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< Back Dr Anna Bramwell-Dicks University of York Supervisor Anna Bramwell-Dicks has an interdisciplinary background which started in Electronics and Music Technology before taking a sideways move to the field of Human-Computer Interaction research. She likes to combine her underlying interest in sound and music with applied psychology and creativity. She is very interested in research involving multimodal interaction (e.g. using audio, haptics, smell and/or proprioception as well as visuals within interfaces) particularly where audio is used to affect user’s behaviour or experiences. She is also very interested in accessibility research and any research in the application area of mental health and mental illness. As a lecturer in Web Development and Interactive Media, based in TFTI, Anna is always interested in work that involves designing and evaluating novel and interesting user experiences, particularly where that leads to the option to create fun, engaging, accessible experiences. She likes to work across a range of application areas ranging from learning environments to e-commerce to escape rooms and cultural exhibits! Anna is keen to work with students who want to design and develop gamified systems to support people with disabilities, physical or mental illness. Or, those who are also interested in multimodal experiences. Research themes: Accessibility Multimodal and multisensory systems Research methods anna.bramwell-dicks@york.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/anna-bramwell-dicks-2b941a28/ LinkedIn BlueSky Github Themes Accessibility Applied Games Design & Development Game Audio 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 Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): 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 Ryan Spick University of York iGGi Alum Deep Learning for Procedural Content Generation in Virtual Environments Ryan Spick is a PhD student with a computer science background, working on methods to improve how content (models, terrain, assets etc.) is created with an autonomous focus, with the main focus on generative deep learning to augment real-world data through a series of neural network layers to learn unlying properties of these data. Ryan has published a variety of papers around his main topic of generating content, such as terrain generation using generative adversarial networks and 3D voxel coloured model generation, to collaborations on other topics using deep learning, such as death prediction in a multiplayer online game and applying a recent map-elites algorithm. He has also worked with several leading industry researchers/games companies to further develop his research skill.If you have any ideas or collaboration opportunities please get in contact through any of the mediums below. Please note: Updating of profile text in progress ryan.spick@hotmail.co.uk Email Mastodon https://www.rjspick.com/ Other links Website https://www.linkedin.com/in/ryan-spick-505b63131/ LinkedIn BlueSky Github Featured Publication(s): System and Method for Point Cloud Generation System and method for training a machine learning model Robust Imitation Learning for Automated Game Testing Behavioural Cloning in VizDoom Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Utilising VIPER for Parameter Space Exploration in Agent Based Wealth Distribution Models Human Point Cloud Generation using Deep Learning Naive mesh-to-mesh coloured model generation using 3D GANs Realistic and textured terrain generation using GANs Procedural Generation using Spatial GANs for Region-Specific Learning of Elevation Data Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Time to die: Death prediction in dota 2 using deep learning Themes Game AI - Previous Next

< Back Luiza Gossian Queen Mary University of London iGGi PG Researcher Available for placement Luiza is a multidisciplinary researcher, game designer and developer interested in translating real world concepts into engaging game mechanics. She is passionate about creating games that can encourage an understanding of ourselves and the socially connected world we live in. Luiza is also an experienced painter, graphic designer and photographer and uses her visual skills and psychology background to prototype experimental game designs, design game documentation and craft atmospheric experiences. A description of Luiza's research: How can a subject as serious as genocide be successfully and respectfully translated into a casual game? Difficult subjects are often implemented with polar opposite approaches in games: either they are made to be highly emotional, socially conscious games that portray the gravity of a situation, yet are only played by those already informed and aware; or they are pure entertainment games that turn these subjects into wild amusement parks that appeal to broader gamer audiences yet do nothing to appropriately address the themes they glorify. Within this polarity there exists the potential to create games that tackle more serious subjects yet do so in a way that is more lighthearted and entertaining, and therefore more likely to reach the audiences who stand to gain the most. In her research, Luiza is exploring how to design games about genocide that break away from traditional approaches and embrace the ludic potential of games. Drawing on theories of intergroup and cultural psychology, as well as her own experiences, she is exploring how these difficult themes can be explored in engaging, effective and informative ways. Currently, she is developing a hypercasual game that abstracts the ten stages of genocide to be used as an educational primer, a Tetris-esq game that uses social media and government sources to present the realities of refugees fleeing their homes, and a cosy mystery-adventure game which enables players to uncover historical crimes in a far away land. l.gossian@outlook.com Email Mastodon http://www.gossianblurs.com/ Other links Website https://www.linkedin.com/in/lu-goss/ LinkedIn https://bsky.app/profile/lugossian.bsky.social BlueSky Github Supervisors: Prof. Sebastian Deterding Dr Anne Hsu Themes Applied Games Design & Development - Previous Next

< Back Dr James Goodman Queen Mary University of London iGGi Alum James has picked up degrees in Chemistry, History, Mathematics, Business Administration and Machine Learning. After a career in Consultancy and IT Project Management he is now finally doing the research he always wanted to. James is interested in opponent modelling, theory of mind and strategic communication in multi-player games, and how statistical forward planning can be used in modern tabletop board-games (or other turn-based environments). With a constrained budget, how much time should an agent spend thinking about it's own plan versus thinking about what other players might be doing to get in the way. How does this balance vary across different games? His secondary research interests are in using AI-playtesting as a tool for game-balancing and game-design. james.goodman@qmul.ac.uk Email Mastodon https://www.tabletopgames.ai/ Other links Website https://www.linkedin.com/in/james-goodman-b388791/ LinkedIn BlueSky Github Supervisors: Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): Seeding for Success: Skill and Stochasticity in Tabletop Games From Code to Play: Benchmarking Program Search for Games Using Large Language Models Skill Depth in Tabletop Board Games Measuring Randomness in Tabletop Games A case study in AI-assisted board game design Following the leader in multiplayer tabletop games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games MultiTree MCTS in Tabletop Games Visualizing Multiplayer Game Spaces TAG: Terraforming Mars Fingerprinting tabletop games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games AI and Wargaming Metagame Autobalancing for Competitive Multiplayer Games Does it matter how well I know what you’re thinking? Opponent Modelling in an RTS game Weighting NTBEA for game AI optimisation Re-determinizing MCTS in Hanabi Noise reduction and targeted exploration in imitation learning for abstract meaning representation parsing UCL+ Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound Themes Design & Development Game AI - Previous Next

< Back Dr Patrik Huber University of York Supervisor Patrik Huber is a researcher, developer and entrepreneur, working on 3D face reconstruction and face analysis in images and videos using 3D face models. He is a Lecturer (Assistant Professor) in Computer Vision in the Department of Computer Science of the University of York, UK, and he’s the Founder of 4dface.io, a small start-up specialising in 3D face models and realistic 3D face avatars for professional applications. His research is focused on computer vision, in particular, he is interested in the question of how to robustly obtain a metrically accurate, pose-invariant 3D representation of a face from 2D images and videos. He is interested in face tracking, 3D face modelling, analysis and synthesis, metrically accurate 3D face shape reconstruction, inverse rendering, and combining deep learning with 3D face models. Patrik is particularly interested in supervising students with a strong background and interest in computer vision, machine learning, computer graphics, and modern C++/Python, on topics related to creating 3D face avatars of players for immersive playing and social experiences , and using face analytics for professional e-sports . Research themes: 3D face avatars for games AR/VR Serious games and social interaction Immersive 3D player experiences Game Analytics Games with a Purpose E-Sports patrik.huber@york.ac.uk Email Mastodon https://www.patrikhuber.ch/ Other links Website https://www.linkedin.com/in/patrik-huber/ LinkedIn BlueSky https://github.com/patrikhuber Github Themes Applied Games Esports Game Data Immersive Technology Player Research - Previous Next

< Back Prof. Marian Ursu Goldsmiths Supervisor Marian Ursu has a first degree in Computer Science, a PhD in Artificial Intelligence, and has worked over the past twenty years in the development of new forms of mediated expression and interaction, in the space of convergence of digital technology with creative practice. He worked at Goldsmiths, University of London, pioneering “creative computing”, a term denoting a fundamental link between digital technologies, the arts and media. At York, he led the development of the Interactive Media subject area in the department of Theatre Film Television and Interactive Media, inherently interdisciplinary, building on Computer Science, User Experience Design, Media Practice and Cultural Studies. He is a co-founder and the Director of the Digital Creativity (DC) Labs ( https://digitalcreativity.ac.uk ), a centre of excellence in impact-driven research in creativity for games, narrative media and the rich space of media convergence that lies in between, and Co-Director of XR Stories ( https://xrstories.co.uk ), a creative industries partnership working across film, TV, games, media arts, heritage, advertising and technology to champion a new future in storytelling, in which he leads on Research and Development. His personal research is situated in the area of narrative experiences in scree media – shared screens (film, TV), personal screens (games, social media), stories in VR, XR narrative experiences – drawing from and building on established narrative art-forms and media including film and TV, radio, theatre, and opera. One of his key research objective is to explore the creative process that emerges in dialogue between humans and machines (AI). On one hand, this is necessary for the authoring of more complex narrative experiences that truly exploit the affordances of interactive and immersive digital media technologies. On the other hand, this is a yet poorly untapped space of opportunities, potentially conducive to significant findings. He is particularly interested in supervising students interested in exploring creativity in dialogue with AI and/or the development of novel narrative experiences, in topics including: Conceptualising the space of interactive storytelling Developing authoring tools and techniques for interactive storytelling Creating new forms of narrative engagement Analysing the concept of creativity in interactive media which emerges in conversation with AI Research themes: Narrative Games; Narrative Experiences Storytelling with Convergent Media Object-Based Media Computational Creativity Live mediated experiences (performance, sports, esports) Entertainment media and mental health Games and Theatre marian.ursu@york.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/marianursu/?originalSubdomain=uk LinkedIn BlueSky Github Themes Creative Computing Player Research - Previous Next

< Back Remo Sasso Queen Mary University of London iGGi PG Researcher I hold a BSc and MSc in Artificial Intelligence at the University of Groningen (NL) and am currently a PhD student at the Queen Mary University of London under the supervision of Paulo Rauber. In addition to my academic work, I have worked as a Machine Learning engineer, and am currently the Head of AI at xDNA, an AI/Cybersecurity-based start-up from the Netherlands. Here I'm leading the initiative Project Aletheia, where we develop AI-driven tools to optimize the workflow of professional fact-checkers, with the overarching goal of ensuring information integrity in the world. Foundation World Models and Foundation Agents for Reinforcement Learning My research focuses on developing reinforcement learning algorithms that are both scalable and sample-efficient through Bayesian methods and model-based approaches, recently with a particular emphasis on Large Language Models (LLMs). My previous research focused on principled, efficient and scalable exploration algorithms for reinforcement learning, e.g. Poster Sampling for Deep Reinforcement Learning (ICML 2023), where we developed a reinforcement learning algorithm that can be considered state-of-the-art in Atari games. Currently I'm particularly interested in the integration of LLMs in the reinforcement learning framework, both as decision-making agents and simulators. My current research, called "Foundation World Models and Foundation Agents for Reinforcement Learning" investigates this integration in-depth and shows that large models show significant potential in various reinforcement learning tasks, ranging from decision-making in stochastic environments to serving as world models. r.sasso@qmul.ac.uk Email https://remosasso.github.io/ Mastodon Other links Website https://www.linkedin.com/in/remo-sasso-b9837a1ba/ LinkedIn BlueSky https://github.com/remosasso Github Supervisor: Dr Paulo Rauber Featured Publication(s): VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts Making Connections: Neurodevelopmental Changes in Brain Connectivity after Adverse Experiences in Early Adolescence Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning Simultaneous multi-view object recognition and grasping in open-ended domains Posterior Sampling for Deep Reinforcement Learning Themes Game AI - 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

< Back Dr Michael Saiger University of York iGGi Alum Available for post-PhD position Michael is a game design researcher investigating how we engage players (particularly young people) in the design and development of applied games. He has facilitated co-design workshops across health and education research, designing solutions to research problems. Most recently, he was employed as a game design researcher on an ESRC funded project to design and evaluate a game for teacher recruitment. A description of Michael's research: Michael's research involves the facilitation and involvement of children and young people in the design of mental health games. Through their research, they have co-designed mental health prototypes and explored the factors to impact participation and engagement. Their research has highlighted how there are facilitation barriers and shifts in participant preferences towards how young people want to interact during co-design. michael.saiger@york.ac.uk Email https://linktr.ee/MichaelJohnSaiger Mastodon https://micia1592.wixsite.com/mikethingsbetter Other links Website https://www.linkedin.com/in/mjsaiger/ LinkedIn BlueSky Github Supervisors: Dr Joe Cutting Prof. Sebastian Deterding Dr Lina Gega Featured Publication(s): Use of Technology in Brief Interventions How Do We Engage Children and Young People in the Design and Development Of Mental Health Games Children and Young People's Involvement in Designing Applied Games: Scoping Review What Factors Do Players Perceive as Methods of Retention in Battle Royale Games? Themes Applied Games Design & Development Player Research - Previous Next

< Back Dr Daniel Hernandez University of York iGGi Alum With the games industry as his target, Daniel Hernandez’s main research objective is to design and implement algorithms that, without any prior knowledge, generate strong gameplaying agents for a wide variety of games. To tackle this “from scratch” learning, he uses, and contributes to, the fields of Multiagent Reinforcement Learning, Game Theory and Deep learning. Self-play is the main object of study in his research. Self-play is a training scheme for multiagent systems in which AIs are trained by acting on an environment against themselves or previous versions of themselves. Such training scheme bypasses obstacles faced by many other training approaches which rely on existing datasets of expert moves or human / AI agents to train against. Daniel’s hope is that further development in Self-play will allow game studios of all sizes to generate strong AI agents for their games in an affordable manner. A storyteller by nature, Daniel has a strong track record of outreach through talks and workshops both in the UK and internationally. By sharing his journey, insights and discoveries he hopes to both inspire and instruct students, researchers and developers to realise the potential that Reinforcement Learning has to improve the games industry. His passionate work on Machine learning goes beyond crafting strong gameplaying agents. He sees the potential of using AI to simplify and automate a wide range of tasks in the games industry. He has led successful projects which used machine learning aimed at automating multiagent game balancing to alleviate the burden of manual game balancing. Daniel received an MEng in Computing: Games, Vision & Interaction from Imperial College London. Wanting to combine the power of AI and the creativity of videogames, Daniel began a PhD journey to explore the misty lands of Multi Agent Reinforcement Learning (MARL). Please note: Updating of profile text in progress Email Mastodon https://danielhp95.github.io Other links Website https://www.linkedin.com/in/dani-hernandez-perez-1106b2107 LinkedIn BlueSky https://github.com/Danielhp95 Github Featured Publication(s): A comparison of self-play algorithms under a generalized framework A generalized framework for self-play training Metagame Autobalancing for Competitive Multiplayer Games Themes Game AI Player Research - Previous Next

< Back Dr Shringi Kumari University of York iGGi Alum Shringi is a seasoned game designer with more than nine years of experience making games for companies including EA, Zynga, Bigpoint, and Wooga. She became a researcher four years ago, wondering how game designers can take inspiration from other creative fields. In her PhD, she is now studying how stage magic can be translated to games for creating believable illusions of choice and moments of surprise. She continues to consult as a game designer for companies and has started a lecturership in game design at University of East London. In the past years she has spoken about game design across the world at a number of known platforms: Indiecade Europe, Develop, Game Happens, SOMA Chicago, GDC India to count some. As a creative, she engages in working on disruptive design both in games and beyond. Her work reflects her Indian background and discusses universal issues of identity, need for diversity and the idea or illusion of home. She has recently published her debut poetry collection,“The Saree Shop” and has featured in a short story anthology with her story ”Garden of Vaginas”. Shringi is supervised by Dr Sebastian Deterding (York) and Dr Gustav Kuhn (Goldsmiths). Please note: Updating of profile text in progress Email Mastodon https://shringikumari.com Other links Website https://www.linkedin.com/in/shringi-kumari-8613678 LinkedIn BlueSky Github Featured Publication(s): The role of uncertainty in moment-to-moment player motivation: a grounded theory Why game designers should study magic Investigating uncertainty in digital games and its impact on player immersion Studying General Agents in Video Games from the Perspective of Player Experience The Magician's Choice: Providing illusory choice and sense of agency with the Equivoque forcing technique. Design Inspiration for Motivating Uncertainty in Games using Stage Magic Principles Themes Player Research - Previous Next