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< 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

< Back Ruizhe "Jay" Yu Xia Queen Mary University of London iGGi PG Researcher Available for placement Ruizhe has bachelor degrees in Mathematics and Physics and a master's degree in Artificial Intelligence. After a short time as a consultant he decided to pursue research into what got him into AI in the first place: game agents. He enjoys games of all kinds, but strategy and RPG games occupy a sizeable portion of his collection. AI agents that perform with superhuman skill in increasingly complex games have appeared in recent years, but these agents are not always useful to game developers. Players within a game exhibit significant variance in their skill levels and play styles. Therefore, game agents with similar variance would better represent the player base. The research Ruizhe proposes will focus on three areas: measuring skill and play styles, developing game agents that mimic a range of human play styles and skill levels, and making these agents human-like. Upon successful completion, this research will improve the game development process via automated playtesting and will enable the development of AI agents that are more engaging and interactive. Email r.yuxia@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Simon Lucas Dr Jeremy Gow Themes Game AI Game Data - Previous Next

< Back Prof. Massimo Poesio Queen Mary University of London Supervisor Massimo Poesio is a cognitive scientist whose primary field is Computational Linguistics / Natural Language Processing. He is interested in the interdisciplinary study of language processing using evidence from computational modelling, corpora, psychological studies, and neuroscience; specific interests include computational models of anaphora resolution (coreference); the study of disagreement on language interpretation through the creation of large corpora containing multiple judgments (an area in which he pioneered the use of games-with-a-purpose with the development of Phrase Detectives, http://www.phrasedetectives.org ); the interpretation of verbal and non-verbal communication in interaction; and the study of conceptual knowledge using a combination of methods from human language technology and neuroscience. He has also been involved in a number of projects applying NLP methods to real life problems, such as detecting deception online, or identifying human rights violations reports in social media. He holds a European Research Council grant on identifying disagreements in language through Games-With-A-Purpose, DALI and is a co-founder of the open access journal Dialogue and Discourse . Using conversational agents in games Applying games to label data for AI Research themes: Game AI Game Design Games with a Purpose Email m.poesio@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Game AI - Previous Next

Partners (All) iGGi is a collaboration between Uni of York + Queen Mary Uni of London: the largest training programme worldwide for doing a PhD in digital games. iGGi Partners We are excited to be collaborating with a number of industry partners. iGGi works with industry in some of the following ways: Researcher Industry Knowledge Exchange - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the researcher and their industry partner. Researcher Sponsorship - for some of our researchers, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - iGGi industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! Check out our Industry Info page here to see these types of collaboration described in more detail. There are many ways for our industry partners to work with iGGi. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. 22 Cans AI and Games Autistica BT BetaJester Limited BiG BlitzGame Studios Bossa Studios British Broadcasting Corporation BBC British Games Institute (BGI) CBT Clinics COMIC Research Carnegie Mellon University Cooperative Innovations Creative AI Creative Assembly Die Gute Fabrik Digital Catapult Dubit Limited Durham University ESL UK Electronic Arts (EA) Enigmatic Studios Falmouth University Fluttermind LLC

< Back Igor Dall'Avanzi Goldsmiths iGGi Alum Creation of accessible tools for the use of procedural audio in video games The aim of this research is to investigate and provide new tools to developers for the use of procedural audio into video games. Procedural approaches could address different issues that commonly afflict game audio. In music, generative systems are not only less repetitive, but offer more adaptability as well. For what concerns sound design, they can provide not only variety, but stronger and more realistic support to the interaction with the game world; interaction that is becoming even deeper with the advent of VR Yet, these methods still need improvement on different sides. One is the level of quality that procedural audio needs to achieve to compete with the current aesthetic established by the use of rendered sounds and music in the media. Another is the additional amount of work required by the CPU to render the assets on runtime, and its variable cost). Finally, there is a general lack of user-friendly tools, to link common programming languages for audio to game engines. Software like MaxMsp, Pure Data or SuperCollider is used to design generative audio systems. A more accessible integration of these software could promote generative approaches among sound designers and composers in the field, that today have instead access to tools mainly designed to be used with rendered assets. My plan is to bring on research first by focusing on how a higher degree of quality could be addressed, exploring tools like the above mentioned MaxMsp, Pure Data, low level solutions, and machine learning algorithms. Primary research will be run to confront procedurally generated audio content with rendered one; to understand its impact on the player, and the level of quality needed to deliver a satisfactory experience. The creation of more accessible interfaces and tools dedicated to implement procedural audio in video games will be investigated and undertaken. I like to make noises of all sort and to play with them. For this reason I graduated in Music Production in 2016 and, at the moment of writing, I am finishing my final project for an MSc in Sound and Music for Interactive Games at Leeds Beckett University. Composer and sound designer, in the last year I have been focusing on audio implementation and programming, and I am currently exploring machine learning approaches for procedural audio. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game Audio Player Research - Previous Next

< Back Dr Raluca Gaina Queen Mary University of London iGGi Outreach Coordinator iGGi Alum + Supervisor Dr Raluca D. Gaina is currently a Lecturer in Game AI at Queen Mary University of London, where she obtained her Ph.D. in Intelligent Games and Games Intelligence in May 2021 (in the area of rolling horizon evolution in general video game playing). She completed a B.Sc. and M.Sc. in Computer Games at the University of Essex in 2015 and 2016, respectively. In 2018, she did a 3-month internship at Microsoft Research Cambridge, working on the Multi-Agent Reinforcement Learning in Malmo Competition (MARLO). She was the track organiser of the Two-Player General Video Game AI Competition (GVGAI) 2016-2019 and was the Vice-Chair for Conferences of the IEEE CIS Games Technical Committee in 2020. Her research interests include general video game playing AI, evolutionary algorithms, and tabletop games. Email r.d.gaina@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games The n-tuple bandit evolutionary algorithm for automatic game improvement Population seeding techniques for rolling horizon evolution in general video game playing Automatic Game Tuning for Strategic Diversity Analysis of vanilla rolling horizon evolution parameters in general video game playing General video game for 2 players: Framework and competition General Video Game Artificial Intelligence Playing with evolution Rolling horizon evolutionary algorithms for general video game playing Self-adaptive rolling horizon evolutionary algorithms for general video game playing Rolling Horizon NEAT for General Video Game Playing Frontiers of GVGAI Planning Planning in GVGAI Efficient heuristic policy optimisation for a challenging strategic card game General video game artificial intelligence Optimising level generators for general video game AI 'Did you hear that?' Learning to play video games from audio cues Project Thyia: A forever gameplayer Tackling sparse rewards in real-time games with statistical forward planning methods General video game ai: A multitrack framework for evaluating agents, games, and content generation algorithms The Multi-Agent Reinforcement Learning in Malm\" O (MARL\" O) Competition VERTIGØ: visualisation of rolling horizon evolutionary algorithms in GVGAI General win prediction from agent experience League of Legends: A Study of Early Game Impact Self-adaptive MCTS for General Video Game Playing The 2016 two-player gvgai competition Introducing real world physics and macro-actions to general video game AI Rolling horizon evolution enhancements in general video game playing Learning local forward models on unforgiving games Themes Game AI - Previous Next

< Back - Meet me @ Develop:Brighton 2026 - Tamsin Isaac University of York iGGi PG Researcher Available for placement Tamsin has been a lifelong gamer ever since receiving her first Game Boy and has long been fascinated by how people engage with games emotionally, socially, and behaviourally. She joined the iGGi CDT in 2023 after completing a BSc and MSc in Psychology at the University of Plymouth, where she developed a growing interest in player motivation, disengagement, and live-service game design. Her PhD research focuses on limited-time events (LTEs) in digital games—temporary content designed to encourage engagement and re-engagement in live-service games. Through this work, she explores how LTEs shape player behaviour, routine, anticipation, disengagement, and return play across platforms and genres. Tamsin’s research combines large-scale content analysis with qualitative diary-and-interview methods to investigate both the structure and lived experience of LTEs. She is currently developing a cross-platform taxonomy of LTEs using data from over 2,600 Steam and Google Play games, alongside player-focused research exploring how individuals decide whether events are “worth” participating in during everyday play. Her work aims to support more ethical, sustainable, and player-friendly approaches to live-service game design by helping researchers and developers better understand how event structures influence player experience and long-term engagement. She is open to collaboration opportunities with game studios interested in live-service systems, player behaviour, engagement design, and event analysis using player data or design insights. When not researching or analysing games, Tamsin enjoys baking, reading, playing cosy indie games, and quietly grinding dailies. Email tamsin.isaac@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Themes Applied Games Design & Development Player Research https://www.youtube.com/watch?v=n32ngtGYNQ8 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 Mariana Lopez University of York Supervisor Dr Mariana Lopez is a researcher in the field of sound design. She works on two main fields: accessibility and heritage. Her work on accessibility focuses on how sound design can be used to create accessible experiences for film and television audiences with sight loss, providing an alternative to traditional Audio Description practices. She was the Principal Investigator of the project Enhancing Audio Description funded by the AHRC. In the field of heritage, she focuses on acoustical heritage, by exploring how acoustic measurement techniques, computer modelling and the recreation of soundscapes can help us understand the sonic experiences of our ancestors. She was the Principal Investigator of the British Academy-funded project – The Soundscapes of the York Mystery Plays. Related to these fields she is supervising and has supervised projects in the field of mental health in connection to the creative arts; interactive installations; serious gaming and its impact on sustainability; accessibility and gaming; and sound design in participatory theatre, among others. Research themes: Game Audio and Music Games with a Purpose Sound and accessibility Equality and social justice Acoustical heritage Sound installations Email mariana.lopez@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Game Audio - Previous Next

< Back James Gardner University of York iGGi PG Researcher I am a third-year PhD student at The University of York, specialising in computer vision and machine learning for 3D scene understanding. Supervised by Dr William Smith, my research focuses on neural-based vision and language priors in inverse rendering and scene representation learning. I'm particularly interested in neural fields, generative models, 3D computer vision, differentiable rendering, geometric deep learning, multi-modal models, and 3D scene understanding in general. My research has been recognised with publications at prestigious conferences including NeurIPS and ECCV. Currently, I am working as a research fellow on the ALL.VP project, funded by BridgeAI and Dock10, developing relightable green screen performance capture using deep learning and inverse rendering techniques. This work aims to provide greater creative control to film and TV productions without requiring expensive LED volumes or post-production. I hold an MEng in Electronic Engineering from The University of York, for which I was awarded the IET Prize for outstanding performance and the Malden Owen Award for the best-graduating student on an MEng programme. A description of James' research: My research lies at the intersection of computer vision, machine learning, and 3D scene understanding, with a particular focus on neural-based approaches and the integration of vision and language priors. My work spans a range of topics including neural fields, generative models, differentiable rendering, and geometric deep learning. A key theme in my research is the use of 3D inductive biases for inverse rendering, addressing challenges such as illumination estimation, albedo/geometry disentanglement, and shadow handling in complex outdoor scenes. I've made contributions in creating a rotation-equivariant neural illumination model and spherical neural models for sky visibility estimation in outdoor inverse rendering. Additionally, my work extends to learning rotation-equivariant latent representations of the world from 360-degree videos, aimed at advancing the field of 3D scene understanding and developing models with an understanding of core physical principles such as object permanence. Through my research, I aim to build computer systems capable of deeply comprehending the 3D world, utilising self-supervised, generative, and non-generative approaches to push the boundaries of what's possible in computer vision and scene representation learning. Email james.gardner@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): The Sky's the Limit: Relightable Outdoor Scenes via a Sky-Pixel Constrained Illumination Prior and Outside-In Visibility Themes Game AI - Previous Next

< Back Dr Guifen Chen Queen Mary University of London Supervisor Dr Guifen Chen is a Lecturer in Neurobiology at QMUL. Her work focuses on the neuronal basis of multisensory integration, spatial cognition and memory. Her lab uses state-of-the-art techniques such as immersive virtual reality and in vivo electrophysiological/probe recording in mice. Her research is currently supported by funding from BBRSC and the Royal Society. Dr Chen completed her undergraduate studies in both biology and computer science at East China Normal University in China. She then pursued PhD in neuroscience, conducting research at both East China Normal University and Boston University in the USA. Following that, she undertook postdoctoral research at University College London in the UK. Her work has been published in high-impact journals such as Nature Communications, eLife, and Current biology. Email guifen.chen@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Design & Development Immersive Technology Player Research - Previous Next

The EPSRC Centre for Doctoral Training in Intelligent Games & Game Intelligence (IGGI) is the world's largest PhD research in games programme. The annual IGGI conference showcases students' work. Based at Uni of York & Queen Mary Uni of London, IGGI collaborates closely with 80+ industry partners. Welcome to iGGi !!! We are a group of people doing research in games... Read More Follow us on social media: (if you musk) BiGGi Con 2026 >> REGISTRATION OPEN! - iGGi THEMES - Game AI Game Data Design & Development Immersive Technology Esports Accessibility Creative Computing Game Audio Player Research Applied Games Check out the latest iGGi NEWS 23 April 2026 BiGGi Con 2026 - REGISTRATION NOW OPEN! Don't miss this year's iGGi Conference >> *BiGGi Con 2026* << 15-17 September 2026 at Queen Mary University of London Click the article for registration details! Read More iGGi GAMES iGGi COMMUNITY PG Researchers Staff Industry Partners Management Team Alumni