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iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: ​ Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! ​ There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Medallia

< Back Esports How might we use esports data to create immersive audience experiences, help players and teams improve, and understand human performance? Project areas include: Modelling team formation and metagame strategies in multiplayer games << Previous Theme page Next Theme page >> iGGi >>> People <<< relevant to this Theme: Dr Tom Collins Supervisor ​ Game AI, Game Audio, Game Data, Player Research, Esports Read More Prof. Anders Drachen Supervisor ​ Player Research, Design & Development, Game Data, Esports Read More Dr Anne Hsu Supervisor ​ Applied Games, Design & Development, Player Research, Esports Read More Dr Athanasios Vasileios Kokkinakis iGGi Alum ​ Game AI, Player Research, Esports Read More Dan Cooke iGGi PG Researcher Available for placement Esports, Game Data, Player Research Read More Dr Phoebe Hesketh iGGi Alum ​ Player Research, Esports Read More Dr Patrik Huber Supervisor ​ Applied Games, Game Data, Immersive Technology, Player Research, Esports Read More Alan Pedrassoli Chitayat iGGi PG Researcher Available for post-PhD position Design & Development, Game Data, Esports Read More Dr Gaetano Dimita Supervisor ​ Applied Games, Creative Computing, Game AI, Player Research, Esports Read More Dr Jon Hook Supervisor ​ Applied Games, Player Research, Esports Read More Dr Ben Kirman Supervisor ​ Player Research, Creative Computing, Design & Development, Applied Games, Esports Read More Dr Charles Ringer iGGi Alum ​ Game AI, Game Data, Esports Read More Load More iGGi People working in this Theme iGGi >>> Publications <<< relevant to this Theme: Applying and Visualising Complex Models in Esport Broadcast Coverage A Pedrassoli Chitayat, F Block, JA Walker, A Drachen Proceedings of the 2024 ACM International Conference on Interactive Media Experiences, 2024 Alan Pedrassoli Chitayat View Details Money laundering through video games, a criminals' playground D Cooke, A Marshall Forensic Science International: Digital Investigation, Volume 50, 2024, 301802, ISSN 2666-2817 Dan Cooke View Details How Could They Win? An Exploration of Win Condition for Esports Narratives AP Chitayat, FO Block, JA Walker, A Drachen Annual Symposium on Computer-Human Interaction in Play (CHI PLAY 2024), 2024 Alan Pedrassoli Chitayat View Details System and method for training a machine learning model R Spick, G Moss, T Bradley, PV Amadori US Patent App. 18/513,849, 2024 Dr Ryan Spick View Details From Passive Viewer to Active Fan: Towards the Design and Large-Scale Evaluation of Interactive Audience Experiences in Esports and Beyond Alan Pedrassoli Chitayat, Alistair Coates, Florian Block, Anders Drachen, James Alfred Walker, James Dean, Mark McConachie, Peter York Proceedings of the 2024 ACM International Conference on Interactive Media Experiences, 2024 Alan Pedrassoli Chitayat View Details Behavioural Cloning in VizDoom R Spick, T Bradley, A Raina, PV Amadori, G Moss arXiv preprint arXiv:2401.03993, 2024 Dr Ryan Spick View Details Load More iGGi Publications for this Theme Previous Next

< Back The Effect of State Representations in Sequential Sensory Prediction: Introducing the Shape Sequence Task Link ​ Author(s) H Siljebrat, A Pickering Abstract ​ More info TBA ​ Link

< Back Formal Constraints and Creativity: Connecting Game Jams, Dogma ’95, the Demo Scene, OuBaPo, and Renga poets Link ​ Author(s) G Lai, I Vecchi Abstract ​ More info TBA ​ Link

< Back Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks Link ​ Author(s) M Akten Abstract ​ More info TBA ​ Link

< Back Thinking and doing: Challenge, agency, and the eudaimonic experience in video games Link ​ Author(s) T Cole, M Gillies Abstract ​ More info TBA ​ Link

< Back Player Research How might we use and combine diverse methods to understand how people experience games, interact with and through them, and are affected by them? Project areas include: Understanding and measuring player experience and motivation Using tools from neuroscience and psychology to understand emotion in game players Obtaining game player feedback without breaking immersion << Previous Theme page Next Theme page >> iGGi >>> People <<< relevant to this Theme: Doruk Balcı iGGi PG Researcher ​ Design & Development, Player Research Read More Prof. David Beer Supervisor ​ Player Research, Applied Games, Creative Computing, Game Data, Game AI Read More Dr Anna Bramwell-Dicks Supervisor ​ Game Audio, Player Research, Design & Development, Applied Games, Accessibility Read More Prof. Paul Cairns Supervisor ​ Applied Games, Player Research, Accessibility, Game Data Read More Dr Nick Ballou iGGi Alum ​ Player Research, Game Data Read More Toby Best iGGi PG Researcher Available for placement Game AI, Design & Development, Player Research Read More Dr Ivan Bravi iGGi Alum ​ Game AI, Player Research Read More Steph Carter iGGi PG Researcher Available for placement Applied Games, Design & Development, Player Research, Accessibility, Game Data Read More Prof. Richard Bartle Supervisor ​ Design & Development, Game AI, Player Research Read More Dr Valerio Bonometti iGGi Alum ​ Player Research Read More Prof. Nick Bryan-Kinns Supervisor ​ Applied Games, Creative Computing, Game Audio, Player Research Read More Dr Ignacio Castro Supervisor ​ Game AI, Applied Games, Player Research, Game Data Read More Load More iGGi People working in this Theme iGGi >>> Publications <<< relevant to this Theme: Can We Generate Realistic Hands Only Using Convolution? M Hosseini, P Hosseini arXiv preprint arXiv:2401.01951, 2024 Peyman Hosseini View Details An appraisal-based chain-of-emotion architecture for affective language model game agents M Croissant, M Frister, G Schofield, C McCall Plos one 19 (5), e0301033, 2024 Maximilian Croissant Madeleine Frister View Details Use of Technology in Brief Interventions L Gega, MJ Saiger Brief CBT and Science-Based Tailoring for Children, Adolescents, and Young Adolescents, and Young Adults, Springer, pp 293-309, 2024 Michael John Saiger View Details Applying and Visualising Complex Models in Esport Broadcast Coverage A Pedrassoli Chitayat, F Block, JA Walker, A Drachen Proceedings of the 2024 ACM International Conference on Interactive Media Experiences, 2024 Alan Pedrassoli Chitayat View Details Player Expectations of Strategy Game AI D Gomme University of Essex, 2024 Dr Daniel Gomme View Details How does Juicy Game Feedback Motivate? Testing Curiosity, Competence, and Effectance D Kao, N Ballou, K Gerling, H Breitsohl, S Deterding Proceedings of the CHI Conference on Human Factors in Computing Systems, 1-16, 2024 Dr Nick Ballou View Details Load More iGGi Publications for this Theme Previous Next

< 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 http://www.twitter.com/ahmedcs982 Twitter https://github.com/ahmedcs Github ​ ​ Themes Creative Computing Design & Development Game AI Game Data Player Research - Previous Next

< Back ​ Dr Henrik Siljebråt Goldsmiths ​ iGGi Alum ​ ​ Henrik has a background in IT/DevOps and a Masters in Cognitive Science from Lund University. Based on established neurobiological correlates of reinforcement learning (RL), I investigate animal learning and decision making using cognitive modeling techniques, such as probabilistic programming and machine learning. Animals somehow manage to create useful representations of incoming sensory information, representations then used for learning and decision making. How these representations of states of the world are integrated into task structure and models of the world is an open question, which I investigate using behavioural experiments with humans and bumblebees and modelling said behaviour using RL combined with hidden state models for representing states and task structure. The potential findings of these experiments have promise to not only elucidate the workings of the animal brain but also provide valuable contributions to artificial intelligence, where improved models of state representations could vastly improve data efficiency and generalizability over current generation systems. Please note: Updating of profile text in progress h.siljebrat@gold.ac.uk Email Mastodon https://henrik.siljebrat.se Other links Website https://www.linkedin.com/in/henrik-siljebrat LinkedIn https://twitter.com/foh Twitter https://github.com/fohria Github ​ Featured Publication(s): On State Representations and Behavioural Modelling Methods in Reinforcement Learning The Effect of State Representations in Sequential Sensory Prediction: Introducing the Shape Sequence Task Towards human-like artificial intelligence using StarCraft 2 Themes - Previous Next

iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: ​ Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! ​ There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. TT Games Limited

< Back Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities Link ​ Author(s) S Berns, T Broad, C Guckelsberger, S Colton Abstract ​ More info TBA ​ Link

< Back Defining the esports bettor: evidence from an online panel survey of emerging adults Link ​ Author(s) H Wardle, E Petrovskaya, D Zendle Abstract ​ More info TBA ​ Link