< Back Dr Kevin Denamganaï University of York iGGi Alum 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. Email kevin.denamganai@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr James Walker Featured Publication(s): CueTip: An Interactive and Explainable Physics-aware Pool Assistant EReLELA: Exploration in Reinforcement Learning via Emergent Language Abstractions Language Model Inversion through End-to-End Differentiation xInv: Explainable Optimization of Inverse Problems 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 Dr Poonam Yadav University of York Supervisor Dr Yadav research is focused on making the Internet of Things (IoT) and edge computing-based distributed systems resilient, reliable, and robust. This is an interdisciplinary research area that requires expertise in system design and integration along with knowledge of sensor systems, wireless networking, and domain and contextual understanding. To achieve resilience and reliability in the area of resource constraints and distributed systems, I focus on coordination and collaboration using interactions among machines, humans and data entities. These interactions could be categorized as machine-to-machine (M2M), machine-to-human (M2H), and human-to-data (H2D), and involve many challenges such as collaborative trust, privacy, legibility and accountability. Dr Yadav is an active reviewer of many top-tier ACM/IEEE IoT and networking conferences and journals. Dr. Yadav leads ACM-W UK professional chapter and is featured as "People of ACM Europe" and among the top ten N2Women Rising Star in Computer networking and communications in 2020. Research themes: E-Sports Use of IoT in Games Gamifications Citizen Science Email poonam.yadav@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Esports Game Data - Previous Next

< Back Dr Jon Hook University of York Supervisor Jon Hook is a Senior Lecturer (equivalent to an Associate Professor) in Interactive Media in the Department of Theatre, Film, Television and Interactive Media at the University of York. His research is situated in the field of Human-Computer Interaction (HCI) and explores the design and development of new interactive media content forms and tools to support their creation. This research combines his deep interest in new forms of interactive technology and media with empirical, theoretical and methodological perspectives, in the human-centred design of novel interfaces and interaction techniques for a broad range of artistic and everyday creative practices. His current research is focused on the design and development of new forms of responsive and immersive media content, with a particular interest in data-driven storytelling. He was recently the principal investigator of the EPSRC funded Perspective Media: Personalised Video Storytelling for Data Engagement project. He also a co-investigator of the InnovateUK WEAVR: Pioneering Fully Integrated Cross-Reality Spectator Experiences in Esports and Beyond immersive experiences demonstrator and the Digital Creativity Labs – a £4m EPSRC, AHRC and InnovateUK funded research centre exploring impact-driven research in the creative industries. He was also previously Co-I of the AHRC Within the walls of York Gaol: Memory, Place and the Immersive Museum the AHRC Digital Creativity for Regional Museums: Immersive Experiences Smart Commissioning Toolkit. He is especially interested in supervising students who’d like to do HCI research that involves making and evaluating new interactive media experiences. Some example topic areas that he might be the right supervisor for include, but aren’t limited to: Games to support broader data engagement and literacy Data-driven storytelling in, and about, games The intersection between games and interactive documentary film Responsive and interactive video storytelling in games The space where theatre and games converge Cultural heritage engagement using games Research themes: Game Design Games with a Purpose E-Sports Player Experience Email jonathan.hook@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Esports Player Research - Previous Next

< 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 Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): The Onboarding Phase in a Game for Text Labelling: Comparing the Effect of Animated vs. Textual Onboarding on Player Experience and Accuracy 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 Cristina Dobre Goldsmiths iGGi Alum Cristina Dobre has a background in Mathematics and Computing receiving distinction in her undergraduate degree in Computer Science. My current focus is on the nonverbal cues that influence and shape the social interaction in immersive VR environments. More broadly, I'm investigating autonomous agents (or virtual humans) in social settings in terms of non-verbal interactions with users. I'm interested in the underlying mechanics of social interaction that help developing an emphatic and engaging virtual human. At the moment, I'm working on ML models based on multimodal datasets to detect various social cues (such as gaze) or various human-defined social attitudes (such as engagement) in social interactions in VR. I'm also interested in generating more complex behaviour for virtual characters (NPCs) that will improve the user's experience with the NPCs in a social VR setting. Designing communication and other social interactions in immersive VR can be a challenging task, and aspects on this are addressed in my research. The findings from these studies can help game designers and game developers determine the appropriate non-player character's non-verbal (and verbal) behaviour in games, especially in VR games. Along with its applications in the games industry, the findings would be useful for other applications such as designing multi-modal human-machine interactions and other systems for medical purposes, for social anxiety disorders therapy, simulations, training or learning. Email cristina.dobre@uni-a.de Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Avatars in mixed-reality meetings: A longitudinal field study of realistic versus cartoon facial likeness effects on communication, task satisfaction, presence, and emotional… Gaze for Dyads & Blinks for Triads: Task Engagement Predictors in Free-Flow VR Interactions Live Link's Awakening of a Humorous Real-Time Character Multimodal Generation of Contextualized Jokes for a Real-Time Virtual Character Social Interactions in Immersive Virtual Environments: People, Agents, and Avatars Rolling Horizon Co-evolution in Two-player General Video Game Playing Using machine learning to generate engaging behaviours in immersive virtual environments More than buttons on controllers: engaging social interactions in narrative VR games through social attitudes detection Nice is Different than Good: Longitudinal Communicative Effects of Realistic and Cartoon Avatars in Real Mixed Reality Work Meetings Immersive Machine Learning for Social Attitude Detection in Virtual Reality Narrative Games Direct Gaze Triggers Higher Frequency of Gaze Change: An Automatic Analysis of Dyads in Unstructured Conversation Themes Game AI Immersive Technology - Previous Next

< Back Dr Valerio Bonometti University of York iGGi Alum Game analytics and player psychology: creating reliable models of player motivation Motivation can be loosely defined as a process of the brain and the mind, capable of driving and deeply shaping human behaviour. Motivational processes are embedded in many everyday life situations, exerting their effects via a wide range of incentive mechanisms and objects. Understanding this process in a videogame context, however, requires a more holistic approach considering not just the incentive properties of the game but also the player personal characteristics. My project aims to create reliable cross-games models of player motivation taking into account the contribution of natural inter individual variability. This will be accomplished linking in-game behavioural data and psychological models via a hybrid approach, where findings from small scale experimental studies (hypothesis-driven) will guide the realization of large scale (data-driven) applications for predicting players' characteristics, future behaviour and motivation evolution. Being able to model player motivation and predict the trajectories of its evolution could possibly lead to personalized and dynamic engagement strategies able to adapt accordingly to the player characteristics and in-game behaviour. Achieving a similar goal would be of pivotal importance in industrial and gamification contexts. I obtained my bachelor degree in Psychological Science and my master degree in Clinical Psychology at Padova University (Italy). During my academic path I acquired knowledge in general psychology, cognitive psychology, psychophysiology, neuroscience and research methodology. After my master degree I spent a considerable amount of time as a research trainee, both abroad and in my country, always investigating the reward process and its effects in various contexts. During this period I worked on various projects across different fields ranging from psychophysiology, player research and game analytics. In my free time I enjoy practicing indoor climbing and travelling, I like figurative art in general and more specifically I’m a huge cinema and graphic-novel enthusiast. Supervisors: Prof. Anders Drachen, Dr Sam Devlin Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): From Theory to Behaviour: Towards a General Model of Engagement Modelling early user-game interactions for joint estimation of survival time and churn probability Predicting skill learning in a large, longitudinal MOBA dataset Mind the gap: Distributed practice enhances performance in a MOBA game Approximating the Manifold Structure of Attributed Incentive Salience from Large-scale Behavioural Data: A Representation Learning Approach Based on Artificial Neural Networks Themes Player Research - Previous Next

< Back Dr Phoebe Hesketh University of York iGGi Alum Phoebe's PhD explored how people learn to play games through gameplay, online media, and community interaction. At the University of York, Phoebe worked on her skills as a researcher by exploring multiple methodologies and disciplines. She built upon her quantitative research skills from Bristol with qualitative research during their PhD including grounded theory and thematic analysis. She took courses in user-centred design and evaluation and designing for accessible player experiences (through AbleGamers). She participated in game jams and game development courses for experience and technical design. She also gave a talk at DEVELOP 2021 communicating and sharing her research and expertise in how players learn to play games to help designers with their onboarding for their games. She originally studied Engineering Mathematics at the University of Bristol which focused on systems and mathematical modelling and simulation, the mathematics and implementation of AI and Machine Learning systems, programming in object-oriented programming languages such as C++ and Java, and developed ray tracers in computer graphics courses. She also worked on projects in linguistics, logistics, computer vision, and physics. Once completing her PhD, Phoebe moved into the games industry as an AI programmer for several years before looking to return to games and player research. She has set up her own company, Take A Mo, that focuses on helping developers analyse their systems and internal systems to maximise access for players in usability, onboarding, accessibility, and representation. She is a currently carving her niche in the industry. Email phoebe@takeamo.co.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Sebastian Deterding Dr Jeremy Gow Featured Publication(s): Learning Team-Based Esport Games: Success Factors in Learning from Spectating How Players Learn Team-versus-Team Esports: First Results from A Grounded Theory Study Themes Esports Player Research - Previous Next

< Back Susanne Binder Queen Mary University of London iGGi Manager iGGi Admin iGGi Manager @ QMUL ; alongside David Hull (iGGi Manager @ UoY) , and supported by Shopna Begum , Helen Tilbrook and Oliver Roughton, she's mostly in charge of making things run at iGGi with particular focus on iGGi-QMUL-specific admin iGGi-QMUL-specific student concerns PR, website and social media industry liaison Email s.binder@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes - Previous Next

< Back Prof. Nick Bryan-Kinns Queen Mary University of London Supervisor Nick Bryan-Kinns is Professor of Interaction Design and Director of the Media and Arts Technology Centre at Queen Mary University of London. He is Distinguished Professor at Wuhan University of Technology, and Guest Professor at Huazhong University of Science and Technology, China. He is Fellow of the Royal Society of Arts, Fellow of the British Computer Society, Senior Member of the Association for Computing Machinery, and leads the Sonic Interaction Design Lab in the Centre for Digital Music. He has published international journal papers on cross-cultural design, participatory design, mutual engagement, interactive art, and tangible interfaces. His research has been exhibited internationally and reported widely from the New Scientist to the BBC. He chaired the Steering Committee for the ACM Creativity and Cognition Conference series, and is a recipient of ACM and BCS Recognition of Service Awards. He is interested in supervising students with HCI, Interaction Design, or AI backgrounds on research into the intersection of Sonic Interaction Design, play, and AI. Especially project which involve designing and evaluating computer mediated experiences for human participation and collaboration. Research themes: Game Audio and Music Games with a Purpose Computational Creativity Player Experience Gamification Email n.bryan-kinns@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing Game Audio 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 Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Player Research - Previous Next

< Back Prof. Richard Bartle University of Essex iGGi Co-Investigator Supervisor Richard Bartle is a renowned pioneer in game design and research. He co-wrote the first virtual world, MUD ("Multi-User Dungeon") in 1978, and has thus been at the forefront of the online games industry from its very inception. He is an influential writer on all aspects of virtual world design, development, and management. As an independent consultant, he has worked with many of the major online game companies in the U.K. and the U.S. over the past 30 years. His 2003 book, Designing Virtual Worlds , has established itself as a foundation text for researchers and developers of virtual worlds alike. His Player Type theory is taught in game design programmes worldwide (he appears in examination questions!). His interests are directed mainly virtual worlds, particularly Massively Multiplayer Online Role-Playing Games (MMORPGs, or MMOs), but cover all aspects of game design. He is keen to see AI used for non-player characters in MMOs (his PhD is in AI), and his current work considers the long-term moral and ethical implications of this. They’re maybe not what you might think they were at first glance… Email rabartle@essex.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Game AI Player Research - Previous Next

< Back Dr Christian Guckelsberger Queen Mary University of London iGGi Alum + Supervisor Intrinsic Motivation in Computational Creativity with Applications to Games. (Industry placement at Splash Damage and Microsoft Research) This research investigates how we can engineer artificial systems that are creative in their own right. Christian addresses this challenge with computational models of intrinsic motivation (IM). Intrinsically motivated agents perform an activity for its inherent satisfaction rather than for some instrumental outcome. A classic example is to act in order to satisfy one’s curiosity. In both theoretical and applied studies, he demonstrates that models of IM can give rise to general, robust and adaptive creative systems. Christian has shown how models of IM can be used to create highly general non-player characters. Such characters can potentially be used in a wide range of games without previous knowledge of the game mechanics, reducing costs and effort in game development while increasing robustness and behavioural variety Christian’s ongoing research stretches beyond video games, investigating the role of computational models of IM for intentional agency, open-ended development and creativity in minimal lifeforms and artificial systems. Christian studied Computer Science, History of Art and Business in Germany and the UK and is now based in London, working towards a PhD in Artificial Intelligence. His work challenges the question how computers could ever become genuinely creative with a highly interdisciplinary approach based on Computing, Cognitive Science and Philosophy. Over the last few years, he published papers on a wide range of topics, held a tutorial on intrinsic motivation in video games, organised workshops on computational serendipity and spent three months at NYU’s Game Innovation Lab for a research collaboration. Christian has substantial industry experience, looking back at three years in the R&D department of SAP SE and a recent internship at Microsoft Research Cambridge. He enjoys working in an international environment with open-minded, passionate people. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Not All the Same: Understanding and Informing Similarity Estimation in Tile-Based Video Games Predicting game difficulty and engagement using AI players Embodiment and computational creativity Intrinsic Motivation in Computational Creativity Applied to Videogames. PhD Thesis. 306 pages. The Relationship of Future State Maximization and von Foerster's Ethical Imperative Through the Lens of Empowerment On the Machine Condition and its Creative Expression. Understanding and Strengthening the Computational Creativity Community: A Report From The Computational Creativity Task Force. Action Selection in the Creative Systems Framework Measuring perceived challenge in digital games: Development & validation of the challenge originating from recent gameplay interaction scale (CORGIS) Generative design in Minecraft: Chronicle challenge Towards Mode Balancing of Generative Models via Diversity Weights Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities Themes Game AI - Previous Next