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< Back Dr Yul HR Kang Queen Mary University of London Supervisor Yul Kang, MD, PhD is a computational cognitive neuroscientist studying how natural & artificial neural networks handle unavoidable uncertainty in sequential decision-making, such as wayfinding during navigation. He uses Bayesian approaches and probabilistic neural representation models, with applications to games, fundamental science, and healthcare. He received his MD in Seoul National University (South Korea), PhD in Columbia University (USA), and did postdoctoral research at the University of Cambridge (UK), where he was elected and served as a Junior Research Fellow. His work was published in top-tier journals such as Current Biology and eLife, and was presented as a talk in leading computational neuroscience conferences such as Cosyne and Bernstein Conference. His work was featured in news outlets such as The Independent. His research addresses how the brain handles unavoidable uncertainty (e.g., from ambiguous visual scene) during sequential decision-making (e.g., wayfinding). It helps understand players’ behaviour and predict their uncertainty given a map (and hence difficulty). Since neurological patients often show specific impairments in such tasks, it may help earlier and more specific diagnosis of diseases. Yul is interested in predicting players’ behaviour, procedural generation of levels by predicting subjective uncertainty and fun, and using games for diagnosis of psychiatric and neurological diseases. Email yul.kang@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game AI Immersive Technology Player Research - 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 Elena Gordon-Petrovskaya University of York iGGi Alum Elena specialises in novel forms of 'predatory' monetisation in digital games and its effects on players and is particularly interested in the links of game design to gaming disorder. She uses her background in psychology and human-computer interaction to take a player-centric perspective: developing knowledge bottom-up and working directly with players as the primary stakeholder. Her work spans ethics, wellbeing, and the lived experience of technology and its use. In her work so far, Elena has conducted a qualitative study with 1000+ players to create a taxonomy of microtransactions that players perceive to be unfair, aggressive, or misleading, and carried out a prevalence assessment of these techniques across the most popular desktop and mobile games. Most recently, her work discovered several types of harms which emerge from player interaction with games perceived as 'designed to drive spending'. Additionally, Elena has contributed to government calls for evidence around game regulation, given talks at seminar series and conferences, and collaborated on a variety of related topics, such as loot box spending, esports betting, and changes to gameplay during COVID. Email elepetrovs@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Sebastian Deterding Dr David Zendle Featured Publication(s): Learnings from the case Maple Refugee: A dystopian story of free-to-play, probability, and gamer consumer activism. Four dilemmas for video game effects scholars: How digital trace data can improve the way we study games Adapting and Enhancing Evolutionary Art for Casual Creation. The many faces of monetisation: Understanding the diversity and extremity of player spending in mobile games via massive-scale transactional analysis The relationship between psycho-environmental characteristics and wellbeing in non-spending players of certain mobile games Why microtransactions may not necessarily be bad: a criticism of the consequentialist evaluation of video game monetisation The lived experience of Internet Gaming Disorder: core symptoms, antecedents and consequences as based on a qualitative analysis of Reddit posts. Prevalence and Salience of Problematic Microtransactions in Top-Grossing Mobile and PC Games: A Content Analysis of User Reviews Predatory Monetisation? A Categorisation of Unfair, Misleading and Aggressive Monetisation Techniques in Digital Games from the Player Perspective Designing Personas for Expressive Robots: Personality in the New Breed of Moving, Speaking, and Colorful Social Home Robots A large-scale study of changes to the quantity, quality, and distribution of video game play during the COVID-19 pandemic How do loot boxes make money? An analysis of a very large dataset of real Chinese CSGO loot box openings Defining the esports bettor: evidence from an online panel survey of emerging adults The Battle Pass: a Mixed-Methods Investigation into a Growing Type of Video Game Monetisation Casual Creators in the Wild: A Typology of Commercial Generative Creativity Support Tools Not all fun and games: The design and evaluation of a game to increase intrinsic motivation in learning programming Exploring the multiverse of analysis options for the Addiction Stroop "These People Had Taken Advantage of Me”: A Grounded Theory of Problematic Consequences of Player Interaction with Mobile Games Perceived as “Designed to Drive Spending" Themes Player Research - Previous Next

< Back Dr Oliver Scholten University of York iGGi Alum Oliver Scholten is working on understanding the use of cryptocurrency technologies for gambling and gaming. His work provides researchers with the tools and context needed to understand player behaviours in these technologically advanced domains. He is the creator of gamba - a python library designed to enable quick replication of existing player behaviour tracking studies. He has also published several peer reviewed articles, and had written evidence published by the UK House of Lords which describes the mechanics behind decentralised gambling applications. As a PhD student, his thesis focuses on decoding and analysing cryptocurrency gambling and cryptocurrency gaming transactions. These transactions offer a more granular insight for researchers into both gambling and gaming than has been historically possible, this work therefore lays the foundations for explorations across different schools of research, and more specifically, advanced player transaction analytics. Please note: Updating of profile text in progress Email oliver@gamba.dev Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): On the Evaluation of Procedural Level Generation Systems On the Behavioural Profiling of Gamblers Using Cryptocurrency Transaction Data Inside the decentralised casino: A longitudinal study of actual cryptocurrency gambling transactions Decentralised Gambling Overview Decentralised Gambling: The York Combined Transaction Set Unconventional Exchange: Methods for Statistical Analysis of Virtual Goods Utilising VIPER for Parameter Space Exploration in Agent Based Wealth Distribution Models Ethereum Crypto-Games: Mechanics, Prevalence, and Gambling Similarities Themes Game Data - 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 Dr Memo Akten Goldsmiths iGGi Alum Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression. This research investigates how the latest developments in Deep Learning can be used to create intelligent systems that enhance artistic expression. These are systems that learn – both offline and online – and people interact with and gesturally ‘conduct’ to expressively produce and manipulate text, images and sounds. The desired relationship between human and machine is analogous to that between an Art Director and graphic designer, or film director and video editor – i.e. a visionary communicates their vision to a ‘doer’ who produces the output under the direction of the visionary, shaping the output with their own vision and skills. Crucially, the desired human-machine relationship here also draws inspirations from that between a pianist and piano, or a conductor and orchestra – i.e. again a visionary communicates their vision to a system which produces the output, but this communication is real-time, continuous and expressive; it’s an immediate response to everything that has been produced so far, creating a closed feedback loop. The key area that the research tackles is as follows: Given a large corpus (e.g. thousands or millions) of example data, we can train a generative deep model. That model will hopefully contain some kind of ‘knowledge’ about the data and its underlying structure. The questions are: i) How can we investigate what the model has learnt? ii) how can we do this interactively and in real-time, and expressively explore the knowledge that the model contains iii) how can we use this to steer the model to produce not just anything that resembles the training data, but what *we* want it to produce, *when* we want it to produce it, again in real-time and through expressive, continuous interaction and control. Memo Akten is an artist and researcher from Istanbul, Turkey. His work explores the collisions between nature, science, technology, ethics, ritual, tradition and religion. He studies and works with complex systems, behaviour, algorithms and software; and collaborates across many disciplines spanning video, sound, light, dance, software, online works, installations and performances. Akten received the Prix Ars Electronica Golden Nica in 2013 for his collaboration with Quayola, ‘Forms’. Exhibitions and performances include the Grand Palais, Paris; Victoria & Albert Museum, London; Royal Opera House, London; Garage Center for Contemporary Culture, Moscow; La Gaîté lyrique, Paris; Holon Design Museum, Israel and the EYE Film Institute, Amsterdam. Please note: Updating of profile text in progress Email memo@memo.tv Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Top-Rated LABS Abstracts 2021 Deep visual instruments: realtime continuous, meaningful human control over deep neural networks for creative expression Deep Meditations: Controlled navigation of latent space Learning to see: you are what you see Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks Mixed-initiative creative interfaces Learning to see Real-time interactive sequence generation and control with Recurrent Neural Network ensembles Collaborative creativity with Monte-Carlo Tree Search and Convolutional Neural Networks Sequence generation with a physiologically plausible model of handwriting and Recurrent Mixture Density Networks Deepdream is blowing my mind All watched over by machines of loving grace: Deepdream edition Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks Themes Game AI - Previous Next

< Back Gorm Lai Goldsmiths iGGi PG Researcher Inspired by the works of Karl Sims and William Latham as well games such as a Spore and No Man's Sky, Gorm's main work is focused on using artificial intelligence and machine learning to generate creatures for use in video games. Combining this with his background as a virtual reality pioneer, his full doctorate is looking into how mixed-initiative co-creative interfaces in vr can assist in creating procedural generated creatures for use in video games. As a stalwart of the game development community, Gorm ran the Danish chapter of the International Game Developer Association (IGDA) for 5 years, started the London Indie Game Developers meetup group which currently features almost 3000 members, co-founded the Nordic Game Jam, as well as the Global Game Jam. The Global Game Jam has been recorded into the Guinness Book of World Records, and has more participating countries than the Winter Olympics. Gorm is a games industry veteran who has worked on 17 commercial video games since 2004, and has spoken at numerous games industry conferences such as GDC, Nordic Game & Develop Brighton. Gorm is a student at Goldsmiths, University of London, where is he is supervised by William Latham and Frederic Fol Leymarie. Email lai.gorm@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Prof. William Latham Featured Publication(s): Formal Constraints and Creativity: Connecting Game Jams, Dogma ’95, the Demo Scene, OuBaPo, and Renga poets What Is a Game Jam? The Dark Side of Game Jams On Mixed-Initiative Content Creation for Video Games Two decades of game jams Virtual Creature Morphology‐A Review Towards Friendly Mixed Initiative Procedural Content Generation: Three Pillars of Industry Introducing: the game jam license Trends in organizing philosophies of game jams and game hackathons The global game jam for teaching and learning Gplayer A compression method for spectral photon map rendering Themes Creative Computing Design & Development Game AI - Previous Next

< Back Sarah Masters University of York iGGi PG Researcher Available for post-PhD position Sarah is an artist, game developer and researcher. They have an MA in Indie Game Development from Falmouth University (Distinction). They are an active part of the games community taking part in game jams and running their own commercially focused game studio working on the debut title Moth Terra. A description of Sarah's research: Sarah’s work takes a research-through-design approach focused on exploring meaning in games and ecogames. Alongside a portfolio of games, their previous work includes running a workshop on Solarpunk vs Grimdark concepts, presenting the Cute Ecologies talk Moth Magic, and contributing to the development of Treescapes: A NERC-Funded Mobile Game exploring the social, cultural, and emotional values of trees. Their work also explores sustainable design approaches to games and interactive experiences. Email sarah.masters@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Featured Publication(s): Radical Alternate Futurescoping: Solarpunk versus Grimdark Better Dead than a Damsel: Gender Representation and Player Churn Themes Applied Games Design & Development Player Research Eudaimonia: A solarpunk city-building choice and consequence game - Save the world in eight years!: https://www.youtube.com/watch?v=_zKcgFluR24 Fatalis - a witchy gardening game: https://www.youtube.com/watch?v=kR_OMidgk14 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 Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games - Previous Next

< Back Dr Mariana Lopez University of York Supervisor Dr Mariana Lopez is a researcher in the field of sound design. She works on two main fields: accessibility and heritage. Her work on accessibility focuses on how sound design can be used to create accessible experiences for film and television audiences with sight loss, providing an alternative to traditional Audio Description practices. She was the Principal Investigator of the project Enhancing Audio Description funded by the AHRC. In the field of heritage, she focuses on acoustical heritage, by exploring how acoustic measurement techniques, computer modelling and the recreation of soundscapes can help us understand the sonic experiences of our ancestors. She was the Principal Investigator of the British Academy-funded project – The Soundscapes of the York Mystery Plays. Related to these fields she is supervising and has supervised projects in the field of mental health in connection to the creative arts; interactive installations; serious gaming and its impact on sustainability; accessibility and gaming; and sound design in participatory theatre, among others. Research themes: Game Audio and Music Games with a Purpose Sound and accessibility Equality and social justice Acoustical heritage Sound installations Email mariana.lopez@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Game Audio - Previous Next

< Back Dr Tom Collins University of York Supervisor Tom runs the Music Computing and Psychology Lab in the Music Department at University of York, and so makes a good supervisor for game audio projects, but he has wider interests in media (e.g., podcasts) and sport (especially football), and in sport how AI can be leveraged to enhance analytics that lead to new insights into, and competitive advantages in, individual and team performance. Tom is internationally recognised for his work in automatic music generation, web systems for music, and information retrieval. His research has been featured by the BBC (BBC Click), The Times, and Financial Times among others. Tom is interested in supervising students who have a background in at least one of the following areas, and who are interested in acquiring knowledge of the others: Data science and machine learning (especially deep learning); One of music, podcasts, or sport; Software engineering (especially full-stack JavaScript development). Email tom.collins@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Esports Game AI Game Audio Game Data Player Research - Previous Next

< Back Prof. Simon Colton Queen Mary University of London iGGi Co-Investigator Supervisor Simon Colton is an AI researcher with particular focus on issues of Computational Creativity, where we engineer software to take on creative responsibilities in art and science projects. He undertakes projects advancing the state of the art in generative technologies such as evolutionary approaches and deep learning, and uses these to help develop software such as The Painting Fool, The WhatIf Machine, the Wevva game designer, the HR3 automated code generator, and the Art Done Quick casual creator for visual art. In turn, these software systems and their output are used in cultural projects such as a poetry readings, art exhibitions, game jams, and even the production of a West-End musical. This enables Simon to undertake much public engagement, with coverage from the BBC, The Guardian, MIT Tech Review, The New Scientist and many others. These practical and cultural projects inform an evolving philosophical discourse around what it means for machines to be creative, and Simon has co-authored numerous essays driving forward our understanding of this important topic. In this way, he has helped to introduce ideas such as automated framing of products and processes, issues of authenticity and the notion of the machine condition, i.e., what the lived experience of a machine is, and how this could be expressed by that machine through creative production. He is particularly interested in supervising students in project where we apply generative technologies to applications in videogame design, visual art, software engineering, music and text generation. One particular current interest is stretching the boundaries of both what can be achieved by, and our understanding of, generation deep learning methods such as generative adversarial networks (GANs) and auto encoders. Another current interest is the design of casual creators, which are creativity support tools where the focus is on users having fun, rather than on efficient, professional production of artefacts. He is currently developing a casual creator for visual art called Art Done Quick for public release, which employs evolutionary and deep learning techniques to deliver a fun-first experience while users make decorative art pieces. Any project involving generative technologies is of interest to Simon. Research Areas: Game AI Game Audio and Music Game Design Computational Creativity Player Experience Casual Creators Generative Deep Learning Email s.colton@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Accessibility Creative Computing Game AI Game Audio Player Research - Previous Next