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  • Location

    Locations (All) iGGi is a collaboration between Uni of York + Queen Mary Uni of London: the largest training programme worldwide for doing a PhD in digital games. Locations iGGi Queen Mary University of London (QMUL) iGGi QMUL is located at the heart of East London on Queen Mary, University of London's Whitechapel campus. Read More University of York (UoY) iGGi York is located just outside the City of York's centre, on University of York's East Campus. Read More Goldsmiths, University of London (Goldsmiths) iGGi Goldsmiths is located in New Cross, South East London, five miles from central London. Read More University of Essex (UoE) iGGi Essex is located two miles from the historic city of Colchester and set in over 200 acres of beautiful parkland. Read More

  • Queen Mary University of London (QMUL) | iGGi PhD

    < Back iGGi QMUL is located at the heart of East London on Queen Mary, University of London's Whitechapel campus. iGGi QMUL is part of QMUL’s School of Electronic Engineering and Computer Science . While QMUL-based iGGi PGRs can belong to more than one research group, they all by default belong to the Game AI Group (GAIG) . The iGGi/GAIG office space is situated within the Digital Environment Research Institute (DERI) at Empire House, Whitechapel campus. How to reach the iGGi Offices at Empire House, Whitechapel The address for the iGGi office space is 2nd Floor Empire House DERI 67-75 New Road London, Whitechapel E1 1HH Whitechapel campus map Accesibility: Empire House access guide Arriving by Tube The Whitechapel campus is easily accessible via public transport, with the Whitechapel Underground station on London Underground's Elizabeth Line (purple on the Tube map), Hammersmith and City Line (pink on the Tube map), and District Line (green on the Tube map), just a seven minute walk away. When you exit the station, turn right and walk along Whitechapel Road until the next larger junction. Turn left into New Road. Empire House will be located to your right. Please use the Transport for London Journey Planner to help you plan your journey: https://tfl.gov.uk/plan-a-journey/ or their interactive maps showing Underground, Docklands Light Railway (DLR) and bus information Arriving by Bus The Whitechapel campus is based on Whitechapel Road, on the 25 and 205 bus routes, and Empire House is just off Whitechapel Road, on New Road. Cycling/Walking If you are travelling by bike or walking, please use the postcode above and the campus map to help you navigate to the venue. Bike storage facilities can be found in the Empire House Basement. Arriving by car For both our Mile End and Whitechapel campuses, car parking for visitors is not offered due to our central location. Local parking restrictions also apply on weekdays and weekends.We therefore strongly recommend you use one of the alternative transport methods listed above. If you do need to drive to campus, QMUL open day published a list of offsite parking options within easy reach of Whitechapel, including park and ride options. If you are a blue badge holder and require parking on site, please email opendays@qmul.ac.uk . Queen Mary University of London (QMUL) iGGi QMUL Gallery Map depicting QMUL Mile End campus & the iGGi Con 2023 venue location iGGi Con 2023 venue: The Graduate Centre (Mile End campus, QMUL), viewed from Bancroft Road iGGi Con 2023 venue: Ground floor entrance of the Graduate Centre - Mile End campus, QMUL Mile End campus with the Graduate Centre on the left Birds eye view of Mile End campus, QMUL Map depicting QMUL Whitechapel campus with Empire House where all of the iGGi Office space is located Empire House Basement, QMUL (Whitechapel) iGGi office space, Empire House, QMUL (Whitechapel campus) The Blizard Building opposite Empire House, Whitechapel campus (QMUL) Previous Next

  • dr-tom-cole

    < Back Dr Tom Cole iGGi Alum + Supervisor Games should be studied as interactive systems, but are more often studied using techniques reserved for non-interactive media. As developers, we are ‘selling ourselves short’, and not exploring the creative and expressive potential of digital games to their fullest. Out of the myriad of affective experiences possible, we generally only design and experience a fraction of what could be offered. Tom hopes to help address this by studying how game mechanics, gameplay systems and control methods can be used and interpreted to create meaning and elicit a wider range of emotional responses than is commonly seen in digital games at present. Broadening and deepening emotional engagement with an emphasis on mechanics and systems. (Industry placement at Bossa Studios) Video games, with their unique properties such as interactivity, agency, control mechanics, feedback loops and gameplay systems, have the potential to impart deep emotional experiences – some already do of course. However, study of this emotional engagement remains lacking. Reliance on techniques and theory appropriated from film, literature and cultural studies yields limited results. There is relatively little understanding of how procedural elements such as control mechanisms and gameplay systems can be leveraged (or synergised with narrative and/or audio-visual elements) for emotional affect. Tom was previously at Supermassive Games where he was a designer on the BAFTA award-winning horror game Until Dawn and artist on Killzone Shadow Fall. Tom got his BSc in Biology with Industrial Experience from Manchester. After teaching science in secondary schools for a while, he decided games were more interesting and got his MA in Digital Games Theory and Design at Brunel. After time at Goldsmiths, University of London and the University for Creative Arts, Rochester, Tom is now Lecturer in Games Development at the University of Greenwich where he teaches games development, design and production. From 2016 to 2024 he led the organisation of Adventurex - the Narrative Games Convention, a sold out international conference which grew from 100 to 650 people during his time leading it. tom@tommakesgames.com Email Mastodon http://www.tommakesgames.com Other links Website https://uk.linkedin.com/in/tom-cole-87043a38 LinkedIn BlueSky Github Featured Publication(s): Emotional exploration and the eudaimonic gameplay experience: A grounded theory More than a bit of coding:(un-) Grounded (non-) Theory in HCI Eudaimonia in Digital Games Thinking and doing: Challenge, agency, and the eudaimonic experience in video games "Moments to Talk About": Designing for the Eudaimonic Gameplay Experience Grounded Theory in games research: making the case and exploring the options Grounded Theory in Games Research: Making the Case and Exploring the Options Emotional and functional challenge in core and avant-garde games The Tragedy of Betrayal: How the design of Ico and Shadow of the Colossus elicits emotion Themes Design & Development Game AI - Previous Next

  • Dr Changjae Oh

    < Back Dr Changjae Oh Queen Mary University of London Supervisor Changjae Oh joined Queen Mary University of London (QMUL) in September 2019 as a Lecturer at the School of Electrical Engineering and Computer Science (EECS). He was a postdoctoral researcher at QMUL EECS from 2018 to 2019. He received a PhD in Electrical and Electronic Engineering in 2018 at Yonsei University, South Korea. His research expertise spans a range of researches that are based on visual signals, such as image processing, computer vision, and vision-based machine perception, combined with machine/deep learning. Within the topics with IGGI, he is particularly interested in students who want to investigate the topics about vision-based AI perception in a game environment and game engines for real-robot perception. c.oh@qmul.ac.uk Email Mastodon https://eecs.qmul.ac.uk/~coh/ Other links Website https://www.linkedin.com/in/changjae-oh-42a36685 LinkedIn BlueSky Github Themes Applied Games Game AI - 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 m.poesio@qmul.ac.uk Email Mastodon https://sites.google.com/view/massimo-poesio/ Other links Website LinkedIn BlueSky https://github.com/dali-ambiguity Github Themes Applied Games Game AI - Previous Next

  • Dr Laurissa Tokarchuk

    < Back Dr Laurissa Tokarchuk Queen Mary University of London iGGi Research Collaboration Coordinator Supervisor Laurissa Tokarchuk is a senior lecturer and researcher working on playful ways of exploring and integrating virtual and real world space. Her primary focus is looking at engaging ways of creating and interacting with AR content in games and incorporating physical sensors for increasing playability in mobile games. Her interests also include merging AI with mobile and social sensing to detect events and behaviours in crowds and games, and the use of technology to promote learning/well-being. Her research has resulted in the widely used SensingKit framework, best poster awards, media appearances in the Guardian and BBC (Royal Institution Christmas Lectures). She is particularly interested in supervising students on the following topics: AR/VR games for learning and cognition design for promoting behaviour change understanding and designing for player behaviour and curiosity in games Research themes: Game AI Games with a Purpose Computational Creativity Player Experience laurissa.tokarchuk@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/~laurissa/ Other links Website https://www.linkedin.com/in/laurissa-tokarchuk-27aa3214/ LinkedIn BlueSky Github Themes Applied Games Creative Computing Game AI Immersive Technology Player Research - Previous Next

  • Tamsin Isaac

    < Back Tamsin Isaac University of York iGGi PG Researcher Available for placement Tamsin has been a lifelong gamer ever since receiving her first Game Boy and has always been fascinated by how people engage with games—both emotionally and behaviourally. She joined the iGGi CDT in 2023 after completing a BSc and MSc in Psychology at the University of Plymouth, where she developed a growing interest in how psychological principles such as motivation and disengagement apply not just to players, but to the systems they interact with. Her PhD research focuses on limited-time events (LTEs) in digital games—temporary content used to drive engagement and re-engagement. By exploring how LTEs influence player engagement, disengagement, and return play in live-service games, her work aims to bring clarity to this rapidly evolving area of game design. She is currently developing a cross-platform taxonomy of LTEs through large-scale content analysis of over 1,000 top-charting mobile and PC games. Alongside this, she is conducting an ongoing diary-plus-interview study to explore how players experience these events in everyday play. Tamsin’s research investigates how different LTE formats affect sustained engagement, disengagement, and re-engagement, with the goal of informing more ethical and effective event design for both players and developers. She is open to Knowledge Exchange opportunities with game studios interested in analysing live-service events, player behaviour, and re-engagement strategies using live data or design insights. When not writing about or analysing games, Tamsin enjoys baking, reading, playing cosy indie games, and quietly grinding dailies. tamsin.isaac@york.ac.uk Email Mastodon http://www.tamsinisaac.com Other links Website http://www.linkedin.com/in/tamsinisaac LinkedIn https://bsky.app/profile/tamsinisaac.bsky.social BlueSky Github Supervisor: Prof. Paul Cairns Themes Applied Games Design & Development Player Research Previous Next

  • Terence Broad

    < Back Dr Terence Broad Goldsmiths iGGi Alum Available for post-PhD position Terence Broad is an artist and researcher working on developing new techniques and interfaces for the manipulation of generative models. His PhD focusses on how pre-trained generative neural networks can be repurposed and reconfigured for authoring novel multimedia content. He is completing his PhD at Goldsmiths, University of London and is also a visiting researcher at the UAL Creative Computing Institute. His research has been published in international conferences, workshops and journals such as SIGGRAPH, NeurIPS, Leonardo and xCoAx. He was acknowledged as an outstanding peer-reviewer by the journal Leonardo. Terence is a practicing artist and often uses the techniques he has developed in his research in the creation of his artworks. His art has been exhibited and screened internationally at venues such as The Whitney Museum of American Art, Ars Electronica, The Barbican and The Whitechapel Gallery. He won the Grand Prize in the ICCV 2019 Computer Vision Art Gallery. t.broad@gold.ac.uk Email Mastodon https://terencebroad.com Other links Website https://www.linkedin.com/in/terence-broad-81350668/ LinkedIn BlueSky https://github.com/terrybroad Github Featured Publication(s): XAIxArts Manifesto: Explainable AI for the Arts Using Generative AI as an Artistic Material: A Hacker's Guide Is computational creativity flourishing on the dead internet? Interactive Machine Learning for Generative Models Envisioning Distant Worlds: Fine-Tuning a Latent Diffusion Model with NASA's Exoplanet Data Active Divergence with Generative Deep Learning--A Survey and Taxonomy Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities Network Bending: Expressive Manipulation of Generative Models in Multiple Domains Active Divergence with Generative Deep Learning--A Survey and Taxonomy Network Bending: Expressive Manipulation of Deep Generative Models Amplifying The Uncanny Transforming the output of GANs by fine-tuning them with features from different datasets Searching for an (un) stable equilibrium: experiments in training generative models without data Autoencoding Blade Runner: Reconstructing Films with Artificial Neural Networks Light field completion using focal stack propagation Autoencoding video frames IoT and Machine Learning for Next Generation Traffic Systems Themes Creative Computing Design & Development - Previous Next

  • Alan Pedrassoli Chitayat

    < Back Dr Alan Pedrassoli Chitayat University of York iGGi Alum Available for post-PhD position Alan is a researcher that focuses on audience experience within esport broadcast. His Machine Learning background allows him to extract complex patterns from game and game related data in order to derive meaningful insights that can be utilised in broadcast. Having worked in the esport industry, both as a software engineer as well as researcher, Alan has experience with both technical and research problems. His research aims to explore the factors that improve the audience experience within esports. This is catered to esport broadcast of all levels, from highly produced professional tournaments to regular streams by content creators and it could be in the form of: Measuring and representing different forms of audience engagement. Exploring the different ways to visualise and utilise Machine Learning to enhance and integrate existing broadcast pipelines. Investigating how community-led narratives can be generated through data. alan.pchitayat@york.ac.uk Email https://linktr.ee/alanpchitayat Mastodon https://alanpchitayat.com/ Other links Website https://www.linkedin.com/in/alan-pchitayat/ LinkedIn BlueSky Github Supervisors: Dr James Walker Prof. Anders Drachen Featured Publication(s): How Could They Win? An Exploration of Win Condition for Esports Narratives Applying and Visualising Complex Models in Esport Broadcast Coverage From Passive Viewer to Active Fan: Towards the Design and Large-Scale Evaluation of Interactive Audience Experiences in Esports and Beyond Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analitics Data-Driven Audience Experiences in Esports Metagaming and metagames in Esports What are you looking at? Team fight prediction through player camera Echo Suite of Software (Showcase Brochure) Automatic Generation of Text for Match Recaps using Esport Caster Commentaries WARDS: Modelling the Worth of Vision in MOBA's DAX: Data-Driven Audience Experiences in Esports Themes Design & Development Esports Game Data - Previous Next

  • Dr Gavin Kearney

    < Back Dr Gavin Kearney University of York Supervisor Dr Gavin Kearney is a highly experienced researcher, lecturer and content creator specialising in spatial audio and surround sound. He joined the University of York as Lecturer in Sound Design in January 2011 and was appointed Associate Professor in Audio and Music Technology in 2016. He has written over 60 research articles and patents on different facets of immersive and interactive audio, including real-time audio signal processing, Ambisonics, virtual and augmented reality and recording and audio post-production technique development. He has undertaken innovative projects in collaboration with Mercedes-Benz Grand Prix, BBC, Dolby, Huawei, Abbey Road and Google amongst others. With the latter, he helped define the Google spatial audio pipeline through development of the SADIE binaural filters and decoders used worldwide. He is also an active sound engineer and producer of immersive audio experiences, working to develop new techniques and workflows for immersive music production in collaboration with Abbey Road Studios. He is Vice-Chair of the AES Audio for Games Technical Committee and was Co-Chair of the 2019 AES Immersive and Interactive Audio Conference at York. Gavin is particularly interested in supervising students with an audio background who wish to explore the following areas relating to audio for games Intelligent sound design Virtual Acoustics Spatial Audio Binaural sound Audio for Virtual and Augmented Reality Immersive audio experiences for next gen mobile platforms Ambisonics and spherical acoustics Using audio to enhance player emotional state (as well as projects on health and well-being) Game Audio for therapy Accessibility through Game Audio gavin.kearney@york.ac.uk Email Mastodon https://www.audiolab.york.ac.uk Other links Website https://www.linkedin.com/in/gavin-p-kearney LinkedIn BlueSky Github Themes Accessibility Applied Games Game AI Game Audio - Previous Next

  • Joshua Kritz

    < Back Joshua Kritz Queen Mary University of London iGGi PG Researcher Available for placement Graduated in Applied Mathematics in computer science, however my love for games pushed me to dedicate myself for studying them. This led me to brave many areas of knowledge, such as: psychology, design, education, production and entrepreneurship. My work as a teacher allowed me develop many of these skills in practice, besides invoking a new perspective about the world. On a personal level, I love new experiences that can teach me new knowledge and, most important, I am very open minded and easy to talk to! I believe discussion leads to enlightenment. A description of Joshua's research: Card games, in particular Trading Card Games (TCGs) thrive on using the synergy between the cards to create emergent and interesting gameplay. However, these games usually have hundreds of different cards to create such rich experience, with some older TCGs featuring thousands of different cards. With such a huge amount of different cards playtesting these games present a big challenge. In example a new set of Magic the Gathering takes over 3 years of development to be fully designed. But even considering simpler exemplars like Dominion or Assencion can be difficult to balance, and both games are known to need a few expansions of experience to indeed provide a well balanced experience. One way to make this task faster and easier is to use automated agents to playtest the game exhaustively and provide much needed data. Whilst this would assist card game development, it is not used in practice, the playtesting of card games is still completely done by players. Even with systematic playtesting there is a limit of how much of the possibilities humans can test. However, implementing playtesting of card games have two big challenges, which are the main reason it has not been implemented in practice yet. First: Automated agents are not great when playing a game with too many variables (different cards) Second: The possible combinations of cards used in a deck or set of a single game is huge. My research aim to address the second issue by using a theory of synergy between cards to reduce the search space necessary to properly evaluate a card game. j.s.kritz@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/joshua-kritz-38808379/ LinkedIn BlueSky Github Supervisor: Dr Raluca Gaina Featured Publication(s): A FAIR catalog of ontology-driven conceptual models A Conceptual Model for the Analysis of Investigation Elements in Games A Vocabulary of Board Game Dynamics Unveiling modern board games: an ML-based approach to BoardGameGeek data analysis When 1+ 1 does not equal 2: Synergy in games Towards an Ontology of Wargame Design Themes Applied Games Design & Development Game AI Previous Next

  • Dr Ahmed Sayed

    < Back Dr Ahmed M. A. Sayed Queen Mary University of London Supervisor Ahmed Sayed is a Lecturer (Assistant Professor) of Big Data and Distributed Systems at the School of EECS, QMUL and leads the Scalable Adaptive Yet Efficient Distributed (SAYED) Systems Lab. He has a PhD in Computer Science and Engineering from the Hong Kong University of Science and Technology. His research interests lie in the intersection of distributed systems, computer networks and machine learning. He is an investigator on several UK and international grants totalling nearly USD$1 million in funding. His work appears in top-tier conferences and journals including NeurIPS, AAAI, MLSys, ACM EuroSys, IEEE INFOCOM, IEEE ICDCS, and IEEE/ACM Transactions on Networking. He is interested in supervising students with a background in game AI, machine learning, distributed systems, and/or creative computing, Ahmed is interested in working with students at the intersection of artificial intelligence, machine learning, and creative computing. He aims to leverage AI/ML methods, game data and player research to design intelligent game agents by creating systems that enable game agents to learn better gaming strategies, thus enhancing the gaming experience. He is open to any research proposals in that space and currently is keen on exploring solutions that are based on leveraging the emerging distributed privacy-preserving ML ecosystems on large-scale game data. If you are interested in working with him on this, please reach out to him. ahmed.sayed@qmul.ac.uk Email Mastodon http://eecs.qmul.ac.uk/~ahmed/ Other links Website https://www.linkedin.com/in/ahmedmabdelmoniem/ LinkedIn BlueSky https://github.com/ahmedcs Github Themes Creative Computing Design & Development Game AI Game Data Player Research - Previous Next

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