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  • Guilherme Matos de Faria

    < Back Guilherme Matos de Faria University of York iGGi Alum I am a Portuguese student with a background in Artificial Intelligence. In 2016 I started attending video game tournaments and learned to analyse my matches and improve from it. When I did my masters in AI, I noticed that I could join my professional skills and my hobbies together to create something relevant to AI and competitive gaming. A description of James' research: I am looking to better understand which actions and decisions have the biggest impact on the outcome of a game. Currently, I am particularly focused on competitive turn based card games. What are the best players doing to win? How can players adapt to improve their chances of success? These are the questions I am hoping to help answer, giving players a better understanding of the game and how to improve. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

  • Charline Foch

    < 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. Email charline.foch@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link 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

  • Nathan Hughes

    < Back Dr Nathan Hughes University of York iGGi Alum Nathan Hughes is a player experience researcher who focuses on how player make choices within games. Specifically, the work explores open world games such as Skyrim and the Witcher 3, as these games allow players a vast amount of choice with little restrictions on how and when these are made. However, little research has considered these choices, so little is known about how players experience choice in open world games. Therefore, research questions for this work include; why do players choose not to pursue the main quest? What do players choose to do instead? When and how do they make this decision? His background is in psychology, and so asks these questions from a psychological perspective. The aim is to uncover how the process of choosing unfolds, and how this is influenced. In turn, this may allow reflections on how the decision-making process operates - by analysing choices within open world games, a more controlled (but still intrinsically motivating) setting can be studied. Email ngjhughes@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor Prof. Paul Cairns Featured Publication(s): Clinicians Risk Becoming "Liability Sinks" for Artificial Intelligence Understanding specific gaming experiences: the case of open world games The need for the human-centred explanation for ML-based clinical decision support systems Growing Together: An Analysis of Measurement Transparency Across 15 Years of Player Motivation Questionnaires Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units Opening the World of Contextually-Specific Player Experiences No Item Is an Island Entire of Itself: A Statistical Analysis of Individual Player Difference Questionnaires Ethereum Crypto-Games: Mechanics, Prevalence, and Gambling Similarities Themes Player Research - Previous Next

  • Charlie Ringer

    < Back Dr Charles Ringer University of York iGGi Alum Charlie Ringer is a researcher interested in applied Machine Learning with a focus on the ways in which we can use Deep Learning to model various facets of video games streams (e.g. stream highlights, emotional moments, in-game events, various streamer behaviours etc.). As such, his work spans many Machine Learning fields, such as Computer Vision, Affect Computing, and Natural Language Processing. His research has three motivating factors. Firstly, the challenge of how to fuse multi-view stream data (e.g. audio, web-cam footage, game footage, chat) into a single model, especially when considering the challenges of ‘in-the-wild’ data. Secondly, the untapped and bountiful data source that livestreaming represents, especially regarding the way in which streamers play games and interact with their audience. Thirdly, the exciting and emerging field of self-supervised learning which has the potential to utilise this abundance of livestream data. Charlie initially worked in the video games industry working mainly on the Magic: The Gathering - Duels of the Planeswalkers series of games before studying a BSc in Computer Science at Goldsmiths, University of London. After his BSc he joined IGGI, firstly at Goldsmiths and then at York. He was recognised as a finalist for the Twitch Research Fellowship 2019 for his research on livestream data. Email charles.ringer@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Machine Learning with Applications From Theory to Behaviour: Towards a General Model of Engagement Modelling early user-game interactions for joint estimation of survival time and churn probability Time to die 2: Improved in-game death prediction in dota 2 Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data Multi-Modal Livestream Highlight Detection from Audio, Visual, and Language Data Twitchchat: A dataset for exploring livestream chat Multimodal joint emotion and game context recognition in league of legends livestreams Streaming Behaviour: Livestreaming as a Paradigm for Analysis of Emotional and Social Signals Deep unsupervised multi-view detection of video game stream highlights Streaming behaviour: Live streaming as a paradigm for multi-view analysis of emotional and social signals Rolling Horizon Co-evolution in Two-player General Video Game Playing Themes Esports Game AI Game Data - Previous Next

  • Daniel Gomme

    < Back Dr Daniel Gomme University of Essex iGGi Alum Players have underlying expectations of the opponents they play against in strategy games: don't break the rules, provide a sense of tension, be able to communicate plans... AI doesn't always fulfil these. Dan's focus is on finding ways to better fulfil those expectations - and even to overtly change them - in order to improve player experience. With qualitative tools and in-game testing, he's found several concrete design mechanisms that can further that goal. Email daniel.gomme@yahoo.co.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor Prof. Richard Bartle Featured Publication(s): Player Expectations of Strategy Game AI Playing with Dezgo: Adapting Human-AI Interaction to the Context of Play Strategy Games: The Components of A Worthy Opponent Distributed Social Multi-Agent Negotiation Framework For Incomplete Information Games Tools To Adjust Tension And Suspense In Strategy Games: An Investigation Themes Design & Development Game AI Player Research - Previous Next

  • dr-tom-cole

    < Back Dr Tom Cole iGGi Alum + Supervisor Games should be studied as interactive systems, but are more often studied using techniques reserved for non-interactive media. As developers, we are ‘selling ourselves short’, and not exploring the creative and expressive potential of digital games to their fullest. Out of the myriad of affective experiences possible, we generally only design and experience a fraction of what could be offered. Tom hopes to help address this by studying how game mechanics, gameplay systems and control methods can be used and interpreted to create meaning and elicit a wider range of emotional responses than is commonly seen in digital games at present. Broadening and deepening emotional engagement with an emphasis on mechanics and systems. (Industry placement at Bossa Studios) Video games, with their unique properties such as interactivity, agency, control mechanics, feedback loops and gameplay systems, have the potential to impart deep emotional experiences – some already do of course. However, study of this emotional engagement remains lacking. Reliance on techniques and theory appropriated from film, literature and cultural studies yields limited results. There is relatively little understanding of how procedural elements such as control mechanisms and gameplay systems can be leveraged (or synergised with narrative and/or audio-visual elements) for emotional affect. Tom was previously at Supermassive Games where he was a designer on the BAFTA award-winning horror game Until Dawn and artist on Killzone Shadow Fall. Tom got his BSc in Biology with Industrial Experience from Manchester. After teaching science in secondary schools for a while, he decided games were more interesting and got his MA in Digital Games Theory and Design at Brunel. After time at Goldsmiths, University of London and the University for Creative Arts, Rochester, Tom is now Lecturer in Games Development at the University of Greenwich where he teaches games development, design and production. From 2016 to 2024 he led the organisation of Adventurex - the Narrative Games Convention, a sold out international conference which grew from 100 to 650 people during his time leading it. Email tom@tommakesgames.com Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): The History of Nintendo Emotional exploration and the eudaimonic gameplay experience: A grounded theory More than a bit of coding:(un-) Grounded (non-) Theory in HCI Eudaimonia in Digital Games Thinking and doing: Challenge, agency, and the eudaimonic experience in video games "Moments to Talk About": Designing for the Eudaimonic Gameplay Experience Grounded Theory in games research: making the case and exploring the options Emotional and functional challenge in core and avant-garde games The Tragedy of Betrayal: How the design of Ico and Shadow of the Colossus elicits emotion Themes Design & Development Game AI https://www.youtube.com/playlist?feature=share&list=PL_17c-ELEJ5334QRqxhRLnnoX8aNdpHL- - https://www.youtube.com/watch?v=8pe5FfHTk-4 Previous Next

  • Luiza Gossian

    < Back - Meet me @ Develop:Brighton 2026 - Luiza Gossian Queen Mary University of London iGGi PG Researcher Available for placement Luiza is a multidisciplinary researcher, game designer and developer interested in translating real world concepts into engaging game mechanics. Her work explores how games can bridge the gap between serious and entertainment design, combining the strengths of both to tackle difficult topics in new and unexpected ways. As an experienced artist, graphic designer and photographer, Luiza uses her visual skills and psychology background to prototype experimental game designs, design game documentation and craft atmospheric experiences. A description of Luiza's research: Luiza’s work explores alternative approaches to serious games that blend the accessibility and engagement of casual game design with the applied foundations of research-driven game development. Using her project Detachment Undone, an abstract arcade game inspired by the ten stages of genocide, she is investigating how to design games about genocide that break away from traditional, narrative-centric approaches and embrace the ludic potential of games. Drawing on theories of intergroup and cultural psychology, she is exploring how these difficult themes can be expressed through mechanics in engaging, effective and informative ways. Email l.gossian@outlook.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Jo Iacovides Dr Jeremy Gow Themes Applied Games Design & Development - Previous Next

  • Karl Clarke

    < Back - Meet me @ Develop:Brighton 2026 - Karl Clarke Queen Mary University of London iGGi PG Researcher Available for placement Karl Clarke is a PhD researcher focused on how virtual environments influence social interaction. He was born in England, grew up in the Middle East, and returned to the UK for university. He holds a Bachelor's and a Master's degree in Audio Technology. During the COVID-19 lockdown, he began exploring virtual reality after getting access to a headset, which led to a shift in focus toward social VR. He is now part of the Intelligent Games and Game Intelligence (iGGi) doctoral programme, where his research looks at how spatial layouts and group behavior are shaped by virtual environments in free-standing social settings. Outside of his research, Karl runs SONAR, a music group hosted in VRChat that uses social VR for live performance and shared listening experiences. Through this project, he has independently learned game development skills in 3D modelling, scripting, and a small amount of graphics programming. He is currently looking to collaborate with VR studios or social platforms working on immersive and social experiences. Email karl.clarke@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Themes Design & Development Immersive Technology Player Research https://www.youtube.com/watch?v=Ldehhn_LdhA Previous Next

  • Prof Nick Pears

    < Back Prof. Nick Pears University of York Supervisor Nick Pears is a Professor of Computer Vision in York’s Vision, Graphics and Learning (VGL) research group. He works on statistical modelling of 3D shapes, with an emphasis on the human face and head. The Liverpool-York Head Model and the associated Headspace training set has been downloaded by over 100 research groups internationally, with the Universal Head Model being downloaded by 50 research groups. His most recent work with his PhD students has focused on semantic disentanglement of 3D images and how to make autonomous vehicles safer and more trustworthy when using computer vision systems. He is assessor for many PhDs including construction of generative models for novel video content using adversarial deep learning techniques. Email nick.pears@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game AI - Previous Next

  • Dr Jeremy Gow

    < Back Dr Jeremy Gow Queen Mary University of London iGGi Training Coordinator Supervisor Jeremy Gow is a game AI researcher with a focus on computational game design, exploring ways in which AI can help us understand players and games, enhance the game development process, and contribute to the creation of game content. He has been a lecturer at EECS and a member of the Queen Mary Game AI group since 2018. He has a background in artificial intelligence and human-computer interaction research, and a PhD in AI from the University of Edinburgh. He is particularly interested in supervising students with a game development or AI background on the following topics: Automated playtesting and QA AI-based game development tools Modelling player experience AI for the design of agents and procedural generators Computational creativity in games Research themes: Game AI Game Analytics Game Design Computational Creativity Email jeremy.gow@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Design & Development Game AI Game Data - Previous Next

  • Phoebe Hesketh

    < Back Dr Phoebe Hesketh University of York iGGi Alum Phoebe's PhD explored how people learn to play games through gameplay, online media, and community interaction. At the University of York, Phoebe worked on her skills as a researcher by exploring multiple methodologies and disciplines. She built upon her quantitative research skills from Bristol with qualitative research during their PhD including grounded theory and thematic analysis. She took courses in user-centred design and evaluation and designing for accessible player experiences (through AbleGamers). She participated in game jams and game development courses for experience and technical design. She also gave a talk at DEVELOP 2021 communicating and sharing her research and expertise in how players learn to play games to help designers with their onboarding for their games. She originally studied Engineering Mathematics at the University of Bristol which focused on systems and mathematical modelling and simulation, the mathematics and implementation of AI and Machine Learning systems, programming in object-oriented programming languages such as C++ and Java, and developed ray tracers in computer graphics courses. She also worked on projects in linguistics, logistics, computer vision, and physics. Once completing her PhD, Phoebe moved into the games industry as an AI programmer for several years before looking to return to games and player research. She has set up her own company, Take A Mo, that focuses on helping developers analyse their systems and internal systems to maximise access for players in usability, onboarding, accessibility, and representation. She is a currently carving her niche in the industry. Email phoebe@takeamo.co.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Sebastian Deterding Dr Jeremy Gow Featured Publication(s): How Players Learn Team-versus-Team Esports: First Results from A Grounded Theory Study Themes Esports Player Research - Previous Next

  • Dr Josh Reiss

    < Back Dr Josh Reiss Queen Mary University of London Supervisor Josh Reiss investigates transformative technologies focused around audio production and sound design. He has published more than 200 scientific papers (including over 50 in premier journals and 5 best paper awards), and co-authored two books. His research has been featured in dozens of original articles and interviews on TV, radio and in the press. He is a Fellow and former Governor of the Audio Engineering Society. He co-founded the highly successful spin-out company, LandR, and recently formed a second start-up, FXive. He maintains a popular blog, YouTube channel and twitter feed for scientific education and dissemination of research activities. Prof. Reiss has a strong interest in games research, especially procedural audio content generation. Procedural content generation supports creation of rich and varied games, maps, levels, characters and narrative elements. But sound design has not kept pace with such innovation. Often the visual aspects of every object in the scene may be procedurally rendered, yet sound designers still rely on huge libraries of pre-recorded samples. This approach is inflexible, limited and uncreative. An alternative is procedural audio, where sounds are created in real-time using software algorithms. But many procedural audio techniques are low quality, computational, or tailored only to a narrow class of sounds. Machine learning from the sample libraries, to select, optimise and improve the procedural models, could be the key to transforming the industry and creating procedural auditory worlds. He welcomes the opportunity to supervise students interested in this or related topics. Research themes: Procedural Content Generation Game Audio and Music Game AI Game Design Computational Creativity Player Experience Email joshua.reiss@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game AI Game Audio - Previous Next

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