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< Back Dr Shanxin Yuan Queen Mary University of London Supervisor Dr Shanxin Yuan is a Lecturer in Digital Environment at Queen Mary University of London. He has rich expertise in deep learning, low level computer vision, and 3D digital modelling of humans from photographs. His PhD thesis focused on 3D hand pose estimation, his work is well recognized in the academia and is also deployed into commercially launched mass market mobile phones. His current research on digital humans focuses reconstructing, modelling, and rendering digital twins. He is interested in super-realistic immersive gaming, body/hand pose and facial expression retargeting, and behaviour analysis with avatars. For the new project in 2023, we are interested in working on human facial expression estimation, high-res realistic face reconstruction and rendering, face re-enactment, and face augmentation. The aim of the project is to build an editable super-realistic 3D human face model that can express novel expressions, views, shapes, and appearance, from multiple sources of input, such as images, sounds, and key points. The related techniques include deep learning, computer vision, natural language processing, and neural rendering. shanxin.yuan@qmul.ac.uk Email Mastodon https://shanxinyuan.github.io/ Other links Website https://www.linkedin.com/in/shanxin-yuan-4859b656/ LinkedIn BlueSky Github Themes Applied Games Creative Computing Game AI Immersive Technology Player Research - Previous Next

< Back Janet Gibbs Goldsmiths iGGi Alum Janet is exploring how multi-modal perceptual feedback contributes to a player's sense of presence in the virtual world. Jaron Lanier described Virtual Reality (VR) as the substitution of the interface between a person and their physical environment with an interface to a simulated environment. This interface is of particular significance in understanding how presence depends on the nature, extent and veridicality of our sensorimotor interaction with the virtual environment, and how that relates to our normal engagement with the real world. In practice, only selected parts of the interface are substituted - we are never fully removed from our physical environment. Our perceptual apparatus evolved to make sense of changing sensations in multiple modalities originating naturally and coherently from the same event or percept. By contrast, in VR, individually crafted feedback using different technologies for each modality are coordinated to appear as if from a single source. VR benefits from a long history of visual and audio technologies, developed in harness for virtual experiences from cinema to computer games. Haptics is a relative newcomer that must be blended with them to create coherent multimodal perceptual experiences. Additionally, haptics is closely related to proprioception, and to the wide range of tactile senses—texture, heat, pain etc—that current VR systems do not address. Building on sensorimotor theory of perception, Janet aims to establish how our perceptual system responds to multi-modal feedback that almost, but not quite, matches what we are used to, in making sense of the simulated environment of VR. JGIBB016@gold.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Investigating Sensorimotor Contingencies in the Enactive Interface A comparison of the effects of haptic and visual feedback on presence in virtual reality Novel Player Experience with Sensory Substitution and Augmentation Investigating sensorimotor contingencies in the enactive interface Themes - Previous Next

< Back Guilherme Matos de Faria University of York iGGi Alum I am a Portuguese student with a background in Artificial Intelligence. In 2016 I started attending video game tournaments and learned to analyse my matches and improve from it. When I did my masters in AI, I noticed that I could join my professional skills and my hobbies together to create something relevant to AI and competitive gaming. A description of James' research: I am looking to better understand which actions and decisions have the biggest impact on the outcome of a game. Currently, I am particularly focused on competitive turn based card games. What are the best players doing to win? How can players adapt to improve their chances of success? These are the questions I am hoping to help answer, giving players a better understanding of the game and how to improve. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next

< Back Prof. Simon Colton Queen Mary University of London iGGi Co-Investigator Supervisor Simon Colton is an AI researcher with particular focus on issues of Computational Creativity, where we engineer software to take on creative responsibilities in art and science projects. He undertakes projects advancing the state of the art in generative technologies such as evolutionary approaches and deep learning, and uses these to help develop software such as The Painting Fool, The WhatIf Machine, the Wevva game designer, the HR3 automated code generator, and the Art Done Quick casual creator for visual art. In turn, these software systems and their output are used in cultural projects such as a poetry readings, art exhibitions, game jams, and even the production of a West-End musical. This enables Simon to undertake much public engagement, with coverage from the BBC, The Guardian, MIT Tech Review, The New Scientist and many others. These practical and cultural projects inform an evolving philosophical discourse around what it means for machines to be creative, and Simon has co-authored numerous essays driving forward our understanding of this important topic. In this way, he has helped to introduce ideas such as automated framing of products and processes, issues of authenticity and the notion of the machine condition, i.e., what the lived experience of a machine is, and how this could be expressed by that machine through creative production. He is particularly interested in supervising students in project where we apply generative technologies to applications in videogame design, visual art, software engineering, music and text generation. One particular current interest is stretching the boundaries of both what can be achieved by, and our understanding of, generation deep learning methods such as generative adversarial networks (GANs) and auto encoders. Another current interest is the design of casual creators, which are creativity support tools where the focus is on users having fun, rather than on efficient, professional production of artefacts. He is currently developing a casual creator for visual art called Art Done Quick for public release, which employs evolutionary and deep learning techniques to deliver a fun-first experience while users make decorative art pieces. Any project involving generative technologies is of interest to Simon. Research Areas: Game AI Game Audio and Music Game Design Computational Creativity Player Experience Casual Creators Generative Deep Learning s.colton@qmul.ac.uk Email Mastodon https://ccg.doc.gold.ac.uk/ccg_old/simoncolton/cv/ Other links Website LinkedIn BlueSky Github Themes Accessibility Creative Computing Game AI Game Audio Player Research - Previous Next

< Back Prof. Greg Slabaugh Queen Mary University of London Supervisor Gregory G. Slabaugh is Professor of Computer Vision and AI and Director of the Digital Environment Research Institute (DERI) at Queen Mary University of London. He is also a Turing Fellow at the Alan Turing Institute. His research work spans computer vision and computer graphics including geometric modelling and image/video-based understanding. He is interested in deep learning approaches including generative techniques like normalizing flow an generative adversarial networks. He previously worked in the games industry as a 3D graphics programmer and his PhD thesis focussed on how to model 3D objects from a collection of images. He is interested in how to create engaging content and interaction from images as well as procedural methods to reduce the effort of 3D modelling. g.slabaugh@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/~gslabaugh Other links Website https://www.linkedin.com/in/greg-slabaugh-a5b03a1/ LinkedIn BlueSky Github Themes Applied Games Creative Computing Immersive Technology - Previous Next

< Back Peter York University of York iGGi Alum PhD student working in analytics and machine learning for esports broadcast and understanding. In particular working with Weavr on various projects related to broadcast and learning tools for Dota 2. Please note: Updating of profile text in progress Email Mastodon https://pete-york.github.io Other links Website LinkedIn BlueSky Github Featured Publication(s): Data-Driven Audience Experiences in Esports Metagaming and metagames in Esports DAX: Data-Driven Audience Experiences in Esports A generalized framework for self-play training Themes Esports Game AI - Previous Next

< Back Dr Guifen Chen Queen Mary University of London Supervisor Dr Guifen Chen is a Lecturer in Neurobiology at QMUL. Her work focuses on the neuronal basis of multisensory integration, spatial cognition and memory. Her lab uses state-of-the-art techniques such as immersive virtual reality and in vivo electrophysiological/probe recording in mice. Her research is currently supported by funding from BBRSC and the Royal Society. Dr Chen completed her undergraduate studies in both biology and computer science at East China Normal University in China. She then pursued PhD in neuroscience, conducting research at both East China Normal University and Boston University in the USA. Following that, she undertook postdoctoral research at University College London in the UK. Her work has been published in high-impact journals such as Nature Communications, eLife, and Current biology. guifen.chen@qmul.ac.uk Email https://orcid.org/0000-0002-5459-660X Mastodon https://www.qmul.ac.uk/sbbs/staff/guifen-chen.html Other links Website https://www.linkedin.com/in/guifen-chen-51039973/ LinkedIn BlueSky https://github.com/annie2013 Github Themes Creative Computing Design & Development Immersive Technology Player Research - Previous Next

< Back Dr Adam Katona University of York iGGi Alum Adam did his MSc in mechatronics at Budapest University of Technology and Economics. After graduation, he spent two years working on automated driving at Robert Bosch GmbH, during which he got exposed to both the classical and the machine learning approach of creating intelligent agents. Evolutionary computation continues to surprise us by producing creative and efficient designs. However despite our best efforts, artificial evolution had not produced anything ascomplex and interesting as natural evolution. As our hardware is becoming faster and number of cores in our chips increase, the lack of computational power is becoming less of an excuse. It is starting to become more and more obvious that some fundamental component of natural evolution is missing from our simulations. One possible candidate is the evolution of evolvability. Evolution seems to produce organisms which are well suited for further evolution. The goal of my research is to find mechanisms which allows evolution to increase evolvability, and incorporate these in the design of more efficient neuroevolution algorithms.This research is in the intersection of evolutionary computation, evolutionary developmental biology and neural networks. mail.adamkatona@gmail.com Email Mastodon https://adamkatona.net/ Other links Website LinkedIn BlueSky https://github.com/adam-katon Github Featured Publication(s): Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Complex computation from developmental priors Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning Quality Evolvability ES: Evolving Individuals With a Distribution of Well Performing and Diverse Offspring Growing 3d artefacts and functional machines with neural cellular automata Time to die: Death prediction in dota 2 using deep learning Themes Game AI - Previous Next

< Back Stefan Stoican University of Essex iGGi Alum Understanding human crowd behaviour via virtual environments: feedback loop between games & research This project uses computer game experiments to explore decision-making in a virtual evacuation simulation. Can one be “saved by the gaze”? Currently, Stefan is investigating how innate social cognition components such as gaze-cuing might inform one’s egress. Do “Us versus Them” scenarios occur? He is also testing how one’s feelings of social identification with the surrounding crowd might modulate one’s risk-taking. Does hoarding prevent herding? Lastly, the project is looking at how cultural differences might affect egress time, when one insists to save personal possessions. More broadly, Stefan’s research concentrates on two key open questions in human crowd behavioural research. Firstly, how do social groups (that the player observes or is a member of) within the simulated crowd of agents affect both individual decision-making and the emergent behaviour of the crowd? Secondly, both empirical and virtual experiments of human crowds have not fully explored the effect of agent or player interactions with underlying landscape features (e.g. layout, signage, debris, large objects and other obstacles, etc). The outcomes of the experimental studies using real human participants will subsequently be used to develop more realistic decision-making and behavioural response algorithms and hence improve the behaviour of simulated agents in follow-on computer games. Stefan’s academic background may lie in Mathematics and Psychology, but his interdisciplinary mindset has constantly pushed him towards games and Computer Science. For his final Mathematics project, he designed an Android app that gamified teaching statistics. As part of his Psychology Masters degree, he investigated the potential benefits of MOBA games such as League of Legends with regard to visual attention. Currently, his extracurricular projects aim to explore video games’ effects on coping with trauma and on one’s perception of vulnerable groups, via commemorative gaming name choices or via in-game refugee storylines, respectively. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next

< Back Connor Watts Queen Mary University of London iGGi PG Researcher Available for placement I am a machine learning research engineer and software developer with commercial experience deploying and maintaining models for start-ups and larger organizations. I have experience researching and developing novel algorithms, as well as designing custom environments for application in domains such as combinatorial optimization, finance and games. c.watts@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/connor-watts-363354232/ LinkedIn BlueSky https://ConnorWatts.github.io Github Supervisor: Dr Paulo Rauber Themes Game AI - Previous Next

< Back Prof. Paul Cairns University of York iGGi Chair Supervisor Paul Cairns is a professor interested in Human-Computer Interaction (HCI) generally and specifically on how games work to produce the experiences that players really value. He has looked extensively at immersion and engagement in games but is also developing new ideas on players experiences of challenge and uncertainty. He has been teaching HCI for over twenty years and is particularly interested in the rigorous application of research methods having co-edited the first book on research methods for HCI and written another about doing better statistics in HCI. He strongly believes in self-explanatory book titles. He is also Scholar-in-Residence at The AbleGamers Charity, based in the USA, through which he is working with players and game developers to inform and advance the development of accessible games. With his colleagues there, he produced the Accessible Player Experiences (APX) design patterns and card deck. He is particularly interested in supervising students with a HCI, behavioural sciences, media or computer science background on the following topics: Understanding player experiences Developing new measures of player experience whether based on self-report, physiological or other instruments Accessible player experiences Using games to understand and inform people’s experiences with other interactive systems Research themes: Accessible Games Games with a Purpose Player Experience paul.cairns@york.ac.uk Email Mastodon https://www-users.cs.york.ac.uk/~pcairns Other links Website https://www.linkedin.com/in/paul-cairns-99a1b32/ LinkedIn BlueSky Github Themes Accessibility Applied Games Game Data Player Research - Previous Next

< Back Dr Valerio Bonometti University of York iGGi Alum Game analytics and player psychology: creating reliable models of player motivation Motivation can be loosely defined as a process of the brain and the mind, capable of driving and deeply shaping human behaviour. Motivational processes are embedded in many everyday life situations, exerting their effects via a wide range of incentive mechanisms and objects. Understanding this process in a videogame context, however, requires a more holistic approach considering not just the incentive properties of the game but also the player personal characteristics. My project aims to create reliable cross-games models of player motivation taking into account the contribution of natural inter individual variability. This will be accomplished linking in-game behavioural data and psychological models via a hybrid approach, where findings from small scale experimental studies (hypothesis-driven) will guide the realization of large scale (data-driven) applications for predicting players' characteristics, future behaviour and motivation evolution. Being able to model player motivation and predict the trajectories of its evolution could possibly lead to personalized and dynamic engagement strategies able to adapt accordingly to the player characteristics and in-game behaviour. Achieving a similar goal would be of pivotal importance in industrial and gamification contexts. I obtained my bachelor degree in Psychological Science and my master degree in Clinical Psychology at Padova University (Italy). During my academic path I acquired knowledge in general psychology, cognitive psychology, psychophysiology, neuroscience and research methodology. After my master degree I spent a considerable amount of time as a research trainee, both abroad and in my country, always investigating the reward process and its effects in various contexts. During this period I worked on various projects across different fields ranging from psychophysiology, player research and game analytics. In my free time I enjoy practicing indoor climbing and travelling, I like figurative art in general and more specifically I’m a huge cinema and graphic-novel enthusiast. Supervisors: Prof. Anders Drachen, Dr Sam Devlin Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): From Theory to Behaviour: Towards a General Model of Engagement Modelling early user-game interactions for joint estimation of survival time and churn probability Predicting skill learning in a large, longitudinal MOBA dataset Mind the gap: Distributed practice enhances performance in a MOBA game Approximating the Manifold Structure of Attributed Incentive Salience from Large-scale Behavioural Data: A Representation Learning Approach Based on Artificial Neural Networks Themes Player Research - Previous Next