< Back Dr Anna Bramwell-Dicks University of York Supervisor Anna Bramwell-Dicks has an interdisciplinary background which started in Electronics and Music Technology before taking a sideways move to the field of Human-Computer Interaction research. She likes to combine her underlying interest in sound and music with applied psychology and creativity. She is very interested in research involving multimodal interaction (e.g. using audio, haptics, smell and/or proprioception as well as visuals within interfaces) particularly where audio is used to affect user’s behaviour or experiences. She is also very interested in accessibility research and any research in the application area of mental health and mental illness. As a lecturer in Web Development and Interactive Media, based in TFTI, Anna is always interested in work that involves designing and evaluating novel and interesting user experiences, particularly where that leads to the option to create fun, engaging, accessible experiences. She likes to work across a range of application areas ranging from learning environments to e-commerce to escape rooms and cultural exhibits! Anna is keen to work with students who want to design and develop gamified systems to support people with disabilities, physical or mental illness. Or, those who are also interested in multimodal experiences. Research themes: Accessibility Multimodal and multisensory systems Research methods Email anna.bramwell-dicks@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Accessibility Applied Games Design & Development Game Audio Player Research - Previous Next

< Back Dr Ignacio Castro Queen Mary University of London Supervisor Ignacio Castro is Lecturer in Data Analytics at Queen Mary University of London. His work sits at the intersection between economics and networks. His interest spans from online social networks and moderation to the macroscopic evolution of the Internet. He has been an investigator on three major grants that hold over £6 million in funding. His work appears in top tier journals and conferences including Web Conference, ACM SIGCOMM, ACM SIGMETRICS, ACM IMC, ICWSM, and IEEE/ACM Trans. on Networking. He is interested in supervising students with a background in social network analysis, NLP and/or machine learning. Email i.castro@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Game AI Game Data Player Research - Previous Next

< Back Dr Ozan Vardal University of York iGGi Alum Ozan studied undergraduate psychology at the University of Groningen, and holds a master's degree in Performance Psychology from the University of Edinburgh, where he wrote theses on the dynamics of psychological momentum in sport competition and the decision-making of expert applied psychologists respectively. He has long been fascinated with the psychological mechanisms underpinning complex skills, owing to his own background as a classically trained musician and his previous work as a performance psychology consultant with competitive athletes. His primary research interests involve the behavioural and neural factors surrounding human learning and skilled performance. A description of Ozan's research: Ozan views games as behaviourally rich environments for the study of complex skills and human learning. The competitive and immersive nature of games encourages millions of players to develop profound skill over hours, days, and even years of practice. Ozan’s work takes advantage of large data repositories generated by such players to study how different patterns of practice result in differences in learning outcomes. He also uses experimental methods in his work, and is currently using neuroimaging methods (MEG) and modelling techniques to identify how shifts between different behavioural and neural states affect performance as people play Tetris. By using games as a vehicle to study psychology, Ozan aims to develop scalable solutions to studying human learning. He hopes for a future where the science of learning is sufficiently advanced, such that (artificial) trainers can recommend optimised practice schedules for motivated learners, in any performance domain. Please note: Updating of profile text in progress Email ov525@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Using video games to study the acquisition and performance of psychomotor skills Mind the gap: Distributed practice enhances performance in a MOBA game Themes Design & Development Esports 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 Email damian.murphy@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game Audio Immersive Technology - Previous Next

< Back Toby Best Queen Mary University of London iGGi PG Researcher Available for post-PhD position Toby has always held video games as an integral part of his livelihood, ever since catching his first Pokémon on the Game Boy Color. The ever-developing evolution of technology, from the humble NES and R.O.B. preventing the video game market crash in 1983, to the Wii’s motion controls, to augmented and virtual reality today, has been a key inspiration, and one of the reasons why he studied Mathematical Computation at University College London. He also has a keen interest in tabletop roleplaying games, such as Dungeons & Dragons and Pathfinder. His research interests involve the potential of combining roleplaying games' collective storytelling and interactive narrative with the power of artificial intelligence and deep learning. A description of Toby's research: Artificial Intelligence is the field of creating digital agents capable of decision-making and rational thought to fulfil a core goal or aspect. For tabletop and video games, an implemented AI would attempt to ‘solve’ the game by finding optimal winning strategies. However, tabletop role-playing games (TTRPGs) are driven by the power of collective storytelling and interactive narrative, as opposed to set rules, and therefore have a more open-ended goal - maximising player enjoyment for all participants. This involves a Game Master (GM) player as both narrator and referee, controlling the non-playable characters (NPCs) and the campaign behind the screen, whereas players usually control one player character (PC) each to interact with the world. There is no ‘failure’ state compared to traditional games, as campaigns can continue until players lose interest or the narrative is ‘complete’; even all PCs dying (known as a total party kill) can drive the narrative in a new direction. This project aims to study and piece together the different elements that would go into a Game Master AI, building on current state-of-the-art game-playing AI, such as Director AIs in games such as Valve’s ‘Left 4 Dead’, and studying the implications of such developments for players and game designers alike. For example, whether it could replicate the playing experiences of a human GM as a replacement, or enhance the experience by working with a human GM. Email t.j.best@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Alena Denisova Dr Raluca Gaina Prof. Simon Lucas Featured Publication(s): "Journeys in the Dark"-Towards Game Master AI in Complex Board Games Why Choose You?-Exploring Attitudes Towards Starter Pokémon Themes Design & Development Game AI Player Research https://www.youtube.com/watch?v=sYRhQ-w5yPA Previous Next

< Back Prasad Sandbhor University of York iGGi PG Researcher Available for post-PhD position Prasad is a serious game designer, researcher and educator specialising in environmental, nature-themed games, with an interdisciplinary practice informed by user-centred design and strategic management. In his PhD, he has developed the 'Thinking Through' framework for designing contextual role-playing games to support understanding of climate actions. He works at The Playful Learning at York (PLaY) Group, co-leads Play for the Planet Network and has co-founded the 'Play in Nature' initiative, which creates playful experiences that connect people with nature. A description of Prasad's research: Prasad's PhD research focuses on designing games that encourage players to 'think through' their climate actions. He designed and evaluated 2 physical role-playing games where players immerse themselves in realistic, relatable scenarios drawn from their own lives and communities. He drew upon climate change education and communication research, utilising serious game design and user-centred design methods to create these games. Instead of dictating what players should do, these games foster spaces for reflection, discussion, and sharing regarding the dilemmas, trade-offs, and tensions associated with climate actions. He has synthesised his findings into a framework called the 'Thinking Through Framework' for designing role-playing games. This framework consists of 7 design principles aimed at researchers, designers, and educators in the fields of climate change education and communication, enabling them to create their own role-playing games for climate action. Email prasad.sandbhor@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Jon Hook Featured Publication(s): Climate Companions: Designing a Live Action Role-playing (LARP) Game that Helps in Thinking Through Climate Actions Learning through play? What board games reveal and conceal about climate change Life on Wings: Relating to a Bird's Life in a City through a Board Game Radical Alternate Futurescoping: Solarpunk versus Grimdark Climate Club: A Group-based Game to Support Sensemaking of Climate Actions Themes Applied Games Design & Development - Previous Next

< Back George Long Queen Mary University of London iGGi PG Researcher Available for placement George is an iGGi PhD student interested in AI assisted game design, specifically the process of game balancing. After graduating with a BSc in Computer Science at the University of Essex, he joined iGGi in 2021. His research focuses on how AI can be used to balance games, in particular games with asymmetric elements. He has most recently been working on using agentic Large Language Models to theorycraft optimal strategies in games. A description of George's research: "My research focuses on balancing games through identifying overpowered or unfair rules, which can then be accounted for: My previous work identified how we can estimate unit point costs in miniature wargames. These wargames are played by forming armies comprised of units, the sum of each unit's point costs must be within the total army budget. Therefore it is crucial that these point costs accurately represent how useful the unit is in combat. We used Linear Regression and Linear Programming to estimate these point costs and improve the balance of an example game. Currently, I am investigating how we can use Large Language Models to theorycraft optimal strategies in games.I used an agentic approach where an agent comes up with an initial theory, tests in out in games, and uses the results of the game to create an iterative feedback loop to improve the strategy." Email g.e.m.long@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr Diego Pérez-Liébana Featured Publication(s): STEP: A Framework for Automated Point Cost Estimation Balancing wargames through predicting unit point costs PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Themes Design & Development Game AI Game Data - Previous Next

< Back Dr Ben Kirman University of York iGGi Training Coordinator Supervisor Available to supervise non-iGGi students for 2024 intake Ben is a Senior Lecturer (Associate Prof) in Interactive Media at the University of York, who has over 20 years' experience as a creative technologist. Since his first programming job fixing Y2K bugs (you're welcome), he has worked with dozens of organisations, large and small, in design and prototyping playful experiences. His research uses game design and playful design as a way to explore the complex effects of emerging technologies through novel and unexpected interactions and experiences. Most often, this is through the design and development of games, digital/physical prototypes, and design fictions. Ben has applied this in topics ranging from immersive theatre, dog technology, non-league football, radical cycle delivery, and time travelling robots, to educational games, esports, new situationism and magic. The unifying theme is play – as a topic of study, a way of working, for research insight, and as expression or output in games or playful experiences. This work, especially the more bizarre stuff, has often been covered by traditional media, including the BBC, New Scientist, Wired, The Guardian, TIME, Metro, the New York Times, and Your Cat magazine. Ben is keen on supervising students with strong creative drives, with an interest in making, design, experimentation, and a broad perspective on games and play. This might be a project about playful props in immersive theatre, or a project about context in locative and site-specific games, or any other project that looks to explore new possibilities and new implications of emerging technology through the lens of play. Research themes include: Game Design Applied Games Computational Creativity Sports with an E and without an E Player Experience Email ben.kirman@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing Design & Development Esports Player Research - Previous Next

< Back Dr Marko Tot Queen Mary University of London iGGi Alum Hello! I'm Marko, and welcome to my page! As a part of the IGGI programme and Game AI research group, I'm working on adapting Statistical Forward Planning methods for complex environments. Statistical Forward Planning methods have proven to be effective in some simpler domains and, without requiring any prior learning, they provide a good out of the box AI algorithm. However, while these algorithms shine in certain games, they struggle to perform well in cases where the reward received from the game is sparse. In games where it takes a series of optimal actions to reach the goal, without any significant feedback from the environment in between, their performance drops significantly. My research is centered on solving this problem through automatic sub-goal generation and utilisation of local learned forward models. Creation of the sub-goals could be used to simulate the feedback from the environment and give regular rewards to the agent even in sparse and complex environments. I started my journey in video games when I got my first PC at the age of six, and at that point it was decided that I'm going to make a career out of it. So here I am, ~20 years later, a PhD. student at Queen Mary University of London, trying to make AI agents that can play games, and regularly spending too much time playing games under the excuse that it's all for 'research purpose'. Email m.tot@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr Diego Pérez-Liébana Featured Publication(s): Adapting a world model for trajectory following in a 3d game Bootstrap Your Own Teacher: Online Policy Distillation for Multi-Game Reinforcement Learning Statistical Forward Planning Algorithms World and human action models towards gameplay ideation Turning Zeroes into Non-Zeroes: Sample Efficient Exploration with Monte Carlo Graph Search Making Something Out of Nothing: Monte Carlo Graph Search in Sparse Reward Environments What are you looking at? Team fight prediction through player camera Themes Game AI - 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

< Back Dr Joe Cutting University of York iGGi Alum + Supervisor Dr Joe Cutting is a Lecturer in Human-Computer Interaction in the Department of Computer Science at the University of York, UK. He has a BSc in Computer Science and an MSc in Cognitive Science from the University of Birmingham and completed an IGGI PhD at the University of York in 2019. Much of his research is in the area of the effects of playing video games on outcomes such as learning, cognitive abilities, wellbeing and behaviour change. This includes new psychological theories of how learning happens in video games and how game play can affect mental health, as well as studies on how game play can prevent cognitive decline in older people. He is also creating applied games to address current issues in education such as student wellbeing and teacher recruitment. Before becoming an academic, Joe enjoyed a varied career which included working as an interactive producer for the London Science Museum and founding his own digital startup company in the area of applied games. Email joe.cutting@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Prof. Paul Cairns Featured Publication(s): 01 01V Difficulty-skill balance does not affect engagement and enjoyment: a pre-registered study using artificial intelligence-controlled difficulty Higher working memory capacity and distraction-resistance associated with strategy (not action) game playing in younger adults, but puzzle game playing in older adults Objective difficulty-skill balance impacts perceived balance but not behaviour: A test of flow and self-determination theory predictions The task-attention theory of game learning: a theory and research agenda The Relationship Between Lockdowns and Video Game Playtime: Multilevel Time-Series Analysis Using Massive-Scale Data Telemetry Four grand challenges for video game effects scholars: How digital trace data can improve the way we study games Measuring the experience of playing self-paced games Measuring game experience using visual distractors Four dilemmas for video game effects scholars: How digital trace data can improve the way we study games The many faces of monetisation: Understanding the diversity and extremity of player spending in mobile games via massive-scale transactional analysis Busy doing nothing? What do players do in idle games? Understanding whether lockdowns lead to increases in the heaviness of gaming using massive-scale data telemetry: An analysis of 251 billion hours of playtime Themes Applied Games Design & Development Player Research - Previous Next

< Back Ruizhe "Jay" Yu Xia Queen Mary University of London iGGi PG Researcher Available for post-PhD position 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 Featured Publication(s): Play Style Identification Using Low-Level Representations of Play Traces in MicroRTS Themes Game AI Game Data - Previous Next