Search Results

< Back Nirit Binyamini Ben Meir Queen Mary University of London iGGi PG Researcher Available for placement Nirit Binyamini Ben-Meir is a designer/ artist based in London. Her work explores the interconnection between society, technology and ecology. She is an Associate Lecturer at the Royal College of Art London, where she gained her MA in Information Experience Design. She has a professional background in visual communication and interaction design. She uses participatory installations, digital tools and responsive plants to create experiences for humans to interact with their biosphere. She combines ecological systems with technology to challenge human perception and provoke thought about bioethics, power relations, and the Anthropocene implications. Nirit’s main research interests are around More-Than-Human Interactions and the integration of living organisms into digital interactions. She investigates how these hybrid interactions may help mediate relatable, sensory experiences with plants and influence people's attitudes towards ecological stewardship. She is developing the Bio-Digital Garden concept, which combines computational elements and living moss, a responsive plant that gives qualitative visual feedback to changes in its environment in real-time. Her exploration focuses on the potential of using human-computer-plant to identify current weak points in pro-environmental behaviour and care for non-human entities, as well as influence people's perceived accountability through tangible feedback, bridging time-scale gaps, and generating a sense of urgency. n.binyaminiben-meir@qmul.ac.uk Email Mastodon https://niritbin.com/ Other links Website LinkedIn BlueSky Github Supervisors: Prof. Sebastian Deterding Featured Publication(s): Domestic Cultures of Plant Care: A Moss Terrarium Probe Experience as a transformational practice Design Methods for Accessing the Pluriverse Forging new narratives Themes Applied Games Creative Computing Design & Development - Previous Next

< Back Dominik Jeurissen Queen Mary University of London iGGi PG Researcher Hey, I'm Dominik Jeurissen, and I'm passionate about both software engineering and machine learning, with a particular interest in fully autonomous agents that do not rely on absurd amounts of data. My focus areas include reinforcement learning, unsupervised learning, and the emerging capabilities of large language models. I earned my MSc in Artificial Intelligence from Maastricht University and my BSc in Computer Science with a focus on Applied Mathematics from RWTH Aachen. During my undergraduate studies, I worked as a software engineer at INFORM GmbH, contributing to their supply management software, add*ONE. A description of Dominik's research: My PhD is a collaboration with Creative Assembly , focusing on researching AI for complex strategy games, such as Total War. With the recent emergence of Large Language Models (LLMs), I’m exploring their potential to enhance game-playing agents. LLMs can instantly recall knowledge on almost any topic (though not without occasional errors), perform basic reasoning, and are easily configured for a wide range of text-based tasks. These abilities make them especially promising for game development, where machine learning agents often struggle due to constantly changing game environments. d.jeurissen@qmul.ac.uk Email https://commandercero.github.io/ Mastodon Other links Website https://www.linkedin.com/in/dominik-jeurissen/ LinkedIn https://bsky.app/profile/dominikjeurissen.bsky.social BlueSky https://github.com/CommanderCero Github Supervisors: Dr Diego Pérez-Liébana Dr Jeremy Gow Featured Publication(s): Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Generating Diverse and Competitive Play-Styles for Strategy Games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Automatic Goal Discovery in Subgoal Monte Carlo Tree Search Game state and action abstracting monte carlo tree search for general strategy game-playing Portfolio search and optimization for general strategy game-playing The Design Of" Stratega": A General Strategy Games Framework Themes Design & Development Game AI Game Data - Previous Next

< Back Dr Kevin Denamganaï University of York iGGi Alum Available for post-PhD position 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. kevin.denamganai@york.ac.uk Email Mastodon https://kevindenamganai.netlify.app/ Other links Website LinkedIn BlueSky https://github.com/Near32/ Github Supervisor(s): Dr James Walker Featured Publication(s): 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 Thryn Henderson University of York iGGi Alum Thryn’s phd explored the practices of personal vignette games, with a particular interest in the vignette game’s approaches to digital persona, their roots in approachable DIY culture, and their importance to marginalised creators. Publications from their work can be found in the Digra 2020 archive and Persona Studies Volume 6, Issue 2 . Thryn’s interest in gaming grows from a delight in telling stories. They endeavour to find the spaces where play incorporates and encourages collaborative narrative, poetry, theatre, activism, subversion, surprise and expression. Most of Thryn’s work in playful media can be found in zines, cardboard installations, paper games, hidden screens, or roaming through the woods around the UK. They are a co-founder of the playful design co-operative Furtive Shambles, currently producing experimental live and tabletop game experiences. thrynhenderson@gmail.com Email Mastodon https://furtiveshambles.com Other links Website LinkedIn BlueSky Github Themes Design & Development - Previous Next

< Back Dr Diego Pérez-Liébana Queen Mary University of London iGGi Industry Liaison Supervisor Born in Madrid (Spain) and living in London (United Kingdom), I am a Senior Lecturer in Computer Games and Artificial Intelligence at Queen Mary University of London. I hold a PhD in Computer Science from the University of Essex (2015) and a Master degree in Computer Science from University Carlos III (Madrid, Spain; 2007). My research is centered in the application of Artificial Intelligence to games, Tree Search and Evolutionary Computation. At the moment, I am especially interested on General Video Game Playing and Strategy games, which involves the creation of content and agents that play any real-time game that is given to it, and research in Abstract Forward Models. I have recently been awarded with an EPSRC grant on Abstract Forward Models for Modern Games. I am author of more than 100 papers in the field of Game AI, published in the main conferences of the field of Computational Intelligence in Games and Evolutionary Computation. I have publications in highly respected journals such as IEEE TOG and TEVC. I have also organised international competitions for the Game AI research community, such as the Physical Travelling Salesman Competition, and the General Video Game AI Competition, held in IEEE (WCCI, CIG) and ACM (GECCO) International Conferences. I also experience in the videogames industry as a game programmer (Revistronic; Madrid, Spain), with titles published for both PC and consoles. I worked as a software engineer (Game Brains; Dublin, Ireland), where I oversaw the development of AI tools that can be applied to the latest industry videogames. I am particularly interested in supervising students with background on applications of Tree Search or Evolutionary Algorithms for strategy games. Research Themes: Game AI Rolling Horizon Evolutionary Algorithms. Monte Carlo Tree Search Statistical Forward Planning methods. Strategy Games. diego.perez@qmul.ac.uk Email Mastodon https://diego-perez.net Other links Website https://www.linkedin.com/in/diegoperezliebana/ LinkedIn BlueSky https://github.com/diegopliebana Github Themes Game AI Game Data - Previous Next

< Back James Gardner University of York iGGi PG Researcher I am a third-year PhD student at The University of York, specialising in computer vision and machine learning for 3D scene understanding. Supervised by Dr William Smith, my research focuses on neural-based vision and language priors in inverse rendering and scene representation learning. I'm particularly interested in neural fields, generative models, 3D computer vision, differentiable rendering, geometric deep learning, multi-modal models, and 3D scene understanding in general. My research has been recognised with publications at prestigious conferences including NeurIPS and ECCV. Currently, I am working as a research fellow on the ALL.VP project, funded by BridgeAI and Dock10, developing relightable green screen performance capture using deep learning and inverse rendering techniques. This work aims to provide greater creative control to film and TV productions without requiring expensive LED volumes or post-production. I hold an MEng in Electronic Engineering from The University of York, for which I was awarded the IET Prize for outstanding performance and the Malden Owen Award for the best-graduating student on an MEng programme. A description of James' research: My research lies at the intersection of computer vision, machine learning, and 3D scene understanding, with a particular focus on neural-based approaches and the integration of vision and language priors. My work spans a range of topics including neural fields, generative models, differentiable rendering, and geometric deep learning. A key theme in my research is the use of 3D inductive biases for inverse rendering, addressing challenges such as illumination estimation, albedo/geometry disentanglement, and shadow handling in complex outdoor scenes. I've made contributions in creating a rotation-equivariant neural illumination model and spherical neural models for sky visibility estimation in outdoor inverse rendering. Additionally, my work extends to learning rotation-equivariant latent representations of the world from 360-degree videos, aimed at advancing the field of 3D scene understanding and developing models with an understanding of core physical principles such as object permanence. Through my research, I aim to build computer systems capable of deeply comprehending the 3D world, utilising self-supervised, generative, and non-generative approaches to push the boundaries of what's possible in computer vision and scene representation learning. james.gardner@york.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/jadgardner/ LinkedIn BlueSky https://jadgardner.github.io/ Github Featured Publication(s): The Sky's the Limit: Relightable Outdoor Scenes via a Sky-Pixel Constrained Illumination Prior and Outside-In Visibility Themes Game AI - Previous Next

< Back Francesca Foffano University of York iGGi PG Researcher Available for post-PhD position Francesca's work represents her fascination with how players elaborate and understand complex situations in video games. She likes to use mixed methods (both qualitative and quantitative) to understand high-level player perception in video games using her competencies in HCI (MSc at the University of Trento) and Psychology (BSc at the University of Padua). Prior to joining the PhD, she developed international experience in industry and research. She worked as Research Fellow on AI and ethics for the European project AI4EU at ECLT (Ca' Foscari University of Venice) and on players' perception of adaptive videogames at Reykjavik University. She also was involved as UX Strategist in creative content for MediaMonks headquarter (Amsterdam). A description of Francesca's research: Players will tell you exactly when they got stuck playing a game, but how we define stuck in the first place is still open to discussion. This PhD research aims to identify how and when this happens to help in predicting when players need support. The goal is to smoothen the player experience by reducing the need for external support (such as online guides, walkthroughs, and online forums) that might affect player immersion. The current stage of the research uses in-depth interviews to understand what players have in common, no matter what task they are doing or game they are playing. So why rely on user tests that consider singular test cases instead of understanding where they originate? ff716@york.ac.uk Email Mastodon https://ffoffano.wordpress.com/about/ Other links Website https://www.linkedin.com/in/foffanofrancesca/ LinkedIn https://bsky.app/profile/francescafoffano.bsky.social BlueSky Github Supervisor: Prof. Paul Cairns Featured Publication(s): A Survey on AI and Ethics: Key factors in building AI trust and awareness across European citizens. When Games Become Inaccessible: A Constructive Grounded Theory on Stuckness in Videogames Artificial intelligence across europe: A study on awareness, attitude and trust When Games Become Inaccessible: A Constructive Grounded Theory on Stuckness in Videogames Investing in AI for social good: an analysis of European national strategies European Strategy on AI: Are we truly fostering social good? Changes of user experience in an adaptive game: a study of an AI manager Themes Player Research - Previous Next

< Back Dr Ben Kirman University of York iGGi Training Coordinator Supervisor Available to supervise non-iGGi students for 2024 intake Ben is a Senior Lecturer (Associate Prof) in Interactive Media at the University of York, who has over 20 years' experience as a creative technologist. Since his first programming job fixing Y2K bugs (you're welcome), he has worked with dozens of organisations, large and small, in design and prototyping playful experiences. His research uses game design and playful design as a way to explore the complex effects of emerging technologies through novel and unexpected interactions and experiences. Most often, this is through the design and development of games, digital/physical prototypes, and design fictions. Ben has applied this in topics ranging from immersive theatre, dog technology, non-league football, radical cycle delivery, and time travelling robots, to educational games, esports, new situationism and magic. The unifying theme is play – as a topic of study, a way of working, for research insight, and as expression or output in games or playful experiences. This work, especially the more bizarre stuff, has often been covered by traditional media, including the BBC, New Scientist, Wired, The Guardian, TIME, Metro, the New York Times, and Your Cat magazine. Ben is keen on supervising students with strong creative drives, with an interest in making, design, experimentation, and a broad perspective on games and play. This might be a project about playful props in immersive theatre, or a project about context in locative and site-specific games, or any other project that looks to explore new possibilities and new implications of emerging technology through the lens of play. Research themes include: Game Design Applied Games Computational Creativity Sports with an E and without an E Player Experience ben.kirman@york.ac.uk Email Mastodon https://ben.kirman.org/ Other links Website LinkedIn BlueSky Github Themes Applied Games Creative Computing Design & Development Esports Player Research - Previous Next

< Back Dr Dan Franks University of York Supervisor Dr Franks is an interdisciplinary researcher and data scientist interested in AI and machine learning. He is experienced in developing and applying evolutionary computation and machine learning methods to understanding behaviour. He is an internationally recognized leader in interdisciplinary research, has published in top journals such as Science and PNAS. Some of his papers are in the top 1% of all papers for media coverage (altmetric), and his work is regularly covered by The New Scientist, National Geographic, Wired, The BBC, The Guardian, The Times, among others. As Reader in the York Centre for Cross-disciplinary Systems Analysis, Dan works on applying AI, machine learning, and agent-based modelling, to problems in other disciplines. Particular interests involve the development of machine learning methods for creating intelligent AI and for understanding complex systems. Research themes: Game AI Game Analytics daniel.franks@york.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI Game Data - Previous Next

< Back Prof. Mark Sandler Queen Mary University of London Supervisor Queen Mary University of London, Centre for Digital Music, School of Electronic Engineering and Computer Science. Mark Sandler has been doing research in audio and music – with a little computer vision as a side line – for over 40 years. He founded the world-leading Centre for Digital Music and has been its Director since 2003 (with a 4 year gap 2010-14). The Centre is now one of the largest such research groupings in the world, with around 80 PhDs, PDRAs and academics. In his early career he invented the Digital Power Amplifier, researched Drum Analysis and Synthesis for Simmons Electronics Ltd, moving into Fractal and Chaos analysis and synthesis, Ambisonic modelling and Fine Grain Audio Compression before becoming one of the pioneers of Music Information Retrieval around 2000. He is a Fellow of the Royal Academy of Engineering, of the IEEE, the IET and the AES. He is also a Fellow of the Alan Turing Institute. He has supervised over 40 PhD candidates successfully through their studies and is currently involved in four other CDTs at QM - in AI and Music (Co-Investigator, Impact, in Data Centric Engineering (Co-Director, Partnerships), in Data-centric Engineering (Director) and Media & Arts Technology (of which he was founding Director 2009-16). Research interests are: Digital Signal Processing, Digital Audio, Digital Music Technology, Music Informatics, Semantic Audio, Music Data Science, Semantic Music Metadata, Auditory User Interaction, Immersive Audio. He is particularly interested in supervising students with a background in Acoustics, Signal Processing, Audio, Machine/Deep Learning in: Virtual acoustics for games Games engines for virtual and augmented reality music experiences Research themes: Games Engines for non-gaming interactive experiences Game Audio and Music mark.sandler@qmul.ac.uk Email Mastodon https://www.linkedin.com/in/mark-sandler-a689b4/ Other links Website LinkedIn BlueSky Github Themes Game Audio - 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 Mastodon Other links Website LinkedIn BlueSky Github Themes Player Research - Previous Next

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