Search Results

< Back Dr Charline Foch University of York iGGi Alum Available for post-PhD position Charline first came to the UK in 2011 to study English and Film Studies at King’s College London, before going on to a MSc in Film, Exhibition and Curation at the University of Edinburgh. By chance, accident or fate, she stumbled into the games industry, working in an independent game studio in Berlin, where she touched upon customer support, community management, content writing and QA for a new MMORPG. This experience gave her the push to start a PhD in video games. In her spare time, she is an avid film viewer, volleyball player, and amateur artist. Charline’s research focuses on how people conceptualise failure, with an emphasis on its perceived positive, desirable effects on player experience. Throughout her PhD, she has conducted research among video games players to gain a better understanding of what they perceive as the purpose and value of failure in the games they play; and conducted research among video games developers to gain a better understanding of what processes, obstacles, and ideas go into the design and implementation of failure in their games. With a focus on single-player, more narrative-driven games, she has used this research to design a cards-based design toolkit to support game designers in approaching the question of fail states and player experience in the early stages of the game development process, helping them reflect on the intersection between failure, game mechanics, storytelling, and player experience when working on their games. Aside from her PhD, Charline has also worked with the Digital Creativity Labs on the PlayOn! project, a European project gathering 9 theatres across Europe working on immersive technologies (VR, AR, apps for audience participation...) and theatre productions. During her time at PlayOn!, she has worked on the connections between the games industry and the performance arts, investigating how technology, game design principles, and theatre can work together, and what barriers practitioners face when attempting to reconcile all sides in a single production through experimentation and collaboration. charline.foch@york.ac.uk Email https://mastodon.gamedev.place/@chafoch Mastodon https://charlinefoch.carrd.co Other links Website https://www.linkedin.com/in/charline-foch-97196663 LinkedIn BlueSky Github Supervisor: Dr Ben Kirman Featured Publication(s): “The game doesn't judge you”: game designers’ perspectives on implementing failure in video games “Slow down and look”: Desirable aspects of failure in video games, from the perspective of players. Themes Design & Development Player Research - Previous Next

< 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. yul.kang@qmul.ac.uk Email Mastodon https://www.yulkang.net/ Other links Website https://www.linkedin.com/in/yul-kang-9b11522b/ LinkedIn BlueSky https://github.com/yulkang Github Themes Creative Computing Game AI Immersive Technology Player Research - Previous Next

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

The EPSRC Centre for Doctoral Training in Intelligent Games & Game Intelligence (IGGI) is the world's largest PhD research in games programme. The annual IGGI conference showcases students' work. Based at Uni of York & Queen Mary Uni of London, IGGI collaborates closely with 80+ industry partners. Welcome to iGGi !!! We are a group of people doing research in games... Read More Follow us on social media: (if you musk) click - Researchers Available for Placement - click - iGGi THEMES - Game AI Game Data Design & Development Immersive Technology Esports Accessibility Creative Computing Game Audio Player Research Applied Games Check out the latest iGGi NEWS 12 September 2025 iGGi Con 2025 Successfully Concluded! The world's favourite doctoral training programme has done it again! Its annual conference was held at York this week, and It's A Wrap! Read More iGGi GAMES iGGi COMMUNITY PG Researchers Staff Industry Partners Management Team Alumni

< Back Peyman Hosseini Queen Mary University of London iGGi PG Researcher Peyman is interested in using his computer science knowledge to support society's well-being. Raised in a family where almost everyone’s work is somehow related to mathematics and its applications, he became passionate about algorithms and combinatorics from an early age. This prompted him to pursue an undergraduate degree in computer engineering with a focus on IT and AI. This background led him to start his PhD at IGGI on building more powerful yet efficient Natural Language Processing models for analysing textual data, a rich and abundant source of gaming feedback. A description of Peyman's research: Peyman's research focuses on advancing deep learning architectures for natural language processing and building tools on top of state-of-the-art models. To contribute to the fundamental understanding and practical application of deep learning in natural language processing, focusing on efficiency and effectiveness, he pursues two main objectives: Designing more efficient models that match or surpass state-of-the-art performance with fewer parameters. Systematically analyzing language models to develop solutions that enhance their effectiveness for end-users, such as game studios. His recent accomplishments towards these goals include: 1. Developing novel attention mechanisms: 1.1 Optimized Attention: 25% parameter reduction 1.2 Efficient Attention: 50% parameter reduction 1.3 Super Attention: 25% parameter reduction with significant performance improvements in language and vision tasks 1.4 All mechanisms demonstrate comparable or superior performance to standard attention across various inputs. 2. Designing and training Hummingbird , a proof-of-concept small language model using Efficient Attention, available on HuggingFace. 3. Conducting a study on large language models' limitations in analyzing lengthy reviews for basic NLP tasks. Proposed solutions offer substantial performance improvements while reducing API costs by more than 90%. s.hosseini@qmul.ac.uk Email Mastodon https://peymanhosseini.net/ Other links Website https://www.linkedin.com/in/peyman-hosseini1 LinkedIn BlueSky https://github.com/Speymanhs Github Supervisors: Dr Ignacio Castro Prof. Matthew Purver Featured Publication(s): Cost-Effective Attention Mechanisms for Low Resource Settings: Necessity & Sufficiency of Linear Transformations Efficient solutions for an intriguing failure of llms: Long context window does not mean LLMs can analyze long sequences flawlessly Brain Drain Optimization (BRADO) Algorithm to Solve Multi-Objective Expert Team Formation Problem in Social Networks You Need to Pay Better Attention: Rethinking the Mathematics of Attention Mechanism GeoPos: A Minimal Positional Encoding for Enhanced Fine-Grained Details in Image Synthesis Using Convolutional Neural Networks Lon-ea at SemEval-2023 Task 11: A Comparison of Activation Functions for Soft and Hard Label Prediction GRACER: Improving the Accuracy of RACER Classifier Using A Greedy Approach Themes Game AI Player Research - 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 Ignacio Castro Queen Mary University of London Supervisor Ignacio Castro is Lecturer in Data Analytics at Queen Mary University of London. His work sits at the intersection between economics and networks. His interest spans from online social networks and moderation to the macroscopic evolution of the Internet. He has been an investigator on three major grants that hold over £6 million in funding. His work appears in top tier journals and conferences including Web Conference, ACM SIGCOMM, ACM SIGMETRICS, ACM IMC, ICWSM, and IEEE/ACM Trans. on Networking. He is interested in supervising students with a background in social network analysis, NLP and/or machine learning. i.castro@qmul.ac.uk Email https://mastodon.social/@ignactro Mastodon https://icastro.info/ Other links Website https://www.linkedin.com/in/ignacio-de-castro-arribas-44a48117/ LinkedIn BlueSky Github Themes Applied Games Game AI Game Data Player Research - Previous Next

< Back Prof. Nick Pears University of York Supervisor Nick Pears is a Professor of Computer Vision in York’s Vision, Graphics and Learning (VGL) research group. He works on statistical modelling of 3D shapes, with an emphasis on the human face and head. The Liverpool-York Head Model and the associated Headspace training set has been downloaded by over 100 research groups internationally, with the Universal Head Model being downloaded by 50 research groups. His most recent work with his PhD students has focused on semantic disentanglement of 3D images and how to make autonomous vehicles safer and more trustworthy when using computer vision systems. He is assessor for many PhDs including construction of generative models for novel video content using adversarial deep learning techniques. nick.pears@york.ac.uk Email Mastodon https://www-users.cs.york.ac.uk/np7/ Other links Website https://www.linkedin.com/in/nick-pears-90970312/ LinkedIn BlueSky Github Themes Creative Computing Game AI - Previous Next

< Back Dr Lorenzo Jamone Queen Mary University of London Supervisor I am a Lecturer in Robotics and Director of the CRISP group (Cognitive Robotics and Intelligent Systems for the People) at the School of Electronic Engineering and Computer Science (EECS) of the Queen Mary University of London (QMUL). The CRISP group is part of ARQ (Advanced Robotics at Queen Mary). Since October 2018, I have been a Turing Fellow at The Alan Turing Institute. I am interested in understanding human (and animal) intelligence, by using computational techniques that include computer simulations and real robots. My research topics include: human creativity and creative problem solving, human perception, human-human non-verbal communication, object affordances, tool use, body schema, eye-hand coordination, dexterous manipulation and object exploration, human-robot interaction and collaboration, tactile and force sensing. I am interested in supervising students with an engineering, computer science or behavioural sciences background on the following topics: Creating computational models of human creativity Creating computational models of decisional agents l.jamone@qmul.ac.uk Email Mastodon https://lorejam.wixsite.com/crisp Other links Website LinkedIn BlueSky Github Themes Applied Games Creative Computing - Previous Next

< Back Joint Writing Retreat - November 2023 Another fantastic Joint Writing Retreat was had with our colleagues at MAT , CDE and AIM this week at the beautiful High Leigh. Feedback from the event, was, as always really positive with: 100% of respondents saying the retreat was useful and beneficial to their research/progress 96% saying they would recommend it to others 95% saying they produced more content than expected With comments about the primary benefit of the retreat being: Scheduled writing time and not having to worry about preparing food, chores etc Refreshing and networking with people in a similar but different sphere made me reframe I feel good writing in a big group. And I have good mood in here Very focused working time and environment. More productive than the office. Very quiet and focused. Not having to think about what food to buy and to prepare and to cook takes the mental load off to just focus on writing. It's surprising how much fretting about food preparation for the week takes out of your day. Here is the word cloud created from the Mentimeter “poll of 3 words” to describe the retreat: Previous 24 Nov 2023 Next

< Back Guilherme Matos de Faria University of York iGGi Alum I am a Portuguese student with a background in Artificial Intelligence. In 2016 I started attending video game tournaments and learned to analyse my matches and improve from it. When I did my masters in AI, I noticed that I could join my professional skills and my hobbies together to create something relevant to AI and competitive gaming. A description of James' research: I am looking to better understand which actions and decisions have the biggest impact on the outcome of a game. Currently, I am particularly focused on competitive turn based card games. What are the best players doing to win? How can players adapt to improve their chances of success? These are the questions I am hoping to help answer, giving players a better understanding of the game and how to improve. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next

< Back Dr Ildar Farkhatdinov Queen Mary University of London Supervisor Dr Ildar Farkhatdinov is a Lecturer in Robotics at QMUL since 11/2016 and a Turing Institute Fellow. He is an internationally leading expert in assistive robotics and human-machine interaction. He is a principle investigator of several projects on wearable robotics, mobility assistance and haptic interfaces (including funding from the UK government on supernumerary robotic limbs and assistive wheelchairs, £500k+). Several of his research works were recognised as the best paper or finalists for best paper awards at leading robotics conferences. Before joining QMUL, he was a postdoctoral research associate at the Human Robotics group of the Department of Bioengineering, Imperial College London (2013-16). He earned Ph.D. in Robotics in 2013 (Sorbonne University, UPMC, France), M.Sc. in Mechanical Engineering in 2008 (KoreaTech, South Korea) and B.Sc. in Automation and Control in 2006 (Moscow University, Russia). He has actively collaborated on a number of large-scale research projects: EPSRC NCNR to create novel robotic solutions for the nuclear industry; EU FP7 BALANCE to develop balance and robotic walking assistance for the elderly; EU FP7 SYMBITRON to develop exoskeleton control for people with spinal cord injury. My research interest relevant to CDT IGGI include serious games for medical applications, as well as using game theory to investigate human-machine interaction. Research themes: Game Design Serious games Virtual reality Game theory i.farkhatdinov@qmul.ac.uk Email Mastodon https://hair-robotics.qmul.ac.uk Other links Website https://www.linkedin.com/in/ildar-farkhatdinov-33075016 LinkedIn BlueSky Github Themes Design & Development Game AI Immersive Technology Player Research - Previous Next