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< Back Dr Terence Broad Goldsmiths iGGi Alum 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. Email t.broad@gold.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link 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

< Back Andrei Iacob University of Essex iGGi Alum Identifying Immersion in games using EEG and other measures (Industry placement at Sony SIE) The project aims to identify markers for immersion in player’s EEG signals. A few steps towards it include designing an experiment that reduces data noise and helps identify time frames for immersion during gameplay, recording EEG data among other “tests” to improve the accuracy of the state localization on a timeline. This research could prove useful for the games industry in a few ways: - it can provide tools for game testing (e.g. which parts of the game are immersive, which parts lack in that aspect) – thus making it easier to improve the game experience across the board; - it could also be used in making real-time adjustments to games (increase / decrease difficulty levels, pace, etc. to enhance the player’s immersion). Although the EEG data is the main focus of the project, it is not the only one. Correlations will be analyzed between different tests and in-game behaviors that should render even more information regarding the player’s state and mindset during gameplay. This information will be just as valuable and perhaps more readily available for widespread use in the near future. Andrei is a keen programmer and gamer. He graduated with a BSc (Hons) in Computer Science from the University of Essex. Andrei’s research interests are in the field of brain- computer interfaces and computer games. His hobbies include programming, gaming, guitar and skiing. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Player Research - Previous Next

< Back Shopna Begum Queen Mary University of London iGGi Administrator iGGi Admin iGGi Administrator at QMUL Shopna is part of the iGGi Admin Team which is responsible for the smooth running of iGGi. In her role as iGGi QMUL Administator she provides administrative services and pastoral care to PhD students and assists the iGGi QMUL Manager in key aspects of the Centre's management. Email shopna.begum@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes - Previous Next

< Back Dr Poonam Yadav University of York Supervisor Dr Yadav research is focused on making the Internet of Things (IoT) and edge computing-based distributed systems resilient, reliable, and robust. This is an interdisciplinary research area that requires expertise in system design and integration along with knowledge of sensor systems, wireless networking, and domain and contextual understanding. To achieve resilience and reliability in the area of resource constraints and distributed systems, I focus on coordination and collaboration using interactions among machines, humans and data entities. These interactions could be categorized as machine-to-machine (M2M), machine-to-human (M2H), and human-to-data (H2D), and involve many challenges such as collaborative trust, privacy, legibility and accountability. Dr Yadav is an active reviewer of many top-tier ACM/IEEE IoT and networking conferences and journals. Dr. Yadav leads ACM-W UK professional chapter and is featured as "People of ACM Europe" and among the top ten N2Women Rising Star in Computer networking and communications in 2020. Research themes: E-Sports Use of IoT in Games Gamifications Citizen Science Email poonam.yadav@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Esports Game Data - Previous Next

< Back Dr Dino Ratcliffe Queen Mary University of London iGGi Alum Teaching AI agents transferable skills for game playing My research focuses on the ability of an AI agent to be able to evaluate the various skills it would need to master a game, such as in an FPS (first person shooter) like doom. If the agent can learn to cluster actions that may split into strategies such as attacking enemies, gathering ammo/health and avoiding enemy fire this information could then be used in similar games. This information would also provide a base for being to evaluate players on a skill level, giving a much more granular view of their strengths and weaknesses in any of these games. This could then be used for better matchmaking in team games, placing players into teams whose skill sets complement each other. Other applications include being able to guide the player into situations that give them more experience in the areas they are weakest. Dino started a MSci in computer science at the University of Essex in 2011. During the next 4 years, he focused on modules that involved improving technical skills and Artificial Intelligence. He was the winner of the K.F Bowden Memorial prize in two separate years. Dino worked at the London startup Signal Media during the summer of 2014 and continued to work for them part time during my masters year. He graduated with a 1st class degree. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Cross-lingual style transfer with conditional prior VAE and style loss Author's declaration Win or learn fast proximal policy optimisation Domain Adaptation for Deep Reinforcement Learning in Visually Distinct Games Clyde: A deep reinforcement learning doom playing agent Themes Game AI - Previous Next

PGRs (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. iGGi PG Researchers iGGi is a community formed of PG Researchers (PGRs), Supervisors, affiliated Partners from industry and academia, and supporting Administrators. The most essential part of this community is of course the group of currently over 70 active iGGi PGRs who, through their research in games and related fields, work on creating positive impact on and through games. Their research topics spread over a wide spectrum of areas, and while you can filter subjects of interest by theme, please see the individual profiles for more detailed information. Filter by iGGi Theme Accessibility Applied Games Creative Computing Design & Development Esports Game AI Game Audio Game Data Immersive Technology Player Research Filter by Location Filter by Start Year Filter by placement/work status Doruk Balcı iGGi PG Researcher Available for placement Design & Development, Player Research Read More Steph Carter iGGi PG Researcher Available for placement Applied Games, Design & Development, Player Research, Accessibility, Game Data Read More Tania Dales iGGi PG Researcher Available for placement Game AI, Design & Development, Immersive Technology, Player Research Read More Alex Flint iGGi PG Researcher Available for placement Design & Development, Player Research Read More Peyman Hosseini iGGi PG Researcher Player Research, Game AI Read More Cameron Johnston iGGi PG Researcher Available for placement Design & Development, Creative Computing Read More Gorm Lai iGGi PG Researcher Creative Computing, Game AI, Design & Development Read More George Long iGGi PG Researcher Available for placement Game AI, Design & Development, Game Data Read More Sahar Mirhadi iGGi PG Researcher Available for post-PhD position Player Research Read More Zoë O’Shea iGGi PG Researcher Design & Development, Immersive Technology, Player Research Read More Prasad Sandbhor iGGi PG Researcher Available for placement Applied Games, Design & Development Read More Philip Smith iGGi PG Researcher Available for placement Applied Games, Design & Development Read More Sunny Thaicharoen iGGi PG Researcher Available for post-PhD position Player Research, Game Data, Esports Read More Lauren Winter iGGi PG Researcher Design & Development, Player Research Read More Nirit Binyamini Ben Meir iGGi PG Researcher Available for placement Applied Games, Design & Development, Creative Computing Read More Karl Clarke iGGi PG Researcher Available for placement Design & Development, Immersive Technology, Player Research Read More Rory Davidson iGGi PG Researcher Available for post-PhD position Player Research, Applied Games, Design & Development Read More Francesca Foffano iGGi PG Researcher Available for post-PhD position Player Research Read More Tamsin Isaac iGGi PG Researcher Available for placement Applied Games, Design & Development, Player Research Read More Bobby Khaleque iGGi PG Researcher Available for post-PhD position Creative Computing, Game AI Read More Nicole Levermore iGGi PG Researcher Available for placement Design & Development, Immersive Technology, Accessibility, Player Research Read More Sarah Masters iGGi PG Researcher Available for post-PhD position Applied Games, Design & Development, Player Research Read More Prakriti Nayak iGGi PG Researcher Available for placement Applied Games, Accessibility, Player Research Read More Younès Rabii iGGi PG Researcher Available for post-PhD position Game AI, Creative Computing, Design & Development Read More Remo Sasso iGGi PG Researcher Game AI Read More Filip Sroka iGGi PG Researcher Game AI, Applied Games, Immersive Technology Read More Connor Watts iGGi PG Researcher Game AI Read More Oliver Withington iGGi PG Researcher Available for post-PhD position Game AI, Creative Computing, Design & Development Read More Toby Best iGGi PG Researcher Available for placement Game AI, Design & Development, Player Research Read More Dan Cooke iGGi PG Researcher Available for placement Esports, Game Data, Player Research Read More Ross Fifield iGGi PG Researcher Player Research Read More James Gardner iGGi PG Researcher Game AI Read More Dominik Jeurissen iGGi PG Researcher Game AI, Design & Development, Game Data Read More Joshua Kritz iGGi PG Researcher Available for placement Game AI, Applied Games, Design & Development Read More Océane Lissillour iGGi PG Researcher Available for placement Design & Development, Player Research Read More Dimitris Menexopoulos iGGi PG Researcher Available for post-PhD position Game Audio, Creative Computing Read More Dien Nguyen iGGi PG Researcher Available for placement Game AI, Applied Games, Design & Development, Creative Computing Read More Erin Robinson iGGi PG Researcher Design & Development, Immersive Technology Read More Amy Smith iGGi PG Researcher Available for post-PhD position Creative Computing, Player Research Read More Luiza Gossian iGGi PG Researcher Available for placement Applied Games, Design & Development Read More Tom Wells iGGi PG Researcher Available for placement Read More Ruizhe "Jay" Yu Xia iGGi PG Researcher Available for placement Game AI, Game Data Read More

< Back Dr Memo Akten Goldsmiths iGGi Alum Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression. This research investigates how the latest developments in Deep Learning can be used to create intelligent systems that enhance artistic expression. These are systems that learn – both offline and online – and people interact with and gesturally ‘conduct’ to expressively produce and manipulate text, images and sounds. The desired relationship between human and machine is analogous to that between an Art Director and graphic designer, or film director and video editor – i.e. a visionary communicates their vision to a ‘doer’ who produces the output under the direction of the visionary, shaping the output with their own vision and skills. Crucially, the desired human-machine relationship here also draws inspirations from that between a pianist and piano, or a conductor and orchestra – i.e. again a visionary communicates their vision to a system which produces the output, but this communication is real-time, continuous and expressive; it’s an immediate response to everything that has been produced so far, creating a closed feedback loop. The key area that the research tackles is as follows: Given a large corpus (e.g. thousands or millions) of example data, we can train a generative deep model. That model will hopefully contain some kind of ‘knowledge’ about the data and its underlying structure. The questions are: i) How can we investigate what the model has learnt? ii) how can we do this interactively and in real-time, and expressively explore the knowledge that the model contains iii) how can we use this to steer the model to produce not just anything that resembles the training data, but what *we* want it to produce, *when* we want it to produce it, again in real-time and through expressive, continuous interaction and control. Memo Akten is an artist and researcher from Istanbul, Turkey. His work explores the collisions between nature, science, technology, ethics, ritual, tradition and religion. He studies and works with complex systems, behaviour, algorithms and software; and collaborates across many disciplines spanning video, sound, light, dance, software, online works, installations and performances. Akten received the Prix Ars Electronica Golden Nica in 2013 for his collaboration with Quayola, ‘Forms’. Exhibitions and performances include the Grand Palais, Paris; Victoria & Albert Museum, London; Royal Opera House, London; Garage Center for Contemporary Culture, Moscow; La Gaîté lyrique, Paris; Holon Design Museum, Israel and the EYE Film Institute, Amsterdam. Please note: Updating of profile text in progress Email memo@memo.tv Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Top-Rated LABS Abstracts 2021 Deep visual instruments: realtime continuous, meaningful human control over deep neural networks for creative expression Deep Meditations: Controlled navigation of latent space Learning to see: you are what you see Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks Mixed-initiative creative interfaces Learning to see Real-time interactive sequence generation and control with Recurrent Neural Network ensembles Collaborative creativity with Monte-Carlo Tree Search and Convolutional Neural Networks Sequence generation with a physiologically plausible model of handwriting and Recurrent Mixture Density Networks Deepdream is blowing my mind All watched over by machines of loving grace: Deepdream edition Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks Themes Game AI - Previous Next

< Back Dr Debbie Maxwell University of York iGGi Research Collaboration Coordinator Supervisor Debbie is a lecturer in User Experience Design and Interactive Media at the Department of Theatre, Film and Television. Her background spans computing, HCI and Design and she currently teaches user experience (UX) design and design methods and critical design on the BSc Interactive Media programme. Her research focuses on the roles of traditional storytelling and engagement in digital contexts. I’m interested in the ways that people interact with and reshape technology through stories, as both method and artefacts, and across media. She is particularly focuses on applying design and stories across health and wellbeing and environmental design drawing on speculative design processes and approaches. Debbie uses interdisciplinary approaches that draw on a range of fields including Human Computer Interaction (HCI), ethnography, interaction design, social anthropology, and service design. Her research always involves working with communities using participatory methods. She is particularly interested in supervising students with a design or HCI background on the following topics: design of applied games for environmental education or knowledge exchange design and application of serious games to mental health and wellbeing contexts design and application of serious games to outdoor spaces, particularly cultural heritage settings Research themes: Games with a Purpose User experience design Design methods and ethnography Speculative design Email debbie.maxwell@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Design & Development Player Research - Previous Next

< 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 Email patrik.huber@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Esports Game Data Immersive Technology Player Research - Previous Next

Staff (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. Staff Staff involved in iGGi include the Supervisors of the iGGi PGRs, the iGGi Co-Investigators (i.e., academic members of staff who have specific roles within iGGi), and the iGGi Admin Team members. All of these people form part of the wider support network for iGGi PGRs. Our 60+ supervisors draw on close links to games industry/related academia, and are conducting interdisciplinary research in areas such as: Understanding player experience, games user research, and game analytics Game audio and music Using games and gamification to support wellbeing, learning, or social change Using esports and other game data to study human behaviour and psychology Interaction, user experience and learning design for games Using machine learning (ML) and other forms of artificial intelligence (AI) to create interesting, fun, believable game agents Augmented creativity tools that support game designers and developers, e.g. procedural content generation, AI-assisted game design and testing Using ideas from game AI to improve real-world decision making beyond games Filter by iGGi Theme Accessibility Applied Games Creative Computing Design & Development Esports Game AI Game Audio Game Data Immersive Technology Player Research Filter by Location All Staff / iGGi Staff / Externals Filter by Role Type - iGGi Management - - iGGi Management - Prof. Richard Bartle Supervisor University of Essex Design & Development, Game AI, Player Research Read More - iGGi Management - Susanne Binder iGGi Admin Queen Mary University of London Read More - iGGi Management - Prof. Paul Cairns Supervisor University of York Applied Games, Player Research, Accessibility, Game Data Read More Dr Tom Cole iGGi Alum + Supervisor Game AI, Design & Development Read More Dr Mike Cook Supervisor Game AI, Design & Development, Creative Computing Read More Dr Alena Denisova Supervisor University of York Applied Games, Player Research, Design & Development Read More Dr Abi Evans Supervisor University of York Design & Development, Immersive Technology, Player Research Read More Dr Dan Franks Supervisor University of York Game AI, Game Data Read More - iGGi Management - Dr Jeremy Gow Supervisor Queen Mary University of London Game AI, Creative Computing, Design & Development, Game Data Read More Dr Miles Hansard Supervisor Queen Mary University of London Game AI, Immersive Technology, Design & Development, Game Data Read More Dr Patrik Huber Supervisor University of York Applied Games, Game Data, Immersive Technology, Player Research, Esports Read More Dr Lorenzo Jamone Supervisor Queen Mary University of London Applied Games, Creative Computing Read More - iGGi Management - Dr Ben Kirman Supervisor University of York Player Research, Creative Computing, Design & Development, Applied Games, Esports Read More - iGGi Management - Prof. Simon Lucas Supervisor Queen Mary University of London Game AI Read More Dr Fiona McNab Supervisor University of York Applied Games Read More - iGGi Management - Dr Diego Pérez-Liébana Supervisor Queen Mary University of London Game AI, Game Data Read More Dr Paulo Rauber Supervisor Queen Mary University of London Game AI Read More - iGGi Management - Oliver Roughton iGGi Admin University of York Read More Dr William Smith Supervisor University of York Creative Computing, Design & Development, Game AI, Player Research Read More Prof. Marian Ursu Supervisor Goldsmiths Player Research, Creative Computing Read More Dr Sarah West Supervisor University of York Player Research, Accessibility, Design & Development Read More Dr David Zendle Supervisor University of York Game Data, Player Research Read More Dr Jen Beeston iGGi Alum + Supervisor University of York Accessibility Read More Dr Anna Bramwell-Dicks Supervisor University of York Game Audio, Player Research, Design & Development, Applied Games, Accessibility Read More Dr Ignacio Castro Supervisor Queen Mary University of London Game AI, Applied Games, Player Research, Game Data Read More Dr Tom Collins Supervisor University of York Game AI, Game Audio, Game Data, Player Research, Esports Read More - iGGi Management - Prof. Peter Cowling Supervisor Queen Mary University of London Game AI, Applied Games, Design & Development Read More - iGGi Management - Prof. Sebastian Deterding Supervisor Applied Games, Creative Computing, Design & Development, Player Research Read More Dr Ildar Farkhatdinov Supervisor Queen Mary University of London Design & Development, Game AI, Immersive Technology, Player Research Read More Dr Raluca Gaina iGGi Alum + Supervisor Queen Mary University of London Game AI Read More Dr Claudio Guarnera Supervisor University of York Applied Games, Creative Computing Read More Dr Jon Hook Supervisor University of York Applied Games, Player Research, Esports Read More - iGGi Management - David Hull iGGi Admin University of York Read More Dr Yul HR Kang Supervisor Queen Mary University of London Game AI, Player Research, Creative Computing, Immersive Technology Read More - iGGi Management - Prof. William Latham Supervisor Goldsmiths Creative Computing, Immersive Technology Read More - iGGi Management - Dr Debbie Maxwell Supervisor University of York Applied Games, Player Research, Design & Development Read More Prof. Damian Murphy Supervisor University of York Creative Computing, Game Audio, Immersive Technology Read More Prof. Massimo Poesio Supervisor Queen Mary University of London Applied Games, Game AI Read More Dr Josh Reiss Supervisor Queen Mary University of London Creative Computing, Game AI, Game Audio Read More Prof. Mark Sandler Supervisor Queen Mary University of London Game Audio Read More - iGGi Management - Helen Tilbrook iGGi Admin University of York Read More Prof. Alex Wade Supervisor University of York Player Research, Applied Games, Creative Computing, Game Data, Esports Read More Dr Andrew James Wood Supervisor University of York Applied Games, Design & Development, Game Data Read More - iGGi Management - Shopna Begum iGGi Admin Queen Mary University of London Read More Prof. Nick Bryan-Kinns Supervisor Queen Mary University of London Applied Games, Creative Computing, Game Audio, Player Research Read More Dr Guifen Chen Supervisor Queen Mary University of London Creative Computing, Design & Development, Immersive Technology, Player Research Read More - iGGi Management - Prof. Simon Colton Supervisor Queen Mary University of London Game AI, Game Audio, Creative Computing, Accessibility, Player Research Read More Dr Joe Cutting iGGi Alum + Supervisor University of York Player Research, Applied Games, Design & Development Read More Prof. Anders Drachen Supervisor Player Research, Design & Development, Game Data, Esports Read More - iGGi Management - Dr Catherine Flick Supervisor Accessibility, Applied Games, Player Research Read More Dr Lina Gega Supervisor University of York Applied Games, Player Research Read More Dr Christian Guckelsberger iGGi Alum + Supervisor Queen Mary University of London Game AI Read More Dr Anne Hsu Supervisor Queen Mary University of London Applied Games, Design & Development, Player Research, Esports Read More Dr Jo Iacovides Supervisor University of York Applied Games, Design & Development, Player Research Read More Dr Gavin Kearney Supervisor University of York Accessibility, Applied Games, Game AI, Game Audio Read More Dr Mariana Lopez Supervisor University of York Applied Games, Game Audio Read More Dr Cade McCall Supervisor University of York Applied Games, Game Data, Player Research Read More Prof. Nick Pears Supervisor University of York Game AI, Creative Computing Read More Prof. Matthew Purver Supervisor Queen Mary University of London Creative Computing, Game AI Read More Dr Søren Riis Supervisor Queen Mary University of London Game AI, Game Data, Creative Computing Read More Prof. Greg Slabaugh Supervisor Queen Mary University of London Applied Games, Creative Computing, Immersive Technology Read More - iGGi Management - Dr Laurissa Tokarchuk Supervisor Queen Mary University of London Immersive Technology, Creative Computing, Player Research, Applied Games, Game AI Read More - iGGi Management - Dr James Walker Supervisor University of York Game AI, Game Data, Creative Computing, Esports Read More Dr Poonam Yadav Supervisor University of York Design & Development, Game Data, Esports Read More

< Back Lisa Sha Li University of York iGGi Alum Gifting in video games (Industry collaboration with BT) Lisa’s research is an exploration of gifting behaviour in video games. In the fields of social science and positive psychology, a considerable amount of research has found out how being generous, and its incarnation in gifting can benefit one’s subjective well-being. However, when it comes to the digital space, little do we know about how people can become happier through gifting. On the one hand, the research is curious about whether the practice of gifting changes in the context of video games. If it changes, the research attempts to identify what features thereof are different or even new, and to understand how gifting protocols could function in the digital space. On the other hand, the research is curious about how to apply gifting to video games, employing its benefits in enhancing social relationships and good feelings. The current purpose is to propose a framework of gifting between a human player and non-player characters that designers can use as an instruction when designing such activities. There is also a potentially high value of gifting in the marketing aspect of the game industry. Inspired by the observation of everyday life, Lisa tries to find better solutions to problems which need to be considered from both artistic and informatics perspectives. She is now a research student at the University of York. She is a graduate of the University of Edinburgh where she received an MSc in Advanced Design Informatics, with Distinction. Her earlier degree is B.Eng in Digital Media Arts (Xiamen University, Software School). She spent half a year in Taiwan as an exchange student in 2012. She did a summer internship developing VR games with the Two Big Ears, back in 2014. Email shali.8.lisa@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Player Research - Previous Next

< Back Dr Dan Franks University of York Supervisor Dr Franks is an interdisciplinary researcher and data scientist interested in AI and machine learning. He is experienced in developing and applying evolutionary computation and machine learning methods to understanding behaviour. He is an internationally recognized leader in interdisciplinary research, has published in top journals such as Science and PNAS. Some of his papers are in the top 1% of all papers for media coverage (altmetric), and his work is regularly covered by The New Scientist, National Geographic, Wired, The BBC, The Guardian, The Times, among others. As Reader in the York Centre for Cross-disciplinary Systems Analysis, Dan works on applying AI, machine learning, and agent-based modelling, to problems in other disciplines. Particular interests involve the development of machine learning methods for creating intelligent AI and for understanding complex systems. Research themes: Game AI Game Analytics Email daniel.franks@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI Game Data - Previous Next