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< Back Prof. Alex Wade University of York Supervisor Alex Wade is a psychologist working in the field of human cognitive neuroscience. He uses a combination of structural and functional brain imaging, electrophysiology, psychophysics and big data analysis to ask how we see, solve problems and make decisions. His most recent work in the domain of video games focuses on what we can learn about global cognitive health and player personality from the analysis of large MOBA datasets in collaboration with Riot games (League of Legends). He is particularly interested in supervising students with a psychology or neuroscience background in the areas of: Using commercial video games to measure cognition and personality How the brain responds to solo- and group gameplay Can we use video games to monitor and modify real-world cognition, behaviour and mental health Research themes: Game Analytics Games with a Purpose Computational Creativity E-Sports Player Experience The neuroscience of gaming Email alex.wade@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing Esports Game Data Player Research - Previous Next

< Back Prof. Richard Bartle University of Essex iGGi Co-Investigator Supervisor Richard Bartle is a renowned pioneer in game design and research. He co-wrote the first virtual world, MUD ("Multi-User Dungeon") in 1978, and has thus been at the forefront of the online games industry from its very inception. He is an influential writer on all aspects of virtual world design, development, and management. As an independent consultant, he has worked with many of the major online game companies in the U.K. and the U.S. over the past 30 years. His 2003 book, Designing Virtual Worlds , has established itself as a foundation text for researchers and developers of virtual worlds alike. His Player Type theory is taught in game design programmes worldwide (he appears in examination questions!). His interests are directed mainly virtual worlds, particularly Massively Multiplayer Online Role-Playing Games (MMORPGs, or MMOs), but cover all aspects of game design. He is keen to see AI used for non-player characters in MMOs (his PhD is in AI), and his current work considers the long-term moral and ethical implications of this. They’re maybe not what you might think they were at first glance… Email rabartle@essex.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Game AI Player Research - Previous Next

< Back - Meet me @ Develop:Brighton 2026 - Nicole Levermore University of York iGGi PG Researcher Available for placement Nicole's academic background is within Neuroscience, having achieved BSc Neuroscience and Psychology, MSc Translational Neuroscience and an MPhil in Auditory Neuroscience. Outside of her research interests, she enjoys playing video games, hiking and playing the cello. A description of Nicole's research: Video games have enormous potential for research on cognition and mental health. In my project, I will use video games to perform basic research into a common psychiatric disorder (ADHD), paving the way for improved diagnosis, monitoring and therapy. ADHD is typically diagnosed in childhood and is characterised by failures of attentional state maintenance. This project involves using cutting-edge neuroimaging techniques to investigate how subjects with and without ADHD switch between attentional states (for example, ‘engagement’ and ‘flow’) while playing a cognitively engaging video game. The ultimate goal is to use video games to understand how mental health impacts people’s ability to focus on cognitively demanding tasks and, potentially, to develop therapeutic intervention. Email nicole.levermore@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Alex Wade Themes Accessibility Design & Development Immersive Technology Player Research https://www.youtube.com/watch?v=gRFe1EOPW_4 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 Prof. Sebastian Deterding iGGi Responsible Innovation Lead Supervisor Sebastian Deterding is a designer-researcher working on playful, gameful, motivational, and eudaimonic design. His work asks how we might re-design the socio-technical rule systems we live in to enable a good life for all. He is founder of the Gamification Research Network, and co-editor of The Gameful World (MIT Press, 2015). An internationally recognised leader of gamification research, he is frequently invited to keynote and speak at venues like Lift, Interaction, GDC, Games Learning Society, Google, IDEO, and MIT, and his work has been covered by The Guardian, The New Scientist, the Los Angeles Times, arte, and EDGE Magazine among others. As a senior research fellow at the Digital Creativity Labs, Sebastian works on the intersection of AI, machine learning, and design for augmented creativity: how can we create systems that learn to automatically adapt and serve optimally engaging content to users, and serve optimally supportive design suggestions and tutorials to creators? He is particularly interested in supervising students with a design, HCI, or behavioural sciences background on the following topics: understanding and designing for uncertainty, curiosity, and epistemic emotions in games applied games for decarbonisation and climate adaptation design for behaviour change Self-determination theory and games Research themes: Game Design Games with a Purpose Computational Creativity Player Experience Gamification Email sebastian.deterding@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing Design & Development Player Research - Previous Next

< Back Dr Michael Saiger University of York iGGi Alum Michael is a game design researcher investigating how we engage players (particularly young people) in the design and development of applied games. He has facilitated co-design workshops across health and education research, designing solutions to research problems. Most recently, he was employed as a game design researcher on an ESRC funded project to design and evaluate a game for teacher recruitment. A description of Michael's research: Michael's research involves the facilitation and involvement of children and young people in the design of mental health games. Through their research, they have co-designed mental health prototypes and explored the factors to impact participation and engagement. Their research has highlighted how there are facilitation barriers and shifts in participant preferences towards how young people want to interact during co-design. Email michael.saiger@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Joe Cutting Prof. Sebastian Deterding Dr Lina Gega Featured Publication(s): "SAM"-School Attachment Monitor for the Assessment of Attachment in Children aged 4-8 Digital innovations in teacher Recruitment: An experimental study Exploring player experience factors for designing persuasive recruitment games Use of Technology in Brief Interventions How Do We Engage Children and Young People in the Design and Development Of Mental Health Games Children and Young People's Involvement in Designing Applied Games: Scoping Review What Factors Do Players Perceive as Methods of Retention in Battle Royale Games? Themes Applied Games Design & Development Player Research - Previous Next

< Back Dr Adrián Barahona-Ríos University of York iGGi Alum From 2018 and in collaboration with Sony Interactive Entertainment Europe, Adrián is researching strategies to increase the efficiency in the creation of procedural audio models for video games by using DSP and machine learning approaches. His main research interests, applied to the synthesis of sound effects, are generative deep learning (GANs, RNNs and VAEs) to synthesise raw audio and machine learning to find out the best parameters for a synthesiser to generate a target sound. Adrián has been enthusiastic about sound and more specifically about game audio since he began his studies. By the time he completed an HND in Creative Media Production in Madrid, he started working in the industry as a recording engineer in an ADR studio for the Spanish localisation of video games (such as Fallout 4, Until Dawn or Just Cause 3). He moved from Spain to the UK in 2015 to take a BA (top-up) in Music Production at the Southampton Solent University and an MSc in Sound Design at the University of Edinburgh immediately after. During that journey, he focused his career in procedural audio and explored ways to create models for interactive applications by using different techniques. Email adrian.barahona.rios@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor Dr Tom Collins Featured Publication(s): RESP: Reference-guided Sequential Prompting for Visual Glitch Detection in Video Games Deep Learning for the Synthesis of Sound Effects NoiseBandNet: controllable time-varying neural synthesis of sound effects using filterbanks Sonifying energy consumption using SpecSinGAN SpecSinGAN: Sound Effect Variation Synthesis Using Single-Image GANs Synthesising Knocking Sound Effects Using Conditional WaveGAN Perception of emotions in knocking sounds: An evaluation study Perceptual Evaluation of Modal Synthesis for Impact-Based Sounds Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Themes Creative Computing Game Audio - Previous Next

< Back Prof. Damian Murphy University of York Supervisor Damian Murphy is Professor in Sound and Music Computing at the Department of Electronic Engineering AudioLab, University of York, where he has been a member of academic staff since 2000, and is the University Research Theme Champion for Creativity. He started his career in the Performing Arts Department at Harrogate College and has previously held positions at Leeds Metropolitan University and Bretton Hall College. His research focuses on virtual acoustics and he has published over 130 journal articles, conference papers and books in the area. He is a member of the Audio Engineering Society, a Fellow of the Higher Education Academy, and a visiting lecturer to the Department of Speech, Music and Hearing at KTH, Stockholm. Prof. Murphy is also an active sound artist and the Director of the £15m XRStories Creative Industries R&D Partnership exploring interactive and immersive storytelling for the UK’s creative and cultural sectors. He is interested in supervising students with interests in sound design, acoustics and audio signal processing and with a particular focus on: Interactive and immersive audio environments for real-time systems Room acoustics simulation and auralisation Assessment of immersive audio content for gameplay and competitive advantage Interactive/immersive audio storytelling Acoustic scene classification using spatial and spectral feature Audio for immersive environments. Research themes: Game AI Game Audio and Music Games with a Purpose Player Experience Email damian.murphy@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game Audio Immersive Technology - Previous Next

< Back Dr Daniel Hernandez University of York iGGi Alum With the games industry as his target, Daniel Hernandez’s main research objective is to design and implement algorithms that, without any prior knowledge, generate strong gameplaying agents for a wide variety of games. To tackle this “from scratch” learning, he uses, and contributes to, the fields of Multiagent Reinforcement Learning, Game Theory and Deep learning. Self-play is the main object of study in his research. Self-play is a training scheme for multiagent systems in which AIs are trained by acting on an environment against themselves or previous versions of themselves. Such training scheme bypasses obstacles faced by many other training approaches which rely on existing datasets of expert moves or human / AI agents to train against. Daniel’s hope is that further development in Self-play will allow game studios of all sizes to generate strong AI agents for their games in an affordable manner. A storyteller by nature, Daniel has a strong track record of outreach through talks and workshops both in the UK and internationally. By sharing his journey, insights and discoveries he hopes to both inspire and instruct students, researchers and developers to realise the potential that Reinforcement Learning has to improve the games industry. His passionate work on Machine learning goes beyond crafting strong gameplaying agents. He sees the potential of using AI to simplify and automate a wide range of tasks in the games industry. He has led successful projects which used machine learning aimed at automating multiagent game balancing to alleviate the burden of manual game balancing. Daniel received an MEng in Computing: Games, Vision & Interaction from Imperial College London. Wanting to combine the power of AI and the creativity of videogames, Daniel began a PhD journey to explore the misty lands of Multi Agent Reinforcement Learning (MARL). Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): A comparison of self-play algorithms under a generalized framework A generalized framework for self-play training Metagame Autobalancing for Competitive Multiplayer Games Themes Game AI Player Research - Previous Next

< Back Remo Sasso Queen Mary University of London iGGi PG Researcher I hold a BSc and MSc in Artificial Intelligence at the University of Groningen (NL) and am currently a PhD student at the Queen Mary University of London under the supervision of Paulo Rauber. In addition to my academic work, I have worked as a Machine Learning engineer, and am currently the Head of AI at xDNA, an AI/Cybersecurity-based start-up from the Netherlands. Here I'm leading the initiative Project Aletheia, where we develop AI-driven tools to optimize the workflow of professional fact-checkers, with the overarching goal of ensuring information integrity in the world. Foundation World Models and Foundation Agents for Reinforcement Learning My research focuses on developing reinforcement learning algorithms that are both scalable and sample-efficient through Bayesian methods and model-based approaches, recently with a particular emphasis on Large Language Models (LLMs). My previous research focused on principled, efficient and scalable exploration algorithms for reinforcement learning, e.g. Poster Sampling for Deep Reinforcement Learning (ICML 2023), where we developed a reinforcement learning algorithm that can be considered state-of-the-art in Atari games. Currently I'm particularly interested in the integration of LLMs in the reinforcement learning framework, both as decision-making agents and simulators. My current research, called "Foundation World Models and Foundation Agents for Reinforcement Learning" investigates this integration in-depth and shows that large models show significant potential in various reinforcement learning tasks, ranging from decision-making in stochastic environments to serving as world models. Email r.sasso@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Paulo Rauber Featured Publication(s): Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds On the Limits of Tabular Hardness Metrics for Deep RL: A Study with the Pharos Benchmark VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts Making Connections: Neurodevelopmental Changes in Brain Connectivity after Adverse Experiences in Early Adolescence Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning Simultaneous multi-view object recognition and grasping in open-ended domains Posterior Sampling for Deep Reinforcement Learning Themes Game AI - Previous Next

< Back Prof. Marian Ursu Goldsmiths Supervisor Marian Ursu has a first degree in Computer Science, a PhD in Artificial Intelligence, and has worked over the past twenty years in the development of new forms of mediated expression and interaction, in the space of convergence of digital technology with creative practice. He worked at Goldsmiths, University of London, pioneering “creative computing”, a term denoting a fundamental link between digital technologies, the arts and media. At York, he led the development of the Interactive Media subject area in the department of Theatre Film Television and Interactive Media, inherently interdisciplinary, building on Computer Science, User Experience Design, Media Practice and Cultural Studies. He is a co-founder and the Director of the Digital Creativity (DC) Labs ( https://digitalcreativity.ac.uk ), a centre of excellence in impact-driven research in creativity for games, narrative media and the rich space of media convergence that lies in between, and Co-Director of XR Stories ( https://xrstories.co.uk ), a creative industries partnership working across film, TV, games, media arts, heritage, advertising and technology to champion a new future in storytelling, in which he leads on Research and Development. His personal research is situated in the area of narrative experiences in scree media – shared screens (film, TV), personal screens (games, social media), stories in VR, XR narrative experiences – drawing from and building on established narrative art-forms and media including film and TV, radio, theatre, and opera. One of his key research objective is to explore the creative process that emerges in dialogue between humans and machines (AI). On one hand, this is necessary for the authoring of more complex narrative experiences that truly exploit the affordances of interactive and immersive digital media technologies. On the other hand, this is a yet poorly untapped space of opportunities, potentially conducive to significant findings. He is particularly interested in supervising students interested in exploring creativity in dialogue with AI and/or the development of novel narrative experiences, in topics including: Conceptualising the space of interactive storytelling Developing authoring tools and techniques for interactive storytelling Creating new forms of narrative engagement Analysing the concept of creativity in interactive media which emerges in conversation with AI Research themes: Narrative Games; Narrative Experiences Storytelling with Convergent Media Object-Based Media Computational Creativity Live mediated experiences (performance, sports, esports) Entertainment media and mental health Games and Theatre Email marian.ursu@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Player Research - Previous Next

< Back Dr Patrik Huber University of York Supervisor Patrik Huber is a researcher, developer and entrepreneur, working on 3D face reconstruction and face analysis in images and videos using 3D face models. He is a Lecturer (Assistant Professor) in Computer Vision in the Department of Computer Science of the University of York, UK, and he’s the Founder of 4dface.io, a small start-up specialising in 3D face models and realistic 3D face avatars for professional applications. His research is focused on computer vision, in particular, he is interested in the question of how to robustly obtain a metrically accurate, pose-invariant 3D representation of a face from 2D images and videos. He is interested in face tracking, 3D face modelling, analysis and synthesis, metrically accurate 3D face shape reconstruction, inverse rendering, and combining deep learning with 3D face models. Patrik is particularly interested in supervising students with a strong background and interest in computer vision, machine learning, computer graphics, and modern C++/Python, on topics related to creating 3D face avatars of players for immersive playing and social experiences , and using face analytics for professional e-sports . Research themes: 3D face avatars for games AR/VR Serious games and social interaction Immersive 3D player experiences Game Analytics Games with a Purpose E-Sports Email patrik.huber@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Esports Game Data Immersive Technology Player Research - Previous Next