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< Back Dr Anne Hsu Queen Mary University of London Supervisor Anne Hsu’s research includes machine learning, artificial agents, natural language processing and learning, human decision making, interaction design, and well-being technology. Her interests include developing interactive systems that use machine learning and understanding of human psychology to improve human behaviour. She is particularly interested in supervising students with a machine learning, design, HCI, or behavioural sciences background on the following topics: understanding and designing for curiosity in games design for behaviour change motivational/educational games Research themes: Game AI Game Design Games with a Purpose Player Experience Gamification anne.hsu@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/anne-showen-hsu LinkedIn BlueSky Github Themes Applied Games Design & Development Esports Player Research - Previous Next

< 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 gavin.kearney@york.ac.uk Email Mastodon https://www.audiolab.york.ac.uk Other links Website https://www.linkedin.com/in/gavin-p-kearney LinkedIn BlueSky Github Themes Accessibility Applied Games Game AI Game Audio - Previous Next

< Back Dr Madeleine Frister University of York iGGi Alum Madeleine joined the IGGI programme in 2020, after obtaining a master’s degree in psychology and cognitive neuroscience from the Friedrich Schiller University in Jena, Germany. Her PhD focuses on how visual characteristics influence gameplay and player experience. In 2021, she co-founded UX studio Vanilla Noir where she works as an independent designer and developer on website, app and game projects. Video games rely heavily on central aspects of human information processing, including perception, attention, and memory. The human mind is severely limited in the amount of information it can process, and a key factor for successful information processing is resisting distraction. Consequently, most user experience guidelines recommend eliminating any unnecessary information to avoid cognitive overload. Yet, in the case of video games, the presence of task-irrelevant items does not seem to compromise player experience, considering that there is an abundance of popular video games that are very high in visual complexity. On the contrary, inducing demand in the form of perceptual distraction may even be desirable in order to introduce challenge which can in turn increase enjoyment. The current project aims to deepen our understanding of perceptual distraction and its effects on game difficulty and player experience, with a specific focus on perceptual similarity between target and distractor items. mf1255@york.ac.uk Email Mastodon https://vanilla-noir.com Other links Website https://www.linkedin.com/in/madeleinefrister LinkedIn BlueSky Github Supervisors Prof. Paul Cairns Dr Laurissa Tokarchuk Dr Fiona McNab Featured Publication(s): Advancing Methodological Approaches in Affect-Adaptive Video Game Design: Empirical Validation of Emotion-Driven Gameplay Modification Perceptual Distraction and its Effects on Difficulty and User Experience in Digital Games An appraisal-based chain-of-emotion architecture for affective language model game agents Examining the effects of video game difficulty adaptation on performance and player experience Examining the influence of perceptual distraction on performance in a working memory game A data-driven approach for examining the demand for relaxation games on Steam during the COVID-19 pandemic Themes Design & Development 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. r.sasso@qmul.ac.uk Email https://remosasso.github.io/ Mastodon Other links Website https://www.linkedin.com/in/remo-sasso-b9837a1ba/ LinkedIn BlueSky https://github.com/remosasso Github Supervisor: Dr Paulo Rauber Featured Publication(s): 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 Dominik Jeurissen Queen Mary University of London iGGi PG Researcher Hey, I'm Dominik Jeurissen, and I'm passionate about both software engineering and machine learning, with a particular interest in fully autonomous agents that do not rely on absurd amounts of data. My focus areas include reinforcement learning, unsupervised learning, and the emerging capabilities of large language models. I earned my MSc in Artificial Intelligence from Maastricht University and my BSc in Computer Science with a focus on Applied Mathematics from RWTH Aachen. During my undergraduate studies, I worked as a software engineer at INFORM GmbH, contributing to their supply management software, add*ONE. A description of Dominik's research: My PhD is a collaboration with Creative Assembly , focusing on researching AI for complex strategy games, such as Total War. With the recent emergence of Large Language Models (LLMs), I’m exploring their potential to enhance game-playing agents. LLMs can instantly recall knowledge on almost any topic (though not without occasional errors), perform basic reasoning, and are easily configured for a wide range of text-based tasks. These abilities make them especially promising for game development, where machine learning agents often struggle due to constantly changing game environments. d.jeurissen@qmul.ac.uk Email https://commandercero.github.io/ Mastodon Other links Website https://www.linkedin.com/in/dominik-jeurissen/ LinkedIn https://bsky.app/profile/dominikjeurissen.bsky.social BlueSky https://github.com/CommanderCero Github Supervisors: Dr Diego Pérez-Liébana Dr Jeremy Gow Featured Publication(s): Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Generating Diverse and Competitive Play-Styles for Strategy Games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Automatic Goal Discovery in Subgoal Monte Carlo Tree Search Game state and action abstracting monte carlo tree search for general strategy game-playing Portfolio search and optimization for general strategy game-playing The Design Of" Stratega": A General Strategy Games Framework Themes Design & Development Game AI Game Data - 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 damian.murphy@york.ac.uk Email Mastodon https://www-users.york.ac.uk/~dtm3/ Other links Website https://uk.linkedin.com/in/damian-murphy-b272b914 LinkedIn BlueSky Github Themes Creative Computing Game Audio Immersive Technology - Previous Next

< 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 Mastodon Other links Website LinkedIn BlueSky Github Themes Game Audio Player Research - Previous Next

< Back Dr Adam Katona University of York iGGi Alum Adam did his MSc in mechatronics at Budapest University of Technology and Economics. After graduation, he spent two years working on automated driving at Robert Bosch GmbH, during which he got exposed to both the classical and the machine learning approach of creating intelligent agents. Evolutionary computation continues to surprise us by producing creative and efficient designs. However despite our best efforts, artificial evolution had not produced anything ascomplex and interesting as natural evolution. As our hardware is becoming faster and number of cores in our chips increase, the lack of computational power is becoming less of an excuse. It is starting to become more and more obvious that some fundamental component of natural evolution is missing from our simulations. One possible candidate is the evolution of evolvability. Evolution seems to produce organisms which are well suited for further evolution. The goal of my research is to find mechanisms which allows evolution to increase evolvability, and incorporate these in the design of more efficient neuroevolution algorithms.This research is in the intersection of evolutionary computation, evolutionary developmental biology and neural networks. mail.adamkatona@gmail.com Email Mastodon https://adamkatona.net/ Other links Website LinkedIn BlueSky https://github.com/adam-katon Github Featured Publication(s): Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Complex computation from developmental priors Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning Quality Evolvability ES: Evolving Individuals With a Distribution of Well Performing and Diverse Offspring Growing 3d artefacts and functional machines with neural cellular automata Time to die: Death prediction in dota 2 using deep learning Themes Game AI - Previous Next

< Back Zoë O’Shea Goldsmiths iGGi PG Researcher Zoë O’Shea is an Irish freelance games designer and artist, working on her thesis in game design and player psychology. Her previous qualifications include 3D Generalism, and an MA in Digital Game Design and Theory. She is endlessly curious about the meaning and value that technology can bring to the world, exploring the human experience as a core principle of her work. She firmly believes in the importance of creating a more joyful and inclusive world. Zoë has previously worked with a range of clients and companies including A Brave Plan, Surgent Studios, Transport for London (TfL) and LEGO. In 2019, Zoë was awarded a Digital Fellowship from the Royal Shakespeare Company (RSC) in collaboration with Magic Leap. Zoë worked with other creatives for a year to explore the future of theatre and Spatial Computing (Mixed Reality). The programme completed in Feb 2020, through the generous support of Magic Leap, the RSC, their technologists, industry partners, i2 Media Research and the University of Portsmouth. Currently, Zoë is working on completing her thesis while offering consultancy services for games and start-ups looking to expand their knowledge in soft aesthetics, tend & befriend game design and immersive technology. A description of Zoë's research: Tend & Befriend: A New Perspective on Player Psychology in Digital Games Many are familiar with the term "fight-or-flight" - a stress response activated when animals come into conflict with a stressor or threat. Less commonly known is "tend & befriend", an alternative theory of stress response which suggests that engaging with tending and affiliative behaviours under duress can soothe and protect us. This thesis investigates this phenomenon in digital games, with a focus on empirical data and design. Results demonstrate a consistent niche in the games industry for "tend & befriend" centric design and the value in synthesising previous design frameworks to create a intentional and polished experience for players. z.oshea@gold.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/meowmentai/ LinkedIn BlueSky Github Supervisor(s): Prof. Richard Bartle Featured Publication(s): The impact of self-representation and consistency in collaborative virtual environments Themes Design & Development Immersive Technology Player Research - Previous Next

< Back Andrei Iacob University of Essex iGGi Alum Identifying Immersion in games using EEG and other measures (Industry placement at Sony SIE) The project aims to identify markers for immersion in player’s EEG signals. A few steps towards it include designing an experiment that reduces data noise and helps identify time frames for immersion during gameplay, recording EEG data among other “tests” to improve the accuracy of the state localization on a timeline. This research could prove useful for the games industry in a few ways: - it can provide tools for game testing (e.g. which parts of the game are immersive, which parts lack in that aspect) – thus making it easier to improve the game experience across the board; - it could also be used in making real-time adjustments to games (increase / decrease difficulty levels, pace, etc. to enhance the player’s immersion). Although the EEG data is the main focus of the project, it is not the only one. Correlations will be analyzed between different tests and in-game behaviors that should render even more information regarding the player’s state and mindset during gameplay. This information will be just as valuable and perhaps more readily available for widespread use in the near future. Andrei is a keen programmer and gamer. He graduated with a BSc (Hons) in Computer Science from the University of Essex. Andrei’s research interests are in the field of brain- computer interfaces and computer games. His hobbies include programming, gaming, guitar and skiing. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Themes Player Research - Previous Next

< Back Dr Matthew Whitby University of York iGGi Alum Matthew Whitby is a games designer, and player experience academic investigating how games can shape how perspectives on a small or grand scale. In particular, his work considers how we can make the development of perspective challenging processes easier for game developers. Previously, Matthew has published his undergraduate dissertation within the Games Journal, which explored the creation and design of Games Installations. Games that make full use of their surrounding space, and in fact incorporate the real world with its digital counterpart. In addition, he’s worked with Motek Medical, a rehabilitation company based in Amsterdam, where he developed socially focused multiplayer applications. More recently, he attended CHI Play 2019 to present the foundational study of his PhD titled: “One of the Baddies All Along: Perspective Challenging Moments in Games”. He continues to develop this idea forward, while developing games (both digital and table-top) in his spare time. Matthew’s work hopes to answer; how games can challenge a player’s perspective, and if this is a phenomenon that can be intentionally designed for? matt_whitby@hotmail.com Email Mastodon https://www.matt-whitby.com Other links Website https://www.linkedin.com/in/matthew-whitby-b324ab83 LinkedIn BlueSky Github Supervisor(s): Prof. Sebastian Deterding Dr Jo Iacovides Themes Design & Development Player Research - Previous Next

< Back Dr Tom Collins University of York Supervisor Tom runs the Music Computing and Psychology Lab in the Music Department at University of York, and so makes a good supervisor for game audio projects, but he has wider interests in media (e.g., podcasts) and sport (especially football), and in sport how AI can be leveraged to enhance analytics that lead to new insights into, and competitive advantages in, individual and team performance. Tom is internationally recognised for his work in automatic music generation, web systems for music, and information retrieval. His research has been featured by the BBC (BBC Click), The Times, and Financial Times among others. Tom is interested in supervising students who have a background in at least one of the following areas, and who are interested in acquiring knowledge of the others: Data science and machine learning (especially deep learning); One of music, podcasts, or sport; Software engineering (especially full-stack JavaScript development). tom.collins@york.ac.uk Email Mastodon https://tomcollinsresearch.net Other links Website LinkedIn BlueSky Github Themes Esports Game AI Game Audio Game Data Player Research - Previous Next