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< Back Measuring game experience using visual distractors Link ​ Author(s) J Cutting Abstract ​ More info TBA ​ Link

< Back ​ Dr Charles Ringer University of York ​ iGGi Alum ​ ​ Charlie Ringer is a researcher interested in applied Machine Learning with a focus on the ways in which we can use Deep Learning to model various facets of video games streams (e.g. stream highlights, emotional moments, in-game events, various streamer behaviours etc.). As such, his work spans many Machine Learning fields, such as Computer Vision, Affect Computing, and Natural Language Processing. His research has three motivating factors. Firstly, the challenge of how to fuse multi-view stream data (e.g. audio, web-cam footage, game footage, chat) into a single model, especially when considering the challenges of ‘in-the-wild’ data. Secondly, the untapped and bountiful data source that livestreaming represents, especially regarding the way in which streamers play games and interact with their audience. Thirdly, the exciting and emerging field of self-supervised learning which has the potential to utilise this abundance of livestream data. Charlie initially worked in the video games industry working mainly on the Magic: The Gathering - Duels of the Planeswalkers series of games before studying a BSc in Computer Science at Goldsmiths, University of London. After his BSc he joined IGGI, firstly at Goldsmiths and then at York. He was recognised as a finalist for the Twitch Research Fellowship 2019 for his research on livestream data. ​ charles.ringer@york.ac.uk Email Mastodon https://www.charlieringer.com Other links Website https://www.linkedin.com/in/charlie-ringer/ LinkedIn https://www.twitter.com/charlieringer Twitter https://www.github.com/charlieringer Github ​ Featured Publication(s): Machine Learning with Applications From Theory to Behaviour: Towards a General Model of Engagement Modelling early user-game interactions for joint estimation of survival time and churn probability Time to die 2: Improved in-game death prediction in dota 2 Autohighlight: Highlight Detection in League of Legends Esports Broadcasts via Crowd-Sourced Data Multi-Modal Livestream Highlight Detection from Audio, Visual, and Language Data Twitchchat: A dataset for exploring livestream chat Multimodal joint emotion and game context recognition in league of legends livestreams Themes Esports Game AI Game Data - Previous Next

< Back The 2016 two-player gvgai competition Link ​ Author(s) RD Gaina, A Couëtoux, DJNJ Soemers, MHM Winands, T Vodopivec, ... Abstract ​ More info TBA ​ Link

< Back iGGi Game Jam 2024 - We Made It!! After 48 hours of intense but not-too-intense game-making, we've assembled for play-testing and general socialising. Overwhelmingly positive feedback suggests that this year's iGGi Game Jam was a success! Following tradition, we also gave out some awards. (The trophies were charmingly designed and 3D printed by the organising team!) Here are the winning teams of the iGGi Game Jam 2024 Awards: Best Vision CONGRATS to the Winning Team: Team Crazy Skiing ( Joshua Silveira Kritz , Nicole Levermore, Anthony Owen) with their game “Ultimate Ski Brawl” Best Mechanic CONGRATS to the Winning Team: Project Googly Eyes ( Toby Best , Daniel Cooke, Callum Deery , George L. ong, Sunny Thaicharoen ) with their game “See What Exists” Best Bug CONGRATS to the Winning Team: Retina Racer ( Karl Clarke , Dominik Jeurissen , Marko Tot , Ruizhe Yu Xia ) with their game Retina Racer Best Narrative/Immersive Experience CONGRATS to the Winning Team: Nice Dynamite ( Ross Fifield , Charline Foch , Bobby Khaleque , Oliver Withington , Kyle Worrall , Michael Saiger ) with their game “Phantom Frames” Best Art Direction CONGRATS to the Winning Team: The Moss Collective ( Nirit Binyamini Ben Meir , Dimitris Menexopoulos , Erin Robinson) with their game “Moss Dance” Last but not least, MASSIVE THANKS go to the organising team who ensured that this year's jam turned into the enjoyable event that it was! Namely: Toby Best, Karl Clarke, Océane Lissillour, Francesca Foffano, Alan Pedrassoli Chitayat, Jeremy Gow, Ben Kirman ​ Previous 12 Jan 2024 Next

< Back Fireworks agent competition Link ​ Author(s) J Walton-Rivers Abstract ​ More info TBA ​ Link

< Back Hardness in Markov Decision Processes: Theory and Practice Link ​ Author(s) M Conserva, P Rauber Abstract ​ More info TBA ​ Link

< Back ​ Dr Jon Hook University of York ​ Supervisor ​ ​ Jon Hook is a Senior Lecturer (equivalent to an Associate Professor) in Interactive Media in the Department of Theatre, Film, Television and Interactive Media at the University of York. His research is situated in the field of Human-Computer Interaction (HCI) and explores the design and development of new interactive media content forms and tools to support their creation. This research combines his deep interest in new forms of interactive technology and media with empirical, theoretical and methodological perspectives, in the human-centred design of novel interfaces and interaction techniques for a broad range of artistic and everyday creative practices. His current research is focused on the design and development of new forms of responsive and immersive media content, with a particular interest in data-driven storytelling. He was recently the principal investigator of the EPSRC funded Perspective Media: Personalised Video Storytelling for Data Engagement project. He also a co-investigator of the InnovateUK WEAVR: Pioneering Fully Integrated Cross-Reality Spectator Experiences in Esports and Beyond immersive experiences demonstrator and the Digital Creativity Labs – a £4m EPSRC, AHRC and InnovateUK funded research centre exploring impact-driven research in the creative industries. He was also previously Co-I of the AHRC Within the walls of York Gaol: Memory, Place and the Immersive Museum the AHRC Digital Creativity for Regional Museums: Immersive Experiences Smart Commissioning Toolkit. He is especially interested in supervising students who’d like to do HCI research that involves making and evaluating new interactive media experiences. Some example topic areas that he might be the right supervisor for include, but aren’t limited to: Games to support broader data engagement and literacy Data-driven storytelling in, and about, games The intersection between games and interactive documentary film Responsive and interactive video storytelling in games The space where theatre and games converge Cultural heritage engagement using games Research themes: Game Design Games with a Purpose E-Sports Player Experience ​ jonathan.hook@york.ac.uk Email Mastodon https://www.jonhook.co.uk Other links Website https://www.linkedin.com/in/jonathan-hook-641b597/ LinkedIn https://twitter.com/jonathanhook Twitter https://github.com/jonathanhook Github ​ ​ Themes Applied Games Esports Player Research - Previous Next

< Back Data-Driven Audience Experiences in Esports Link ​ Author(s) A Kokkinakis, [...] P York, A Pedrassoli Chitayat, [...] B Kirman, J Hook, A Drachen, M Ursu, F Block Abstract ​ More info TBA ​ Link

< Back University of York (UoY) iGGi York is located just outside the City of York's centre, on University of York's East Campus. The Computer Science building (where our iGGi offices are) is located by the Lake. Please see map of the campus . How to reach the campus Details of how to reach the campus can be found on UoY web page Transport, maps and parkings . See also the information provided below. Arriving by car There is parking on Campus East. Please note that car parks are pay and display. The postcode for Campus East is YO10 5GY The nearest car parks to the venue are on Kimberlow Lane. Please see pay and display parking for location of the three car parks. There are usually plenty of spaces available. (Please note that when you view the map it automatically shows Campus West which also has a lake. You will need to swipe the map to the left to see Campus East). You will approach the car parks on Kimberlow Lane via Field Lane or Hull Road depending on which direction you are travelling from. (Please note that Lakeside Way is closed to traffic). When you view the map, the meeting and conference venue is near the small lake, which is named ‘Lake’ on the map and is just off Lakeside Way. Public Transport from York Train Station If you wish to use public transport from the hotel and/or from York Station to the campus, please see Map of York and campus Bus routes 66 and 67 go near the hotel and station and to the campus. You should alight at University of York, Campus East Coach Stop (see Field Lane on the map). Route 66 bus timetable & Timetable Route 67 bus timetable After getting off the bus, walk down the slope towards the lake. iGGi University of York Gallery Computer Science Building - University of York, Campus East Ron Cooke Hub - University of York, Campus East Piazza Building - University of York, Campus East Map of Campus East, University of York Previous Next

< Back System and method for training a machine learning model Link ​ Author(s) R Spick, G Moss, T Bradley, PV Amadori Abstract ​ More info TBA ​ Link

< Back Computer aided design of handwriting trajectories with the kinematic theory of rapid human movements Link ​ Author(s) D Berio, FF Leymarie, R Plamondon Abstract ​ More info TBA ​ Link

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