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< Back Dr Chris Madge Queen Mary University of London iGGi Alum Turning Difficult Scientific Problems into Easy Games: Crowdsourcing Solutions via Gamification The aim of the research is to exploit, on a large scale, the idea introducing game elements in a non-game context (gamification) and make use of a large population of non-expert users to solve scientific problems (crowdsourcing). The proposed research follows the increasingly popular concept of splitting a large, complex task into small easily digestible tasks that lend themselves to division, distribution and game representation. This research will begin by taking advantage of the University of Essex’s expertise in the field of Natural Language Engineering. Multiple games will be created to attempt to encourage people to participate in training natural language models. This will be achieved by splitting these tasks into smaller problems that can be represented as games, and easily solved by players that could not easily be solved computationally. Alongside this, the success of different gamification methods and game design choices will be evaluated to determine their effect on the information gathered and the accuracy achieved. This evaluation will be used to guide the development of future games in the research with a view to producing better quality models for solving natural language problems, and improving gamification. Prior to starting my PhD with IGGI I completed a BSc in Computer Science and MSc in Advanced Computer Science. During both of those I took multiple computer game and AI courses in addition to text analytics and natural language engineering courses. During my BSc I was fortunate to work at Signal Media as an intern on text analytics related problems. Before starting my BSc I worked as a software developer for 5 years, primarily in web application development. I’ve had a passion for games from a very young age and continue to play on PC, mobile and consoles today. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Gamifying language resource acquisition Progression in a language annotation game with a purpose Incremental game mechanics applied to text annotation Making text annotation fun with a clicker game The design of a clicker game for text labelling Crowdsourcing and aggregating nested markable annotations Testing TileAttack with Three Key Audiences Experiment-driven development of a gwap for marking segments in text Metrics of games-with-a-purpose for NLP applications Testing game mechanics in games with a purpose for NLP applications TileAttack Novel Incentives for Phrase Detectives Themes Player Research - Previous Next

< Back Dr Nathan Hughes University of York iGGi Alum Nathan Hughes is a player experience researcher who focuses on how player make choices within games. Specifically, the work explores open world games such as Skyrim and the Witcher 3, as these games allow players a vast amount of choice with little restrictions on how and when these are made. However, little research has considered these choices, so little is known about how players experience choice in open world games. Therefore, research questions for this work include; why do players choose not to pursue the main quest? What do players choose to do instead? When and how do they make this decision? His background is in psychology, and so asks these questions from a psychological perspective. The aim is to uncover how the process of choosing unfolds, and how this is influenced. In turn, this may allow reflections on how the decision-making process operates - by analysing choices within open world games, a more controlled (but still intrinsically motivating) setting can be studied. ngjhughes@gmail.com Email Mastodon https://faethfulexplorations.wordpress.com Other links Website https://www.linkedin.com/in/nathan-hughes-1035b611b/ LinkedIn BlueSky Github Supervisor Prof. Paul Cairns Featured Publication(s): Clinicians Risk Becoming "Liability Sinks" for Artificial Intelligence Understanding specific gaming experiences: the case of open world games The need for the human-centred explanation for ML-based clinical decision support systems Growing Together: An Analysis of Measurement Transparency Across 15 Years of Player Motivation Questionnaires Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units Growing together: An analysis of measurement transparency across 15 years of player motivation questionnaires Opening the World of Contextually-Specific Player Experiences No Item Is an Island Entire of Itself: A Statistical Analysis of Individual Player Difference Questionnaires Ethereum Crypto-Games: Mechanics, Prevalence, and Gambling Similarities Themes Player Research - Previous Next

< Back Dr Søren Riis Queen Mary University of London Supervisor Søren Riis has more than 15 years of experience in teaching computability, complexity and the art of creating fast efficient algorithms. He has a strong interest in reinforcement learning and generative adversarial networks (GANs) related to strategy games. Riis has been actively involved in computer chess, and is listed on the wiki of influential people in chess programming https://www.chessprogramming.org/ Søren Riis is a strong player of strategy games including Chess, Shogi, Go and Bridge at an internal level. He has worked as a consultant for an AI company and is involved in applying deep learning for the card game of bridge. For the last 5 years he has been working on technical projects related to machine learning and reinforcement learning. He has practical experience and interest in scientific computing on super computers, and in creating C and C++ libraries to run from within python. Søren Riis is particularly interested in supervising students with a strong technical and/or maths background. Aptitude for strategy games with an interest in one the following ares is an advantage. Games requiring inductive reasoning combined with exploration. Hidden identity games (Werewolf, Resistance/Avalon, Mafia etc) Using GANs to sample realistic scenarios during gameplay Deep Reinforcement Learning in multi-agent strategy games Building and analysing games for investigating evolution of communication. Research themes: Game AI Game Design Game Creativity Games and mathematics s.riis@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/profiles/riissoren.html Other links Website https://www.linkedin.com/soren-riis-13602117/ LinkedIn BlueSky Github Themes Creative Computing Game AI Game Data - 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 Mastodon Other links Website https://www.linkedin.com/in/alex-fletcher-64ab72176 LinkedIn BlueSky Github Themes Applied Games Game Audio Player Research - Previous Next

< Back Prof. Greg Slabaugh Queen Mary University of London Supervisor Gregory G. Slabaugh is Professor of Computer Vision and AI and Director of the Digital Environment Research Institute (DERI) at Queen Mary University of London. He is also a Turing Fellow at the Alan Turing Institute. His research work spans computer vision and computer graphics including geometric modelling and image/video-based understanding. He is interested in deep learning approaches including generative techniques like normalizing flow an generative adversarial networks. He previously worked in the games industry as a 3D graphics programmer and his PhD thesis focussed on how to model 3D objects from a collection of images. He is interested in how to create engaging content and interaction from images as well as procedural methods to reduce the effort of 3D modelling. g.slabaugh@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/~gslabaugh Other links Website https://www.linkedin.com/in/greg-slabaugh-a5b03a1/ LinkedIn BlueSky Github Themes Applied Games Creative Computing Immersive Technology - Previous Next

< Back Peter York University of York iGGi Alum PhD student working in analytics and machine learning for esports broadcast and understanding. In particular working with Weavr on various projects related to broadcast and learning tools for Dota 2. Please note: Updating of profile text in progress Email Mastodon https://pete-york.github.io Other links Website LinkedIn BlueSky Github Featured Publication(s): Data-Driven Audience Experiences in Esports Metagaming and metagames in Esports DAX: Data-Driven Audience Experiences in Esports A generalized framework for self-play training Themes Esports Game AI - Previous Next

< Back Dr Sokol Murturi Goldsmiths iGGi Alum AI for game design: learning from designers For my PhD I am investigating how AI can help developers by learning to generate content in a similar fashion to the developers themselves. I envision a framework based on reinforcement learning, where an AI can learn a design policy for some content domain (e.g., FPS maps or platformer levels) by observing human designers. The AI would learn to take particular design actions in certain kinds of content states. Recent research into reinforcement learning has shown it is a powerful framework for developing complex agent behaviours and I believe there is a lot of potential to apply this work to game design. How would a human and artificial designer interact? Assume that an AI has learned to design a specific kind of content, such as a house, by observing human designers at work. A human designer could then partially develop some new content, and ask the AI to suggest some variations on it (see figure below), with both AI and human iterating on the design in a mixed-initiative interaction. The AI could learn from feedback from both the human designer and playtesting. As human feedback may not produce enough data for effective learning, the AI could perhaps extend this with data from simulated playtests. Game design decisions are often made with an expectation of how the player will react, and I could also look at how player models could be incorporated into the AI designer. In a reinforcement learning approach, the state could represent content+player, and the AI could learn to take design actions aimed a specific types of player. Developers could use this framework to develop content targeted at an individual player's style. Moreover, if the AI has learned something about how the human designer creates content, it can then be used live during the game to modify game elements in response to player interaction. Developers could set up modular levels, giving the AI the ability to adapt certain areas with content generated specifically to match the player. smurt001@gold.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next

< Back Prasad Sandbhor University of York iGGi PG Researcher Available for placement Prasad is a serious game designer and researcher. He has designed digital, tabletop and hybrid games in diverse areas such as education, healthcare, entrepreneurship, social safety, accessibility and sustainability. He is a part of the ‘Play in Nature’ initiative that crafts playful experiences to connect people with nature around them. He also teaches game design and user experience design. As a multidisciplinary design consultant, Prasad has been involved in conceptualising and creating B2C and B2B digital products for Indian as well as international organisations. His professional experience of 8 years in setting and leading design teams has made him proficient in strategic management of design. Prasad has been able to maintain his secret identity as a freelance author too. He writes short stories and essays in his native language, Marathi. A description of Prasad's research: Prasad’s PhD research explores designing games that facilitate the sensemaking of climate actions among university students. It defines ‘sensemaking’ as a structured process aiding the understanding of alternative pro-environmental actions within complex constraints, involving activities like reflection, brainstorming, and critiquing. The primary objective of his work is to identify game elements that impact players’ ability to make sense of climate actions to articulate design and facilitation guidelines for researchers, designers, and educators from climate change education and communication domains. It also aims to explore the transferability of sensemaking from the game into the real world. As a part of his research, Prasad is designing 3 climate change games using user-centred methods and exploratively evaluating them to see how they help players experience and develop sensemaking. He started with ‘Climate Club’, a tabletop role-playing game dealing with climate action-related decision-making challenges within everyday constraints. Its evaluation showed that the use of curated group setup, relatable contexts, problem-solving mechanic, and explicit mention of climate issues enhances sensemaking while group dynamics and asymmetric role-plays may cause hindrance. Combining these with other literature findings, Prasad designed ‘Climate Club 2.0’, a mini-live action role-playing game (LARP) about planning a climate-friendly holiday which is currently under evaluation. prasad.sandbhor@york.ac.uk Email Mastodon https://linktr.ee/prasadsandbhor Other links Website https://www.linkedin.com/in/prasad-sandbhor/ LinkedIn BlueSky Github Supervisor: Dr Jon Hook Featured Publication(s): Radical Alternate Futurescoping: Solarpunk versus Grimdark Climate Club: A Group-based Game to Support Sensemaking of Climate Actions Radical Alternate Futurescoping: Solarpunk versus Grimdark Themes Applied Games Design & Development - Previous Next

< Back 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 always been fascinated by how people engage with games—both emotionally 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 how psychological principles such as motivation and disengagement apply not just to players, but to the systems they interact with. Her PhD research focuses on limited-time events (LTEs) in digital games—temporary content used to drive engagement and re-engagement. By exploring how LTEs influence player engagement, disengagement, and return play in live-service games, her work aims to bring clarity to this rapidly evolving area of game design. She is currently developing a cross-platform taxonomy of LTEs through large-scale content analysis of over 1,000 top-charting mobile and PC games. Alongside this, she is conducting an ongoing diary-plus-interview study to explore how players experience these events in everyday play. Tamsin’s research investigates how different LTE formats affect sustained engagement, disengagement, and re-engagement, with the goal of informing more ethical and effective event design for both players and developers. She is open to Knowledge Exchange opportunities with game studios interested in analysing live-service events, player behaviour, and re-engagement strategies using live data or design insights. When not writing about or analysing games, Tamsin enjoys baking, reading, playing cosy indie games, and quietly grinding dailies. tamsin.isaac@york.ac.uk Email Mastodon http://www.tamsinisaac.com Other links Website http://www.linkedin.com/in/tamsinisaac LinkedIn https://bsky.app/profile/tamsinisaac.bsky.social BlueSky Github Supervisor: Prof. Paul Cairns Themes Applied Games Design & Development Player Research https://www.youtube.com/watch?v=n32ngtGYNQ8 Previous Next

< 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