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< Back Dr Gavin Kearney University of York Supervisor Dr Gavin Kearney is a highly experienced researcher, lecturer and content creator specialising in spatial audio and surround sound. He joined the University of York as Lecturer in Sound Design in January 2011 and was appointed Associate Professor in Audio and Music Technology in 2016. He has written over 60 research articles and patents on different facets of immersive and interactive audio, including real-time audio signal processing, Ambisonics, virtual and augmented reality and recording and audio post-production technique development. He has undertaken innovative projects in collaboration with Mercedes-Benz Grand Prix, BBC, Dolby, Huawei, Abbey Road and Google amongst others. With the latter, he helped define the Google spatial audio pipeline through development of the SADIE binaural filters and decoders used worldwide. He is also an active sound engineer and producer of immersive audio experiences, working to develop new techniques and workflows for immersive music production in collaboration with Abbey Road Studios. He is Vice-Chair of the AES Audio for Games Technical Committee and was Co-Chair of the 2019 AES Immersive and Interactive Audio Conference at York. Gavin is particularly interested in supervising students with an audio background who wish to explore the following areas relating to audio for games Intelligent sound design Virtual Acoustics Spatial Audio Binaural sound Audio for Virtual and Augmented Reality Immersive audio experiences for next gen mobile platforms Ambisonics and spherical acoustics Using audio to enhance player emotional state (as well as projects on health and well-being) Game Audio for therapy Accessibility through Game Audio Email gavin.kearney@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Accessibility Applied Games Game AI Game Audio - Previous Next

< Back Rob Homewood Goldsmiths iGGi Alum Personalised Aesthetics for Games The worldwide games industry is a huge market and as the spectrum of people who spend time playing games increases, there is more and more competition to create games that capture the attentions of a wide audience. Whilst games have been traditionally designed with specific cultural demographics in mind, a game that could dynamically match the cultural values of a range of demographics would maximize its potential market. Robert’s research looks at developing techniques for procedurally generating dynamic game assets that can be viewed as being relevant at a ‘per player’ level. He aims to do this by actively profiling a player’s social networks and building up a picture of the cultural references with which they identify. This knowledge could then be used to create game assets that match an aesthetic the player would likely feel comfortable with, allowing a more flexible decoupling between game mechanics and aesthetic during the design process. Designers could then focus on creating interesting game mechanics that could work in a variety of settings and the system would fill in the aesthetic detail based on the requirements of the individual player at run-time. Having studied in five countries, Robert is currently undertaking a PhD at Goldsmiths, University of London where he is part of the EPSRC funded IGGI (Intelligent Games and Games Intelligence) program. He also holds a Bachelor’s degree in Game Design and Production Management from the University of Abertay Dundee which included a year of studies at the George Mason University Computer Game Design Program. He also spent a year studying Serious Games at Masters level at the University of Skövde in Sweden (which has the longest running Serious Games program in the world). Robert has an active interest in the media arts field and has exhibited his work in three countries. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Player Research - Previous Next

< Back Dr Kyle Worrall University of York iGGi Alum Available for post-PhD position Kyle is a final-year PhD researcher at the Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI) at the University of York, where his work centers on pioneering deep learning-driven music tools for video game composers. In addition to his research, Kyle is a Lecturer in Games Programming at Edge Hill University, where he encourages the next generation of game developers to appreciate the critical role of audio in interactive experiences. Beyond academia, Kyle is the Founder of Cocreative Technology, an ethical AI music startup on a mission to empower musicians with cutting-edge, AI-driven tools that amplify creative expression, combat burnout, and elevate the emotional depth of game soundtracks. Kyle's research explores how deep learning and generative AI can enhance the creative workflow of video game composers, and improve the experience of players by reducing musical repetition. His work spans symbolic music generation, and real-time adaptive music systems, aiming to improve the emotional expressiveness and of game audio. His recent publications focus on deep learning models for interactive music authoring, expressive performance modelling, the ethical considerations in AI-assisted creativity, and the integration of neural networks with procedural music generation in games. By combining symbolic AI and audio signal processing, Kyle develops tools that support composers in ideation, iteration, and adaptive composition, while remaining transparent and musically intuitive. An experienced speaker, Kyle has presented at leading industry events, including Airwiggle's AirCon 2025, Game Sound Con 2024, Audio Dev Con 2024, the Global Arts and Psychology Symposium 2023, the Play Again Symposium 2024, and the Digital Creativity, Industry and Culture Conference 2022. He is also a regular contributor to the IGGI Conference (2020–2024), and has been featured in TechCrunch, Dazed, The Story of the Sound, and The Audio Programmer podcast, as well as featured on a panel with leaders in game audio from Meta and Sony. Email kyle.worrall@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Jon Hook Dr Tom Collins Dr Josh Reiss Featured Publication(s): RenCon Report: Cue-Free Express & Pedal Final Fantasy VII Remake Music Redesign for Evolved Expectations Across Console Generations Considerations and Concerns of Professional Game Composers Regarding Artificially Intelligent Music Technology Comparative evaluation in the wild: Systems for the expressive rendering of music Reflection Across AI-based Music Composition The Ethics of Creative AI Themes Creative Computing Game Audio https://www.youtube.com/watch?v=m5vCJCB2-2A https://www.youtube.com/watch?v=AllYuKKxks8 Previous Next

< Back Dr Andrew James Wood University of York Supervisor I am an interdisciplinary researcher at the University of York. My background is in Mathematical Physics but my interests are now in applying computational and mathematical techniques to interesting problems, mostly in Biology. This includes such topics as collective motion (particularly in interaction networks and the role of noise) and microbiology (particularly in metabolism, industrial biotechnology, spatial structure and plasmid dynamics) as well as modelling naval conflicts and glycosylation. I have a natural interest in games and am interested in the interface between games and science, be that in using games to do, or disseminate, science or in utilising mechanisms and insights from research to inspire games. Research themes: Game Analytics Game Design Games with a Purpose Gamification Email jamie.wood@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Design & Development Game Data - Previous Next

< Back Dimitris Menexopoulos Queen Mary University of London iGGi PG Researcher Available for post-PhD position Dimitris Menexopoulos, also known as Menex, is a versatile music composer, sound designer, audio technologist and multi-instrumentalist from Thessaloniki, Greece, currently based in London, UK. With an academic background in geoscience, electronic production and information experience design, he draws elements from a broad knowledge base across art, science and technology to inform his work. He has worked in film, games, XR, branding, fashion and the automotive sector for more than ten years. He is a full BAFTA member. A description of Dimitris' research: Procedural content generation supports the creation of rich and varied games, but audio design has not kept pace with such innovation. Often the visual aspects of every asset in the scene may be procedurally rendered, yet audio developers still largely rely on pre - recorded samples in order to carry out their tasks. However, much of the information required to determine smooth audio - visual interactions is already included in the game assets. For example, the size, shape, material and movement of assets offer potential types of data that can drive audio algorithms directly. This research explores how available graphics information in the game engine can be used to generate the sound effects produced when objects interact in real - time, by combining the affordances of procedural audio and sonification. Email contact@menex.world Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Josh Reiss Dr Tom Collins Featured Publication(s): Procedural Sonification of Environmental Phenomena for Realistic Sound Design Using texture maps to procedurally generate sound in virtual environments The State of the Art in Procedural Audio Themes Creative Computing Game Audio - Previous Next

< Back James Gardner University of York iGGi PG Researcher Final-year PhD student at the University of York and Co-Founder of pxld.ai, an AI startup for VFX. My research focuses on inverse rendering, scene representation learning, and world models. I previously held a Research Fellowship at the University of York and interned as a Research Scientist at Toshiba. An MEng graduate and IET Prize winner, I contribute to the open source project Nerfstudio and have reviewed for NeurIPS, CVPR, ICCV, ECCV, and BMVC. My work is published in top-tier venues including TPAMI, NeurIPS, CVPR, and ECCV. A description of James' research: My research explores how AI systems can build richer world models from the limited views available in images and video. I study representations that reason beyond the image plane: what lies outside the camera’s view, how light and visibility shape observations, and how future views can be predicted from partial evidence. This work sits at the intersection of computer vision, machine learning, and computer graphics, aiming to learn models that are aware of space, direction, and scene structure. In the long term, it supports more capable systems for understanding, reconstructing, and editing visual worlds, with applications in immersive media, games, VFX, robotics, and augmented reality. 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 Henrik Siljebråt Goldsmiths iGGi Alum Henrik has a background in IT/DevOps and a Masters in Cognitive Science from Lund University. Based on established neurobiological correlates of reinforcement learning (RL), I investigate animal learning and decision making using cognitive modeling techniques, such as probabilistic programming and machine learning. Animals somehow manage to create useful representations of incoming sensory information, representations then used for learning and decision making. How these representations of states of the world are integrated into task structure and models of the world is an open question, which I investigate using behavioural experiments with humans and bumblebees and modelling said behaviour using RL combined with hidden state models for representing states and task structure. The potential findings of these experiments have promise to not only elucidate the workings of the animal brain but also provide valuable contributions to artificial intelligence, where improved models of state representations could vastly improve data efficiency and generalizability over current generation systems. Please note: Updating of profile text in progress Email h.siljebrat@gold.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): On State Representations and Behavioural Modelling Methods in Reinforcement Learning The Effect of State Representations in Sequential Sensory Prediction: Introducing the Shape Sequence Task Towards human-like artificial intelligence using StarCraft 2 Themes - Previous Next

< Back Filip Sroka Queen Mary University of London iGGi PG Researcher Filip is a Computer Science researcher specialising in Game AI. He acquired an Integrated Masters in Computer Science from Queen Mary University of London and is pursuing a PhD in Game AI with iGGi. An avid LEGO collector and investor, Filip brings a unique blend of technical and creative abilities to his work. He is excited about the potential of the Metaverse and is driven by the role of technology in shaping its future. A description of Filip's research: His research explores the integration of Dynamic Difficulty Adjustment (DDA) and Procedural Content Generation (PCG) into VR rhythm games to optimise motor learning and skill acquisition. By leveraging learning theories, the project creates personalised, adaptive training environments. Beyond commercial gaming, this framework demonstrates how adaptive systems can be used to maximise engagement and training efficiency, offering high-value insights for game developers, immersive tech creators, and the digital health and fitness industry. Email f.sroka@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Alena Denisova Dr Laurissa Tokarchuk Dr Jeremy Gow Themes Applied Games Game AI Immersive Technology - 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. Email m.conserva@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Simon Lucas Dr Paulo Rauber Featured Publication(s): Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches ForestCast: Forecasting Deforestation Risk at Scale with Deep Learning Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds Heterogeneous graph neural networks for species distribution modeling Mapping Farmed Landscapes from Remote Sensing On the Limits of Tabular Hardness Metrics for Deep RL: A Study with the Pharos Benchmark 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

< Back Alex Fletcher Queen Mary University of London iGGi Alum Alex Fletcher is a freelance audio engineer and junior game developer working on understanding the perceived flow and player experiences in mobile rhythm games and how a dynamic difficulty adjustment system would improve these experiences. The function of EEG and other biosensors as an additional measurement of player experience is of particular interest as further research in its use as an adaptive system. Other areas of research interest include game-based learning and games with a purpose. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Game Audio Player Research - Previous Next

< Back Prof. Peter Cowling Queen Mary University of London iGGi Director Supervisor Peter Cowling has led teams that have won £45 million for research into games and digital creativity. After decades of experience in novel models and algorithms for AI decision-making, his research is now targeted on finding and promoting promising research directions in AI, games and digital creative technology, to benefit people and wider society. Playful ideas, curiosity and games have a central role! As Principal Investigator, he led the teams which won the grants for IGGI (2014 and 2019) and Digital Creativity Labs (2015). He is a member of the Programme Advisory Board which informs strategy in the Digital Economy area of UK research council funding. He has sat on several research council grant funding prioritisation panels, chairing two. He has presented ideas for the use of games as a tool to influence and understand the human condition at a number of venues, including TEDx and 10 Downing Street. He has published over 100 papers, winning 2 best paper awards at AIIDE. His research technology has over 5 million installs in commercial games – he was invited to talk at GDC about that. He would be interested to supervise students whose research uses games as a tool to gather opinion or promote understanding: to identify research directions and harness the future potential of games, creativity and AI to benefit people and society. He is particularly interested in how games and other curious, creative things can help us to understand a world of complex interacting agents, each living a world created by their own thought (!). Research themes: Research visions for games and AI Game design/development to influence, inform and understand people and society Game AI Email peter.cowling@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Design & Development Game AI - 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