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< 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 Mastodon Other links Website https://www.linkedin.com/in/robert-j-homewood-36906132/ LinkedIn BlueSky Github Themes Player Research - Previous Next

< Back Dr Sarah West University of York Supervisor Sarah West is an interdisciplinary researcher and practitioner working to bring diverse voices into research through participatory approaches, including citizen science. Sarah is currently Director of SEI York, a Centre of the Stockholm Environment Institute, a science-to-policy research institute, whose York Centre is at the University of York in the Department of Environment and Geography. She has used citizen science approaches to address topics as diverse as air pollution, biodiversity, parenting, and exploring community responses to Covid-19. Her projects mainly take place in the UK and Kenya. Sarah has spent over a decade designing, running and evaluating citizen science projects, and together with other SEI colleagues has written reports for Defra, UK Earth Observation Framework and journal articles exploring who participates in citizen science, their motivations for participation, and how volunteers can be recruited and retained. She is particularly interested in exploring how different messaging and communication affects participation in citizen science projects. sarah.west@york.ac.uk Email Mastodon https://www.york.ac.uk/sei/staff/sarah-west/ Other links Website https://www.linkedin.com/in/sarah-west-59b82690/ LinkedIn BlueSky Github Themes Accessibility Design & Development Player Research - Previous Next

< Back Pilar Zhang Qiu Queen Mary University of London iGGi Alum Pilar is a researcher with a background in Design Engineering. She has a keen interest in user experience and interaction, wearables and the use of cyber-physical systems in the medical field. Her PhD centres around the creation of play assessments for neuromotor conditions in children with cerebral palsy. This gravitates around the idea that better and more objective clinical data can be obtained through gamification of common assessments. Please note: Updating of profile text in progress Email Mastodon https://www.pilarzhangqiu.com/ Other links Website https://www.linkedin.com/in/pilar-zhang-qiu/ LinkedIn BlueSky https://github.com/pili-zhangqiu Github Themes Applied Games - Previous Next

< Back - @ Develop:Brighton 2025 - Toby Best Queen Mary University of London iGGi PG Researcher Available for placement 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. t.j.best@qmul.ac.uk Email Mastodon https://l0rdr0b.github.io/ Other links Website https://www.linkedin.com/in/toby-best-776336136/ LinkedIn BlueSky https://github.com/L0RDR0B Github 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 Previous Next

< Back Dr Evelyn Tan University of York iGGi Alum Evelyn holds a master’s degree in Industrial-Organisational Psychology from University College London (UCL) and has previously worked in the HR Technology industry where she undertook projects on game-based assessment, virtual team coaching and virtual reality (VR) hiring and training. She has published her work on developing trust in virtual work teams at CHI PLAY 2019, a premier conference for games research. On the Emergence and Development of Team Cohesion in Newly Formed Virtual Teams Evelyn specialises in teamwork and team dynamics. She is interested in uncovering how cohesion emerges and develops, and to identify its predictors. Her goal is to understand how to build high-performing teams that make people want to stay and remain united in the pursuit of their shared objectives. Under IGGI, she studies virtual teams in competitive esport games, specifically newly formed ad hoc teams. By applying theories and principles from psychology, her work can be extended to address the challenges faced by real-world teams with similar characteristics, for example emergency response teams and short-term project teams. By studying team cohesion – its emergence and development – her work addresses the broader challenges of building high-performing teams which retain their members. Please note: Updating of profile text in progress Email Mastodon https://sites.google.com/view/evelyntan Other links Website https://www.linkedin.com/in/evelyntisiantan/ LinkedIn BlueSky https://github.com/ett506 Github Featured Publication(s): Communication Sequences Indicate Team Cohesion: A Mixed-Methods Study of Ad Hoc League of Legends Teams Less is More: Analysing Communication in Teams of Strangers Trusted Teammates: Commercial Digital Games Can Be Effective Trust-Building Tools Themes Esports Player Research - Previous Next

< Back Cameron Johnston Queen Mary University of London iGGi PG Researcher Available for placement Cam holds an MPhys in Theoretical Physics from the University of Edinburgh, wherein he combined infectious disease models with fluid dynamics to examine the validity of wastewater-based epidemiology as a method of passively monitoring the prevalence of COVID-19 in an urban population. During his studies, Cam began to learn game development as a way of improving his programming skills, using C++ and the Unreal Engine to develop a number of small projects and compete in game jams. After completing his MPhys, Cam was eager to take his experience developing physics simulations even further, which lead him to joining the iGGi programme. About Cam's Research: 'Impossible physical models' refer to digital models of any physics that differs from what would be experienced in everyday life. This covers 'incorrect' physics (disagreeing with observation but mathematically valid), and unfamiliar physics (that which is physically correct but irrelevant on a human scale). By creating interactive, virtual environments around these models, it becomes possible to experience the impossible. This research aims to explore the potential of 'impossible physical models' in the context of video games from the perspectives of game design and education. The project explores what work has already been done into this topic, expands on this work, and finds new areas to explore. The goal of this research is to introduce new relationships between physics and video games, and to engender developers to explore physics as a tool for design. cameron.johnston@qmul.ac.uk Email Mastodon http://crjohnston.com Other links Website https://www.linkedin.com/in/c-r-johnston/ LinkedIn BlueSky Github Supervisor: Dr Josh Reiss Themes Creative Computing Design & Development - Previous Next

< Back Laura Helsby University of York iGGi PG Researcher Laura Helsby is a HCI researcher with a background in psychology, currently examining how features of games might be beneficial to wellbeing and mood. She is particularly interested in how people with persistent low mood play and experience games, and what this might mean for their wellbeing. So far, she has conducted one interview study asking people with low mood what they play and why, and one diary study investigating the 'in the moment' effects and motivations for gaming. Future plans involve making more direct measures of the impact of particular games on wellbeing, as well as looking further into the FPS and simulation genres to unpack what about these games might make them appealing to people with persistent low mood. Laura has achieved an MSc in Foundations in Clinical Psychology from Newcastle University and a BSc in Psychology from the University of York. In her spare time, Laura enjoys denying she is a computer scientist at all. Her hobbies include reviewing books professionally, board game nights and of course, playing video games. laura.helsby@york.ac.uk Email Mastodon Other links Website LinkedIn https://bsky.app/profile/laurahelsby.bsky.social BlueSky Github Supervisors: Prof. Paul Cairns Dr Jo Iacovides Featured Publication(s): "Leave our kids alone!": Exploring Concerns Reported by Parents in 1-star Reviews Do People Use Games to Compensate for Psychological Needs During Crises? A Mixed-Methods Study of Gaming During COVID-19 Lockdowns Themes Applied Games Player Research - Previous Next

< Back Dr Kevin Denamganaï University of York iGGi Alum Available for post-PhD position After graduating as an Engineer from the Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA), France, with two double-degree diplomas, a MEng in Electrical Engineering and Information Science from the Osaka Prefecture University (OPU), Japan, and a MRes in Artificial Intelligence and Robotics from the Université de Cergy-Pontoise (UCP), France, Kevin Denamganaï spent a year accumulating experience as a Robotics & Machine Learning freelancer. He is now putting those skills at use in the IGGI PhD program, that, among other things, gives him the opportunity to reunite with video games. Indeed, it was thanks to a keen interest towards video game creation that he started learning programming around 12. His research interests are about everything psychology, neuroscience, AI, (deep) reinforcement/imitation learning, robotics, and natural/artificial language emergence and understanding as well as human-computer interfaces, challenging the question what are the necessary components of artificial agents to be able to converse with human-beings in an engaging manner and to be able to cooperate with them towards a pre-defined goal, e.g. clearing a level in a given video game. kevin.denamganai@york.ac.uk Email Mastodon https://kevindenamganai.netlify.app/ Other links Website LinkedIn BlueSky https://github.com/Near32/ Github Supervisor(s): Dr James Walker Featured Publication(s): ETHER: Aligning Emergent Communication for Hindsight Experience Replay Visual Referential Games Further the Emergence of Disentangled Representations Meta-Referential Games to Learn Compositional Learning Behaviours A comparison of self-play algorithms under a generalized framework On (Emergent) Systematic Generalisation and Compositionality in Visual Referential Games with Straight-Through Gumbel-Softmax Estimator ReferentialGym: A Nomenclature and Framework for Language Emergence & Grounding in (Visual) Referential Games A generalized framework for self-play training Coupled Kuramoto oscillator-based control laws for both formation and obstacle avoidance control of two-wheeled mobile robots Obstacle avoidance control law for two-wheeled mobile robots controlled by oscillators Themes Game AI - Previous Next

< Back Tom Wells University of York iGGi PG Researcher Available for placement Tom has an interest in niche alternative and indie games which evoke strong emotions and are narratively immersive. He studied Experimental Psychology as an undergraduate in Oxford, specialising in conscious brightness perception in specific optical pigments. His Masters was in Computational Neuroscience, Cognition and AI from Nottingham, and focused on Computer Vision (specifically facial recognition) and Visual Attention. He enjoys heavy metal, strength sports and literature. A description of Tom's research: With the rise of digital art, Uncanny Valley has emerged from an esoteric robotics concept into an infectious memetic phenomenon, with specific memes such as 'Uncanny/Canny Mr. Incredible', or more generally uncanny faces being used as reaction images for humor. Critics and players will now refer to specific media being 'Uncanny' rather than using more general words as 'off-putting', demonstrating uncanniness cementing itself in the public consciousness as examples increasingly abound; ergo digital artists should be aware of evoking the uncanny even with modern rendering technology, as audiences become increasingly discerning of the Uncanny. This is most pertinent in videogames, where rendering is performed in real-time, meaning rendering constraints must be implemented. This potentially confines characters to the Uncanny Valley, as it may not be possible to increase graphical fidelity, thus artists may be left to either accept the uncanny or demaster their work (both undesirable options). This project aims to learn about the Uncanny Valley pertaining to modern skin rendering techniques, using artificial intelligence (specifically GANs) to directly map skin rendering parameters onto user assessments of uncanniness and realism. This can then be reverse engineered to provide automated tools for generatively rendering realistic non-uncanny skin, and predicting audience responses to skin realism, expediting QA testing. The primary experimental stage is to generate a face database with photorealistic skin to be assessed using psychometrics by participants. This is additionally one of few studies looking into the novel phenomena of training AI's to generate human-oriented psychologically salient content. tw1700@york.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes - Previous Next

< Back - @ Develop:Brighton 2025 - 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 peter.cowling@qmul.ac.uk Email Mastodon https://www.petercowling.com/ Other links Website https://uk.linkedin.com/in/peter-cowling-3590962 LinkedIn BlueSky Github Themes Applied Games Design & Development Game AI - Previous Next

< Back Nathan John Queen Mary University of London iGGi PG Researcher After graduating with a MEng in Computer Science from the University of Bristol, Nathan joined the games industry as a programmer, working for Climax Studios, Gaming Corps and Freejam, before moving to a career as a general software engineer, while still developing indie games on the side. His experiences across a range of industries sparked a passion for testing, and left him wondering if there were was to improve the automated testing in game development. Borne from an experiment Nathan had performed training AIs to play his indie game WarpBall, in which he found the agents solved for exploits in the authored AI rather than playing the game well, his research project proposes a novel method for improving the quality of behaviour of human authored agents by pitting them against trained agents and observing what bad behaviours/exploits the trained agents reveal. Authored agents refer to AI agents whose actions are explicitly designed by programmers using traditional techniques such as Utility functions, Behaviour Trees and state machines; trained agents refer to agents whose behaviour is learned by playing many games against the authored agents. n.m.john-mcdougall@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/vethan4/ LinkedIn BlueSky Github Supervisors: Dr Jeremy Gow Dr Laurissa Tokarchuk Themes Design & Development Game AI - Previous Next

< Back - @ Develop:Brighton 2025 - Joshua Kritz Queen Mary University of London iGGi PG Researcher Available for placement Graduated in Applied Mathematics in computer science, however my love for games pushed me to dedicate myself for studying them. This led me to brave many areas of knowledge, such as: psychology, design, education, production and entrepreneurship. My work as a teacher allowed me develop many of these skills in practice, besides invoking a new perspective about the world. On a personal level, I love new experiences that can teach me new knowledge and, most important, I am very open minded and easy to talk to! I believe discussion leads to enlightenment. A description of Joshua's research: Card games, in particular Trading Card Games (TCGs) thrive on using the synergy between the cards to create emergent and interesting gameplay. However, these games usually have hundreds of different cards to create such rich experience, with some older TCGs featuring thousands of different cards. With such a huge amount of different cards playtesting these games present a big challenge. In example a new set of Magic the Gathering takes over 3 years of development to be fully designed. But even considering simpler exemplars like Dominion or Assencion can be difficult to balance, and both games are known to need a few expansions of experience to indeed provide a well balanced experience. One way to make this task faster and easier is to use automated agents to playtest the game exhaustively and provide much needed data. Whilst this would assist card game development, it is not used in practice, the playtesting of card games is still completely done by players. Even with systematic playtesting there is a limit of how much of the possibilities humans can test. However, implementing playtesting of card games have two big challenges, which are the main reason it has not been implemented in practice yet. First: Automated agents are not great when playing a game with too many variables (different cards) Second: The possible combinations of cards used in a deck or set of a single game is huge. My research aim to address the second issue by using a theory of synergy between cards to reduce the search space necessary to properly evaluate a card game. j.s.kritz@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/joshua-kritz-38808379/ LinkedIn BlueSky Github Supervisor: Dr Raluca Gaina Featured Publication(s): A FAIR catalog of ontology-driven conceptual models A Conceptual Model for the Analysis of Investigation Elements in Games A Vocabulary of Board Game Dynamics Unveiling modern board games: an ML-based approach to BoardGameGeek data analysis When 1+ 1 does not equal 2: Synergy in games Towards an Ontology of Wargame Design Themes Applied Games Design & Development Game AI Previous Next