gaming, what effects alternative controls have upon play, and what it’s like for these players in multiplayer or online games. Jen is broadly interested in HCI, user experience, player experience, inclusivity, social play, and game communities. Outside of her work, she enjoys walking, thinking, reading, crochet, art, and tabletop roleplaying games. Email jen.beeston@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Validation and Prioritization of Design Options for Accessible Player Experiences Social experiences of people with disabilities in playing (in) accessible digital games Enabled players: The value of accessible digital games Accessible player experiences (APX): The players Characteristics and motivations of players with disabilities in digital games Perceptions of Telepresence Robot Form Themes Accessibility - Previous Next

< Back Dr Oliver Withington Queen Mary University of London iGGi Alum 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. Email owithington@hotmail.co.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Jeremy Gow Dr Laurissa Tokarchuk Featured Publication(s): Designer Difficulties: Visualizing the Possibility Spaces of Dynamic Difficulty Adjustment Systems Exploring the Possibility Space of 1 Billion Spells 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 https://www.youtube.com/watch?v=4m1gYriq_pc Previous Next

< Back Andrew Martin Queen Mary University of London iGGi Alum Applications in game development for programming language theory and AI Modern game development is highly iterative. Iteration is usually discussed in terms of a team completing design iterations, but can also be considered at the level of an individual developer attempting to complete a task, or experimenting with some ideas. At this level, the feedback loop provided by the tool becomes critical. Programming environments in particular often have a very poor feedback loop. Programming feedback can be thought of in terms of how quickly and seamlessly the user is able to observe the results of their work. This process is usually plagued with manual tasks and long pauses. It is common that a user will need to recompile, relaunch their program, and then manually recreate whatever state is required to observe the behaviour that they are working on. Frameworks like Elm, React and Vuejs are establishing a new norm of automatic hot-reloading with state preservation. These systems represent a branch of programming language research that is strongly focused on developer experience. In order to improve upon this work for game development, we must overcome the unique challenges that game development entails. Although the systems mentioned are all quite recent, there is a rich vein of research to draw on, which can be traced through dataflow programming, Smalltalk, Erlang, functional-reactive programming, Lisp and more. Predictive completions are considered by many to be a natural next-step in the evolution of live programming environments. An AI programming assistant would propose program fragments as completions or alternatives. The agent may seek to anticipate the user’s intent, or to provide creative suggestions. There is much relevant research in the fields of program synthesis, inductive logic programming, machine learning and genetic programming. One significant problem is how to smoothly and safely integrate a system like this into the user’s workflow. Many of the properties useful for safely enabling live programming features, such as isolation of side-effects, will also permit an AI agent to safely generate and execute code. Andy graduated from Imperial College London with an MEng in Computing in 2011. Following this he worked on game engine tools and technology at a startup called Fen Research, and then as a senior developer at a software consulting firm called LShift. In 2016 he spent six months working as a Research Associate in the Computational Creativity group at Goldsmiths, before starting his PhD. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

< Back Dr Yizhao Jin Queen Mary University of London iGGi Alum Currently a student at Queen Mary University of London (QMUL), I have delved deep into the realms of artificial intelligence and game design. With a passion for understanding the complexities behind real-time strategy (RTS) games and their dynamic, unpredictable nature, I have committed myself to contribute novel insights to this domain. Research: My primary research area is Hierarchical Reinforcement Learning (HRL) for Real-Time Strategy (RTS) games. RTS games, known for their intricate mechanics and vast decision spaces, present a formidable challenge for traditional AI approaches. By employing HRL, I aim to develop agents that can not only understand the multi-layered tactics and strategies of these games but also learn to adapt to ever-changing game scenarios efficiently. The main objectives of my research are: Better Generalization: To create agents that can seamlessly transition between different RTS games or various maps within the same game without extensive retraining. This involves understanding common strategic threads across multiple game domains. Efficient Training: RTS games are inherently time-consuming due to their vast decision spaces and prolonged gameplay. My research seeks ways to optimize the training process, ensuring that AI agents can learn faster and with fewer computational resources. Email acw596@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Greg Slabaugh Prof. Simon Lucas Themes Game AI Previous Next

< Back Dr Myat Aung University of York iGGi Alum Immersion is a state in which players are engaged to a degree of total absorption that inhibits the ability to correctly report one’s surroundings or time. Present theory on immersion has developed a coherent model that provides sufficient evidence to distinguish itself from other cognitive concepts such as presence, attention, selective attention, absorption and flow. However, immersion research thus far has been hindered by difficulties with taking in-vivo measurements of cognition and physiological responses during videogame play. This presents an ideal opportunity for implementations of neuroimaging methods to carry out such real time measurements of attention, as well as other cognitive processes and their roles in videogame immersion. Using various combinations of neural and physiological methods such as skin conductance, eye tracking, electroencephalography and even functional magnetic resonance imaging, it is now possible to obtain richer data in immersion research. The goal of this project is to apply such methods in order to better define and measure videogame immersion, identify the cognitive processes and hierarchical models that are involved in immersion and ultimately contribute to the literature in videogame immersion. Though neuroimaging is limited by statistical sensitivity, challenging experimental logistics and non-ideal lab environments, they are still presently the best tools available to obtain fine-grain data of attention and the many other cognitive components of immersion. Such knowledge would contribute significantly to a better understanding of effective development of videogames, as well as educational tools. I am an MPsych Psychology graduate from the University of York, having studied Psychology, Cognitive Neuroscience & Neuroimaging for four years. My Master’s research was primarily in vision, attempting to manipulate and record parahippocampal responses to visual stimuli selected parametrically by computer algorithms. During my degree I also spent much of my time researching videogames, studying the literature on the effects of videogame play on sleep, and working with a IGGI PhD student as a lab assistant. Between my degree and my PhD, I have also been working as a data analyst at Digital Creativity Labs researching skill learning in large gaming populations from Riot Games’ League of Legends. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Different rules for binocular combination of luminance flicker in cortical and subcortical pathways Investigating the non-disruptive measurement of immersive player experience The trails of just cause 2: spatio-temporal player profiling in open-world games Predicting skill learning in a large, longitudinal MOBA dataset Themes Game AI - Previous Next

< Back - Meet me @ Develop:Brighton 2026 - Tania Dales University of York iGGi PG Researcher Available for placement Tania is an indie video game designer and developer, working with horror, science fiction and games which are a little strange, bizarre and uncomfortable. About Tania's research: "My research explores the relationship between humanoid character design and existential horror in video games. I adopt a mixed methods approach, investigating existing games, designer interviews and player surveys, along with a research-through-design methodology, reflecting on the practice of character design. The core games I am exploring incorporate themes of existential horror, identity, self, and human existence. In video games with horror themes, non-playable characters (NPCs) are often used to prompt a reaction from the player, and it isn’t always fear. There are often times when the NPC isn’t acting in an outwardly threatening way, yet it still causes us to become unsettled. My research explores unsettling NPCs that incorporate themes of existential horror." Email tania.dales@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Ben Kirman Themes Design & Development Game AI Immersive Technology Player Research - Previous Next

< Back Dr Chris Madge Queen Mary University of London iGGi Alum Turning Difficult Scientific Problems into Easy Games: Crowdsourcing Solutions via Gamification The aim of the research is to exploit, on a large scale, the idea introducing game elements in a non-game context (gamification) and make use of a large population of non-expert users to solve scientific problems (crowdsourcing). The proposed research follows the increasingly popular concept of splitting a large, complex task into small easily digestible tasks that lend themselves to division, distribution and game representation. This research will begin by taking advantage of the University of Essex’s expertise in the field of Natural Language Engineering. Multiple games will be created to attempt to encourage people to participate in training natural language models. This will be achieved by splitting these tasks into smaller problems that can be represented as games, and easily solved by players that could not easily be solved computationally. Alongside this, the success of different gamification methods and game design choices will be evaluated to determine their effect on the information gathered and the accuracy achieved. This evaluation will be used to guide the development of future games in the research with a view to producing better quality models for solving natural language problems, and improving gamification. Prior to starting my PhD with IGGI I completed a BSc in Computer Science and MSc in Advanced Computer Science. During both of those I took multiple computer game and AI courses in addition to text analytics and natural language engineering courses. During my BSc I was fortunate to work at Signal Media as an intern on text analytics related problems. Before starting my BSc I worked as a software developer for 5 years, primarily in web application development. I’ve had a passion for games from a very young age and continue to play on PC, mobile and consoles today. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): The Onboarding Phase in a Game for Text Labelling: Comparing the Effect of Animated vs. Textual Onboarding on Player Experience and Accuracy Gamifying language resource acquisition Progression in a language annotation game with a purpose Incremental game mechanics applied to text annotation Making text annotation fun with a clicker game The design of a clicker game for text labelling Crowdsourcing and aggregating nested markable annotations Testing TileAttack with Three Key Audiences Experiment-driven development of a gwap for marking segments in text Metrics of games-with-a-purpose for NLP applications Testing game mechanics in games with a purpose for NLP applications TileAttack Novel Incentives for Phrase Detectives Themes Player Research - 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. Email mike@possibilityspace.org Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Design & Development Game AI - Previous Next

< Back Evgenii Kashin University of York iGGi Alum Evgenii, a Computer Science enthusiast, began crafting games in school using the Warcraft3 editor. He spent five years as a Machine Learning Engineer, excelling in computer vision and graphics. His work at Snap included creating engaging lenses and researching 3D object capturing. An ECCV2020 article on face manipulation, with over 100 citations, is a testament to his prowess. Away from work, he enjoys bouldering, hiking, racing, and gaming. My research is dedicated to establishing a cost-effective approach for creating and generating 3D scenes for game development, a critical aspect of modern VR/AR applications. Harnessing the potential of generative visual content, I aim to develop algorithms capable of realistically completing 3D scenes from a few images. This could revolutionize the entertainment and creative industries, particularly game development. Picture having only a couple of images from your favourite film and envisioning the entire scene. Such technology can enhance the efficiency of 3D artists, democratize game development, and serve as entertainment in itself. Currently, I am developing an algorithm to achieve this goal. The proposed solution employs a general pretrained text-to-image model for supervision, with a NeRF 3D representation of the scene. The central concept involves iterative outpainting, where each iteration updates the NeRF weights. Email evgenii.kashin@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor Dr William Smith Featured Publication(s): The Sky's the Limit: Relightable Outdoor Scenes via a Sky-Pixel Constrained Illumination Prior and Outside-In Visibility Stylegan2 distillation for feed-forward image manipulation Themes Creative Computing - Previous Next

< Back Dr Claudio Guarnera University of York Supervisor You can get more out of your site elements by making them dynamic. To connect this element to content from your collection, select the element and click Connect to Data. Once connected, you can update it anytime without affecting your design or updating elements by hand. Add any type of content to your collection, such as rich text, images, videos and more, or upload it via CSV file. You can also collect and store information from your site visitors using input elements like custom forms and fields. Be sure to click Sync after making changes in a collection, so visitors can see your newest content on your live site. Email claudio.guarnera@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing - Previous Next

< Back Dr Ben Kirman University of York iGGi Training Coordinator Supervisor Available to supervise non-iGGi students for 2024 intake Ben is a Senior Lecturer (Associate Prof) in Interactive Media at the University of York, who has over 20 years' experience as a creative technologist. Since his first programming job fixing Y2K bugs (you're welcome), he has worked with dozens of organisations, large and small, in design and prototyping playful experiences. His research uses game design and playful design as a way to explore the complex effects of emerging technologies through novel and unexpected interactions and experiences. Most often, this is through the design and development of games, digital/physical prototypes, and design fictions. Ben has applied this in topics ranging from immersive theatre, dog technology, non-league football, radical cycle delivery, and time travelling robots, to educational games, esports, new situationism and magic. The unifying theme is play – as a topic of study, a way of working, for research insight, and as expression or output in games or playful experiences. This work, especially the more bizarre stuff, has often been covered by traditional media, including the BBC, New Scientist, Wired, The Guardian, TIME, Metro, the New York Times, and Your Cat magazine. Ben is keen on supervising students with strong creative drives, with an interest in making, design, experimentation, and a broad perspective on games and play. This might be a project about playful props in immersive theatre, or a project about context in locative and site-specific games, or any other project that looks to explore new possibilities and new implications of emerging technology through the lens of play. Research themes include: Game Design Applied Games Computational Creativity Sports with an E and without an E Player Experience Email ben.kirman@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing Design & Development Esports Player Research - Previous Next