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  • Sahar Mirhadi

    < Back Sahar Mirhadi University of York iGGi PG Researcher Available for post-PhD position Sahar Mirhadi is a final-year PhD researcher investigating how video games support during challenging times. Her contributions have been published in the Proceedings of the ACM Conference on Human-Computer Interaction, and she has presented at Devcom on transforming the complexity of turn-based games into a strategic advantage. She is also a passionate Magic: The Gathering player, collaborating with competitive Magic team Worldly Counsel to convert tournament insights into a deeper understanding of player motivations and team dynamics. Sahar is also a Safe In Our World Ambassador, a recipient of the Magic: The Gathering New Perspectives Grant for Marginalised Players, and a member of the Birds of Paradise collective. A description of Sahar's research: Sahar's PhD research project investigates the specific aspects of games that facilitate coping for players during difficult life experiences. Building on earlier work that mapped broad links between game aspects and coping strategies, Sahar’s first study showed that games can support a variety of coping strategies, including emotion-focused, avoidance, and meaning-focused coping. However, questions remained about how these effects occur across different gaming contexts. To address this, her second study employed in-depth interviews and a grounded theory approach with players of Disco Elysium, Darkest Dungeon and Stardew Valley. The findings led to the development of the Games as Dynamic Coping Systems theory, which posits that specific aspects of video games scaffold a diverse range of coping strategies for players facing personal difficulties. The model highlights the dynamic interplay between what the player brings (e.g., prior experiences, needs, skills) and what the game provides (such as Narrative, Game Environment and Character Interactions). Through this interaction, players develop coping strategies, and the outcomes from coping feed back into their ongoing gaming and life experiences. While the grounded theory offered a deeper understanding of how specific game aspects support various coping strategies, it also revealed a gap: the temporal dynamics of coping. Sahar’s ongoing work aims to explore how players transition between coping strategies over time and what factors shape these transitions. Her overall aim is to provide a deeper understanding of specific aspects within games that support coping, shedding light on the potential benefits and limitations of video games during times of difficulty. Email sm2904@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Alena Denisova Dr Jo Iacovides Themes Player Research https://www.youtube.com/watch?v=0nTTCR25O0Y Previous Next

  • Oliver Withington

    < Back Dr Oliver Withington Queen Mary University of London iGGi Alum Available for post-PhD position Oliver Withington is a AI and games researcher working on novel methods for evaluating content generation systems for games. Following a successful career in the healthcare technology industry he decided to combine his life long love of games and interest in AI research into a PhD with the iGGi CDT in 2020. He lives in London with his wife and two young daughters, and when he is not writing about, thinking about, or talking about games you can probably find him in either his local bouldering gym, or in the park either pursuing or being pursued by two small children. A description of Oliver's research: Oliver's primary motivation is to make the evaluation of novel content generators more standardised, robust and straightforward for both researchers and game designers. Currently his focus is on techniques for producing informative visualisations of the output spaces of content generators. His work has been published at many of the leading conferences in his field, and he has also taken his work and ideas to the game industry, most recently in the form of a talk at GDC 2025's AI Summit. Email owithington@hotmail.co.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Jeremy Gow Dr Laurissa Tokarchuk Featured Publication(s): Designer Difficulties: Visualizing the Possibility Spaces of Dynamic Difficulty Adjustment Systems Exploring the Possibility Space of 1 Billion Spells Exploring Minecraft Settlement Generators with Generative Shift Analysis HarmonyMapper: Generating Emotionally Divers Chord Progressions for Games. The Right Variety: Improving Expressive Range Analysis with Metric Selection Methods Visualising Generative Spaces Using Convolutional Neural Network Embeddings Compressing and Comparing the Generative Spaces of Procedural Content Generators Illuminating Super Mario Bros: quality-diversity within platformer level generation Themes Creative Computing Design & Development Game AI https://www.youtube.com/watch?v=4m1gYriq_pc Previous Next

  • Lauren Winter

    < Back Lauren Winter University of York iGGi PG Researcher Lauren was introduced to gaming from an early age when they received a PlayStation One as a gift. From there, video games became a huge part of their life, exploring new worlds through the eyes of a vast array of characters. Following their undergraduate degree in Psychology with Sociology, they completed their MSc in Psychology Research Methods at the University of Nottingham. A fascination with looking for trends in data and creating complex spreadsheets in Excel led them to a job analysing student information in a school, where they also ran four Esports teams competing across three games. Their research interests primarily focus on player research in team-based PVP games and looking at players’ awareness of each other in these environments. A description of Lauren's research: Lauren’s work investigates the player experience in team-versus-team games such as League of Legends. This is achieved through the lens of social presence: the awareness of others in a digital environment. The social experience has been found to be one that is related, but separate to the more commonly explored facets of player experience. Through measuring player experiences in popular team-verus-team games, validating a purpose-designed questionnaire, and developing a bespoke game in Unity, Laurens’ work explores how the ‘social’ in these social games is built between and within teams, and how all of the players contribute to this shared experience. Email lauren.winter@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Featured Publication(s): "Leave our kids alone!": Exploring Concerns Reported by Parents in 1-star Reviews "Leave our kids alone!": Exploring Concerns Reported by Parents in 1-star Reviews Better Dead than a Damsel: Gender Representation and Player Churn Themes Design & Development Player Research - Previous Next

  • Prof Massimo Poesio

    < Back Prof. Massimo Poesio Queen Mary University of London Supervisor Massimo Poesio is a cognitive scientist whose primary field is Computational Linguistics / Natural Language Processing. He is interested in the interdisciplinary study of language processing using evidence from computational modelling, corpora, psychological studies, and neuroscience; specific interests include computational models of anaphora resolution (coreference); the study of disagreement on language interpretation through the creation of large corpora containing multiple judgments (an area in which he pioneered the use of games-with-a-purpose with the development of Phrase Detectives, http://www.phrasedetectives.org ); the interpretation of verbal and non-verbal communication in interaction; and the study of conceptual knowledge using a combination of methods from human language technology and neuroscience. He has also been involved in a number of projects applying NLP methods to real life problems, such as detecting deception online, or identifying human rights violations reports in social media. He holds a European Research Council grant on identifying disagreements in language through Games-With-A-Purpose, DALI and is a co-founder of the open access journal Dialogue and Discourse . Using conversational agents in games Applying games to label data for AI Research themes: Game AI Game Design Games with a Purpose Email m.poesio@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Game AI - Previous Next

  • Luke Farrar

    < Back Luke Farrar University of York iGGi Alum Luke Farrar is an iGGi PhD student at The University of York undertaking research in Flexible and Realistic Character Animations in Complex and Dynamic Environments. Luke's research focuses through his bachelor's and master's degrees were on applying machine learning to interesting and unique settings. In his bachelor's he focused on creating an application for individuals that suffered from cognitive impairments through the use of the "Microsoft HoloLens" and machine learning to allow those individuals to maintain a semblance of everyday life. In his postgraduate Luke focused on using machine learning to generalise high-fidelity scientific simulations to rapidly generate predictions for parameter combinations that had not yet been sampled in order to accelerate the production of new results. Luke revels in all things AI, knowing that there is always more to learn and seeks to continually deepen his understanding around AI. A description of Luke's research: Modern games have an increasing focus on hyper-realism and immersion to better capture the attention of players. One of the ways that games can break this immersion is by having animations that break the flow of movement or actions through the use of predefined animations. Motion matching is a solution for predicting the best next frame of an animation by looking at the pose and user trajectory. The downside however, is that when you increase the amount of possible animations in the database the runtime cost also increases. A solution was proposed known as 'learned motion matching' (Holden et al., 2020) which takes the positive properties of motion matching but also achieves the scalability of neural-network-based generative models. This project will explore and improve the learned motion matching method through implementation of memory layers to improve accuracy without the sacrifice of increasing runtime costs. A restructuring and adaptation of the existing machine learning neural network used could also improve the learned motion matching method as breaking down each step of the learned motion matching at each step could uncover optimisations that are not initially visible. Another way restructuring could improve the learned motion matching is through creating a more succinct all-in-one approach which may streamline the process. Email lukebfarrar@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Miles Hansard Dr Patrik Huber Dr James Walker Themes Immersive Technology - Previous Next

  • Sam Hughes

    < Back Sam Hughes University of York iGGi Alum Affect and Emotion using Immersive Sound in Intelligent Games. (On Industrial Placement with Remedy Entertainment) Recent advances in high definition video displays and 3-D headsets, coupled with motion tracking and biosensor technologies, have enabled video games to reach unprecedented levels of visual immersion and interaction. There is little research however on how the aural feedback of the player, which can help assess their emotional state, can be used to inform the game intelligence and affect the emotive impact of the game. Furthermore, improvements in domestic surround sound and binaural technology are paving the way for fully enveloping and realistic soundtracks that extend the gameplay beyond the visual and can significantly enhance the emotive experience. This research project therefore addresses how current sensor and tracking technologies can be enhanced through analysis of player aural reactions such that the game intelligence can in turn provoke a conditional response via the reproduced soundtrack. In other words, how can the emotional impact of a spatial soundtrack during gameplay be enhanced by the user aural response alongside other physiological detections such as heartbeat and movement? Sam is a sound designer and voice actor who founded the audio journalism site, The Sound Architect™. Sam was selected as one of the first to ever receive the Prince William Scholarship from both BAFTA & Warner Bros. to study MSc Post Production with Sound Design at The University of York where he graduated with a Distinction and a Departmental Award for achieving the Highest Overall Average Grade. Sam has been highly active in the community for years including writing for BAFTA Guru, sitting on the BAFTA Youth Board, running Game Audio North and being an active member of BAFTA Crew Games. Most recently Sam has worked regularly with game audio company Sweet Justice on a variety of titles that include mobile and AAA. Sam’s recent credits include Injustice 2 and Madden NFL 2017. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Player Research - Previous Next

  • Dr Alena Denisova

    < Back Dr Alena Denisova University of York Supervisor Alena Denisova is a Lecturer in Computer Science at the University of York, UK. She is actively involved in collaborative and interdisciplinary projects that involve conceptualising and measuring user experience of video games and designing and building educational and persuasive interactive media. Her research explores the role of the `placebo effect’ of technology in shaping player experiences, perceived challenge and uncertainty in video games, and, more recently, emotionally impactful player experiences - understanding how these experiences are shaped with the view to inform the design of games that promote these experiences. Alena is an active member of the games HCI community: she is a co-chair of the IEEE Task Force on Automatic Gameplay Evaluation and a member of the Programme Committee for the annual CHI and CHI Play conferences. She is interested in supervising students that have qualitative, mixed method or design experience that they wish to apply to studying digital games. Possible research topics include exploring what makes choices in games meaningful for players, how perceived uncertainty, risk-aversion, and luck affect decision making in games, and how skill is acquired and advanced throughout while playing video games. She is also keen to work with students who wish to work on games with a purpose. For instance, designing and developing games that promote informed decision-making about moral and ethical choices, such as promoting sustainable lifestyle, reflecting on important real-life issues, developing personally, etc. Email alena.denisova@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Design & Development Player Research - Previous Next

  • Igor Dallavanzi

    < Back Igor Dall'Avanzi Goldsmiths iGGi Alum Creation of accessible tools for the use of procedural audio in video games The aim of this research is to investigate and provide new tools to developers for the use of procedural audio into video games. Procedural approaches could address different issues that commonly afflict game audio. In music, generative systems are not only less repetitive, but offer more adaptability as well. For what concerns sound design, they can provide not only variety, but stronger and more realistic support to the interaction with the game world; interaction that is becoming even deeper with the advent of VR Yet, these methods still need improvement on different sides. One is the level of quality that procedural audio needs to achieve to compete with the current aesthetic established by the use of rendered sounds and music in the media. Another is the additional amount of work required by the CPU to render the assets on runtime, and its variable cost). Finally, there is a general lack of user-friendly tools, to link common programming languages for audio to game engines. Software like MaxMsp, Pure Data or SuperCollider is used to design generative audio systems. A more accessible integration of these software could promote generative approaches among sound designers and composers in the field, that today have instead access to tools mainly designed to be used with rendered assets. My plan is to bring on research first by focusing on how a higher degree of quality could be addressed, exploring tools like the above mentioned MaxMsp, Pure Data, low level solutions, and machine learning algorithms. Primary research will be run to confront procedurally generated audio content with rendered one; to understand its impact on the player, and the level of quality needed to deliver a satisfactory experience. The creation of more accessible interfaces and tools dedicated to implement procedural audio in video games will be investigated and undertaken. I like to make noises of all sort and to play with them. For this reason I graduated in Music Production in 2016 and, at the moment of writing, I am finishing my final project for an MSc in Sound and Music for Interactive Games at Leeds Beckett University. Composer and sound designer, in the last year I have been focusing on audio implementation and programming, and I am currently exploring machine learning approaches for procedural audio. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game Audio Player Research - Previous Next

  • Remo Sasso

    < 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. Email r.sasso@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Paulo Rauber Featured Publication(s): Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds On the Limits of Tabular Hardness Metrics for Deep RL: A Study with the Pharos Benchmark 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

  • Dr James Walker

    < Back Dr James Walker University of York iGGi Industry Liaison Supervisor Dr James Walker is a Senior Lecturer in Computer Science and Digital Creativity at the University of York. A member of the Digital Creativity Labs, and the York Cross-disciplinary Centre for Systems Analysis (YCCSA). His current research focuses on bio-inspired algorithms (including AI and machine learning) and their application to games and game data analytics. He is also a senior member of the IEEE. Email James@digitalcreativity.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Esports Game AI Game Data - Previous Next

  • Doruk Balci

    < Back Doruk Balcı University of York iGGi PG Researcher Available for placement I am a game maker interested in the relationship between player creativity and game design. My work is centered around the transformative capabilities of players to invent their own metagames and play-practices, and how to support this through game design. My other interests include: drawing, literature, making zines and browser games, and playing with tools I don’t really understand. Designing for Appropriative Play How do we make games which we want to be messed with, changed fundamentally beyond our expectations in play? How do we make up rules that are intended to be bent, changed or broken? Why would we want that? Play practices that transform structures, subvert expectations and re-define their contexts are celebrated in many aspects of culture and can lead to personal and meaningful experiences. Yet research on this topic from a game design perspective has been scarce. In my project, I am exploring how we can design game systems that invite players to assume ownership of their play-practices through exploring alternative paradigms of game design. Email doruk.balci@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Jo Iacovides Featured Publication(s): Digital Playground: The Hidden Politics of Children's Online Play Spaces, Virtual Worlds and Connected Games Game Rules as Player Tools: Introspective Rulebook Method Player Discretion is Advised: Designing for Rule-Changing Play Themes Design & Development Player Research - Previous Next

  • David Hull

    < Back David Hull University of York iGGi Manager iGGi Admin I have worked at the University of York since October 1995, almost all of it in the Department of Computer Science. My various roles have included Laboratory and Facilities Manager, Technical Manager and, most recently, Project Manager. Outside work, I have been a change-ringer for almost 50 years, and am currently a member of the band that rings the bells weekly at York Minster. I am also an accredited teacher of bellringing. I do parkrun most weeks, alongside the occasional 10k and half marathon, like to watch cricket, and play the clarinet and piano. Email iggi-admin@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes - Previous Next

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