< Back Callum Deery University of York iGGi Alum Callum is a researcher and game developer investigating how real-time player experience measurement can be used to drive adaptive games. Aiming to embed player experience questionnaires into games in a way that doesn’t break immersion and presence, his PhD is focussed on leveraging the wide range of existing player experience questionnaires to improve games ability to adapt to players. This will involve exploring the states of immersion and presence: What is necessary to maintain them? What experiences can players reflect on without breaking immersion? How do we embed a questionnaire into an in-development game without disrupting the player experience? Email callum.deery@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr James Walker Dr Anna Bramwell-Dicks Themes Accessibility Design & Development Player Research - Previous Next

< Back Rory Davidson University of York iGGi PG Researcher Available for post-PhD position Learning and Strategy Acquisition in Digital Games Given the success and impact of games and the gaming industry, it is unsurprising that it has become the centre of a significant body of academic research and other literature. However, while the cognitive effects of gameplay have been extensively studied, this has typically been done from a “black-box” perspective – that is, looking at the effects of gameplay as a whole upon some other task or metric, such as ability to strategize or proclivity to violence – leaving the inner mechanisms of cognition during gameplay much less understood. In particular, while the idea of learning from games is an area of continued interest in educational psychology, very little literature exists on the subject of how learning in games actually occurs on a cognitive level. This study aims to fill this knowledge gap by examining the ways in which player learning and strategy acquisition occur within games. This examination will have two main hierarchical goals. In the first phase, the study will use experimental methods inspired by analysis of learning methods used in games as well as literature review of more general theories of learning and cognition, such as the dual-process account or the CLARION model, in order to form a model better specialized for the field of digital gaming. In the second phase, it will analyse how such a theory may be put to practical use to inform the design of games and game-like experiences. These two phases can be summed up in the following main research questions: Phase 1: How can strategy acquisition in digital games most effectively be explained as a cognitive process? Phase 2: How can this understanding be put into practice in the development of games with specific desirable characteristics? By linking a more complete understanding of cognition and learning during games with measurable or observable gameplay characteristics, this study will further research on gameplay experience, such as that on immersion. The first phase of research additionally has relevance to the field of AI, in which human responses to difficult and complex problems such as digital games may be mimicked or otherwise used to inform the design of new techniques, as well as to gamification, which attempts to elicit such responses in non-game contexts. Email rd553@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Featured Publication(s): Automatic Game Tuning for Strategic Diversity Themes Applied Games Design & Development Player Research - Previous Next

< Back Dr Ivan Bravi Queen Mary University of London iGGi Alum Ivan Bravi has obtained his B.Sc and M.Sc in Engineering of Computer Systems at the Politecnico di Milano, Italy. From January to July 2016 he was Visiting Scholar at the NYU’s Game Innovation Lab in New York, under the supervision of Prof. Julian Togelius. Since October 2017 he's an IGGI PhD student at Queen Mary University of London under the supervision of Simon Lucas. Ivan has published several workshop and conference papers in different venues such as IJCAI, Evostar, CIG, FDG, AAAI and CoG. Automatic playtesting of games can significantly streamline the process of designing, developing and releasing a game. It is also a possible application of Artificial General Intelligence (AGI): having a set of flexible algorithms that can play games regardless of their type decouples the two problems (playtesting and developing AGI algorithms) advancing both independently. When it comes to developing new AGI algorithms for game-playing a crucial characteristic is the ability of expressing different behaviours. Most of the research has focused on peak performance game-playing agents, this research project instead focuses on producing agents that are able to show different playing styles (behaviours) with no explicit domain information embedded in the algorithm. Behavioural expressivity arises from the parameterisable components of an algorithm. In classical Statistical Forward Planning (SFP) it is very straightforward to adjust these, e.g. how far ahead it's planning. A very important component of SFP algorithms is the heuristic function used to evaluate the quality of game states. Being able to define heuristics in a game-agnostic manner is a key element in maintaining the algorithms generally. Email i.bravi@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): Program Committee and Subreviewers Evaluating and Enhancing Gameplay Behavioural Expressivity of Planning-Playing Artificial Intelligence for Automatic Playtesting Self-adaptive MCTS for General Video Game Playing Rinascimento: Playing Splendor-Like Games With Event-Value Functions Rinascimento: searching the behaviour space of Splendor Rinascimento: using event-value functions for playing Splendor Learning local forward models on unforgiving games Rinascimento: Optimising statistical forward planning agents for playing splendor A local approach to forward model learning: Results on the game of life game Game AI hyperparameter tuning in rinascimento Efficient evolutionary methods for game agent optimisation: Model-based is best Shallow decision-making analysis in general video game playing Evolving UCT alternatives for general video game playing Evolving game-specific UCB alternatives for general video game playing Themes Game AI Player Research - Previous Next

< Back Dr Miles Hansard Queen Mary University of London Supervisor Miles Hansard is a computer vision researcher, working on geometric and statistical methods for 3D scene understanding and rendering. He is also interested in active 3D sensing technologies, including depth cameras, lidar, and millimetre-wave radar. His recent projects include GPU methods for real-time atmospheric effects, commodity radar localization of UAVs, and grasp planning for robotic manipulation. He has also worked on human perceptual processes, including eye-movements, geometric judgements, and binocular stereopsis. Miles Hansard is a Senior Lecturer in computer graphics, and a member of the Vision Group and Centre for Advanced Robotics, at QMUL. He is available to supervise projects in the following areas: Simulation of complex physical effects (e.g. the motion of cloth, fire, and fluids), using machine learning. Physically plausible character animation in complex environments (e.g. slippery terrain), using machine learning. Email miles.hansard@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Game AI Game Data Immersive Technology - Previous Next

< Back Dr Athanasios Vasileios Kokkinakis University of York iGGi Alum Videogame Correlates of Real-Life Cognitive Traits Video-games have been increasingly gaining momentum and popularity, both with the public but also with the scientific world who has seen their usefulness in multiple areas. Researchers have been making bold claims of Videogames increasing Intelligence monopolizing the public’s attention and taking it away from what Videogames are excellent at; serving as diagnostic tools examining constructs such Reaction Times, Memory and fluid Intelligence. The sharp decline of the aforementioned concepts has been linked to multiple diseases such as the prodrome of Schizophrenia, Alzheimer’s and Dementia. Moreover, their measurement has been linked to important life outcomes such as Academic Achievement, Time in Unemployment, Unwanted Pregnancies and Mathematical Achievement among others. In my doctoral thesis I have correlated these constructs with the massively played video-game League of Legends. By cross-validating Psychometric measurements with Video-game metrics we can possibly identify at risk populations and stage Health Interventions or even identify “gifted” children or children that lag behind at an early age and place them in appropriate training curricula. He acquired his BSc in Psychology from the University of Bangor and he then went to complete his MSc in Cognitive Neuroscience at the University of York. In his first experiment he attempted to see whether “expert video-gamers” would show less Attentional Resources when compared to a control group of non-gamers and whether a short training session of approximately a week had any effects on the non-gamer group. His MSc, although not related to gaming, gave him valuable experience with EEG and MEG which he hopes to incorporate into his future experiments. In his most recent experiments he correlated psychometric Intelligence with Videogame Scores, more specifically League of Legends Tiers. He believes that these scores may give us insight on multiple developmental trajectories for instance healthy aging. Email athanasios dot kokkinakis *at* z)!gmail*com Website LinkedIn Mastodon BlueSky GitHub Other Link Prof. Alex Wade Prof. Peter Cowling Featured Publication(s): Data-Driven Audience Experiences in Esports Metagaming and metagames in Esports Videogame Correlates of Real Life Traits and Characteristics. Exploring the relationship between video game expertise and fluid intelligence Temporal and spatial localization of prediction-error signals in the visual brain What's in a name? Ages and names predict the valence of social interactions in a massive online game MEG adaptation resolves the spatiotemporal characteristics of face-sensitive brain responses Predicting skill learning in a large, longitudinal MOBA dataset Automatic Generation of Text for Match Recaps using Esport Caster Commentaries WARDS: Modelling the Worth of Vision in MOBA's DAX: Data-Driven Audience Experiences in Esports Time to die 2: Improved in-game death prediction in dota 2 Themes Esports Game AI Player Research Research Gate Google Scholar Previous Next

< Back Erin Robinson University of York iGGi PG Researcher Erin Robinson is a multimedia artist, experimental musician and PhD Researcher from London. Her work primarily involves the design of interactive installations, where she takes a participatory approach to evolving visual-scapes, but also takes form in fixed media, sound art, free improvisation, live visuals and immersive experiences. Her work critically engages with the concepts of posthumanism and postmodernism, exploring notions of authenticity and existence in the digital anthropocene by blurring lines between organic and non-organic entities, reality and virtuality, self and otherness. She is a founding member of SubPhonics, an experimental music and sound art collective based in London. Recent works include ‘Flora_Synthetica’, shown at Peckham Digital 2024, and ‘Pluriversal Perspectives: Moss’, shown at the South London Botanical Institute and Conference for Designing Interactive Systems (Copenhagen) 2024. A description of Erin's research: "My research adopts a practice-based approach to exploring participant-contributed materials, a technique positioned at the intersection of participatory and new media arts. This interactive technique enables participants to contribute aesthetic and semiotic materials to new media artworks through open forms of interaction, including but not limited to, text input, drawing, and video feed. Although both participatory and new media artistic practices involve audience engagement, traditional interactive media often impose restrictive computational frameworks. In contrast, participatory practices, typically conducted in person, allow participants greater freedom, resulting in deeper engagement and more diverse, unexpected outcomes that reflect the audience's perspectives and behaviours. This research underscores the potential of digital artworks to provide more expansive and identity-reflecting experiences by incorporating participant-contributed materials. By using strengths of participatory practices, digital artworks can achieve a richer and more personalised form of interaction, and meaningful engagement with audiences." Email erin.robinson@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Prof. Sebastian Deterding Themes Design & Development Immersive Technology - Previous Next

< Back Helen Tilbrook University of York iGGi Administrator iGGi Admin iGGi Administrator at York Email helen.tilbrook@york.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 Tania Dales University of York iGGi PG Researcher Available for placement Tania is an indie video game designer and developer, working with horror, science fiction and games which are a little strange, bizarre and uncomfortable. About Tania's research: "My research explores the relationship between humanoid character design and existential horror in video games. I adopt a mixed methods approach, investigating existing games, designer interviews and player surveys, along with a research-through-design methodology, reflecting on the practice of character design. The core games I am exploring incorporate themes of existential horror, identity, self, and human existence. In video games with horror themes, non-playable characters (NPCs) are often used to prompt a reaction from the player, and it isn’t always fear. There are often times when the NPC isn’t acting in an outwardly threatening way, yet it still causes us to become unsettled. My research explores unsettling NPCs that incorporate themes of existential horror." Email tania.dales@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Ben Kirman Themes Design & Development Game AI Immersive Technology Player Research - Previous Next

< Back Prof. Simon Lucas Queen Mary University of London iGGi Co-Investigator Supervisor Simon Lucas is a professor of Artificial Intelligence and Head of the School of Electronic Engineering and Computer Science at Queen Mary University of London where he also heads the Game AI Research Group. He holds a PhD degree (1991) in Electronics and Computer Science from the University of Southampton. He is the founding Editor-in-Chief of the IEEE Transactions on Games and co-founded the IEEE Conference on Games. His research involves developing and applying computational intelligence techniques to build better game AI, use AI to design better games, provide deep insights into the nature of intelligence and work towards Artificial General Intelligence. He is the QMUL lead for the EPSRC-funded CDT in Intelligent Games and Game Intelligence (IGGI). He has supervised more that 15 PhD students to completion, most of them in Game AI. Research themes: Game AI Agents (RL, Monte Carlo Tree Search, Rolling Horizon Evolution) Learning Forward Models Automated Game Design, Procedural Content Generation Game AI for real-world problem solving Email simon.lucas@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

< Back Dr Daniel Berio Goldsmiths iGGi Alum AutoGraff: A Procedural Model of Graffiti Form. (Industry placement at Media Molecule) The purpose of this study is to investigate techniques for the procedural and interactive generation of synthetic instances of graffiti art. Considering graffiti as a special case of the calligraphic tradition, I propose a "movement centric" alternative to traditional curve generation techniques, in which a curve is defined through a physiologically plausible simulation of a (human) movement underlying its production rather than by an explicit definition of its geometry. In my thesis, I consider both single traces left by a brush (in a series of strokes) and the extension to 2D shapes (representing deformed letters in a large variety of artistic styles). I demonstrate how this approach is useful in a number of settings including computer aided design (CAD), procedural content generation for virtual environments in games and movies, computer animation as well as for the smooth control of robotic drawing devices. Daniel Berio is a researcher and artist from Florence, Italy. Since a young age Daniel was actively involved in the international graffiti art scene. In parallel he developed a professional career initially as a graphic designer and later as a graphics programmer in video games, multimedia and audio-visual software. In 2013 he obtained a Master degree from the Royal Academy of Art in The Hague (Netherlands), where he developed drawing machines and installations materializing graffiti-inspired procedural forms. Today Daniel is continuing his research in the procedural generation of graffiti within the IGGI (Intelligent Games and Game Intelligence) PhD program at Goldsmiths, University of London. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Word-as-image for semantic typography Optimality Principles in the Procedural Generation of Graffiti Style SURFACE: Xbox Controlled Hot-wire Foam Cutter The role of image characteristics and embodiment in the evaluation of graffiti Emergence in the Expressive Machine The CyberAnthill: A Computational Sculpture Sketch-Based Modeling of Parametric Shapes Artistic Sketching for Expressive Coding Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks Sequence generation with a physiologically plausible model of handwriting and Recurrent Mixture Density Networks AutoGraff: Towards a computational understanding of graffiti writing and related art forms Kinematics reconstruction of static calligraphic traces from curvilinear shape features Interactive generation of calligraphic trajectories from Gaussian mixtures Sketching and Layering Graffiti Primitives. Kinematic Reconstruction of Calligraphic Traces from Shape Features Expressive curve editing with the sigma lognormal model Dynamic graffiti stylisation with stochastic optimal control Computer aided design of handwriting trajectories with the kinematic theory of rapid human movements Generating calligraphic trajectories with model predictive control Learning dynamic graffiti strokes with a compliant robot Computational models for the analysis and synthesis of graffiti tag strokes Towards human-robot gesture recognition using point-based medialness Transhuman Expression Human-Machine Interaction as a Neutral Base for a New Artistic and Creative Practice Themes Game AI - 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