Search Results

< Back Dr Laura Helsby University of York iGGi Alum Laura Helsby is a HCI researcher with a background in psychology, currently examining how features of games might be beneficial to wellbeing and mood. She is particularly interested in how people with persistent low mood play and experience games, and what this might mean for their wellbeing. So far, she has conducted one interview study asking people with low mood what they play and why, and one diary study investigating the 'in the moment' effects and motivations for gaming. Future plans involve making more direct measures of the impact of particular games on wellbeing, as well as looking further into the FPS and simulation genres to unpack what about these games might make them appealing to people with persistent low mood. Laura has achieved an MSc in Foundations in Clinical Psychology from Newcastle University and a BSc in Psychology from the University of York. In her spare time, Laura enjoys denying she is a computer scientist at all. Her hobbies include reviewing books professionally, board game nights and of course, playing video games. laura.helsby@york.ac.uk Email Mastodon Other links Website LinkedIn https://bsky.app/profile/laurahelsby.bsky.social BlueSky Github Supervisors: Prof. Paul Cairns Dr Jo Iacovides Featured Publication(s): "Leave our kids alone!": Exploring Concerns Reported by Parents in 1-star Reviews Do People Use Games to Compensate for Psychological Needs During Crises? A Mixed-Methods Study of Gaming During COVID-19 Lockdowns Themes Applied Games Player Research - Previous Next

< Back Dr Myat Aung University of York iGGi Alum Immersion is a state in which players are engaged to a degree of total absorption that inhibits the ability to correctly report one’s surroundings or time. Present theory on immersion has developed a coherent model that provides sufficient evidence to distinguish itself from other cognitive concepts such as presence, attention, selective attention, absorption and flow. However, immersion research thus far has been hindered by difficulties with taking in-vivo measurements of cognition and physiological responses during videogame play. This presents an ideal opportunity for implementations of neuroimaging methods to carry out such real time measurements of attention, as well as other cognitive processes and their roles in videogame immersion. Using various combinations of neural and physiological methods such as skin conductance, eye tracking, electroencephalography and even functional magnetic resonance imaging, it is now possible to obtain richer data in immersion research. The goal of this project is to apply such methods in order to better define and measure videogame immersion, identify the cognitive processes and hierarchical models that are involved in immersion and ultimately contribute to the literature in videogame immersion. Though neuroimaging is limited by statistical sensitivity, challenging experimental logistics and non-ideal lab environments, they are still presently the best tools available to obtain fine-grain data of attention and the many other cognitive components of immersion. Such knowledge would contribute significantly to a better understanding of effective development of videogames, as well as educational tools. I am an MPsych Psychology graduate from the University of York, having studied Psychology, Cognitive Neuroscience & Neuroimaging for four years. My Master’s research was primarily in vision, attempting to manipulate and record parahippocampal responses to visual stimuli selected parametrically by computer algorithms. During my degree I also spent much of my time researching videogames, studying the literature on the effects of videogame play on sleep, and working with a IGGI PhD student as a lab assistant. Between my degree and my PhD, I have also been working as a data analyst at Digital Creativity Labs researching skill learning in large gaming populations from Riot Games’ League of Legends. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Different rules for binocular combination of luminance flicker in cortical and subcortical pathways Investigating the non-disruptive measurement of immersive player experience The trails of just cause 2: spatio-temporal player profiling in open-world games Predicting skill learning in a large, longitudinal MOBA dataset Themes Game AI - Previous Next

< 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. shali.8.lisa@gmail.com Email Mastodon Other links Website LinkedIn BlueSky Github Themes 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 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 Nirit Binyamini Ben Meir Queen Mary University of London iGGi PG Researcher Available for placement Nirit Binyamini Ben-Meir is a designer/ artist based in London. Her work explores the interconnection between society, technology and ecology. She is an Associate Lecturer at the Royal College of Art London, where she gained her MA in Information Experience Design. She has a professional background in visual communication and interaction design. She uses participatory installations, digital tools and responsive plants to create experiences for humans to interact with their biosphere. She combines ecological systems with technology to challenge human perception and provoke thought about bioethics, power relations, and the Anthropocene implications. Nirit’s main research interests are around More-Than-Human Interactions and the integration of living organisms into digital interactions. She investigates how these hybrid interactions may help mediate relatable, sensory experiences with plants and influence people's attitudes towards ecological stewardship. She is developing the Bio-Digital Garden concept, which combines computational elements and living moss, a responsive plant that gives qualitative visual feedback to changes in its environment in real-time. Her exploration focuses on the potential of using human-computer-plant to identify current weak points in pro-environmental behaviour and care for non-human entities, as well as influence people's perceived accountability through tangible feedback, bridging time-scale gaps, and generating a sense of urgency. n.binyaminiben-meir@qmul.ac.uk Email Mastodon https://niritbin.com/ Other links Website LinkedIn BlueSky Github Supervisors: Prof. Sebastian Deterding Featured Publication(s): Domestic Cultures of Plant Care: A Moss Terrarium Probe Experience as a transformational practice Design Methods for Accessing the Pluriverse Forging new narratives Themes Applied Games Creative Computing Design & Development - Previous Next

< Back Dr Anthony Constantinou Queen Mary University of London Supervisor Anthony Constantinou’s research is on Bayesian Artificial Intelligence for causal discovery and intelligent decision making under uncertainty. He applies his research to a wide range of areas, including gaming, sports, medicine and finance. He is the founder of the Bayesian Artificial Intelligence research lab at Queen Mary University of London. He is interested in supervising students who are interested in working with machine learning algorithms that discover causal relationships from data (applied to game data), or building intelligent decision-making models using Bayesian networks (applied to game data). Please note that these projects focus on working with game data. Students interested in these projects should have skills that are relevant to: Machine learning for causal discovery Bayesian networks Statistics and probability theory a.constantinou@qmul.ac.uk Email Mastodon https://www.constantinou.info Other links Website https://www.linkedin.com/in/anthony-c-constantinou-728b6b49/ LinkedIn BlueSky Github Themes Game AI - 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

< Back Dr David Zendle University of York Supervisor David Zendle is an active researcher into the effects of both video games and gambling, and is the author of several key references on the topic of video game monetisation. His most well-known publications deal with the potential effects of loot boxes. His recent work focuses on understanding the diversity of ways that video game play impacts wellbeing, and involves the analysis of large-scale datasets of player behaviour and spending. David is an academic affiliate of the Behavioural Insights Team and holds a research position within the NHS. He is particularly interested in building evidence-based policy in the domain of video game regulation, and has provided oral testimony on video game effects to a variety of government investigations across the globe. David is particularly interested in supervising students with an industry, economics, legal, or behavioural sciences background. He is interested in work on the following topics: The long-term effects of video game play (both positive and negative) Video game monetisation Video game regulation and policy Dark video game design Research themes: Game Analytics Game effects Game policy david.zendle@york.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game Data Player Research - Previous Next

< Back Dr Ozan Vardal University of York iGGi Alum Ozan studied undergraduate psychology at the University of Groningen, and holds a master's degree in Performance Psychology from the University of Edinburgh, where he wrote theses on the dynamics of psychological momentum in sport competition and the decision-making of expert applied psychologists respectively. He has long been fascinated with the psychological mechanisms underpinning complex skills, owing to his own background as a classically trained musician and his previous work as a performance psychology consultant with competitive athletes. His primary research interests involve the behavioural and neural factors surrounding human learning and skilled performance. A description of Ozan's research: Ozan views games as behaviourally rich environments for the study of complex skills and human learning. The competitive and immersive nature of games encourages millions of players to develop profound skill over hours, days, and even years of practice. Ozan’s work takes advantage of large data repositories generated by such players to study how different patterns of practice result in differences in learning outcomes. He also uses experimental methods in his work, and is currently using neuroimaging methods (MEG) and modelling techniques to identify how shifts between different behavioural and neural states affect performance as people play Tetris. By using games as a vehicle to study psychology, Ozan aims to develop scalable solutions to studying human learning. He hopes for a future where the science of learning is sufficiently advanced, such that (artificial) trainers can recommend optimised practice schedules for motivated learners, in any performance domain. Please note: Updating of profile text in progress ov525@york.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/ozanvardal LinkedIn BlueSky https://www.github.com/ozvar Github Featured Publication(s): Mind the gap: Distributed practice enhances performance in a MOBA game Themes Design & Development Esports Game Data - Previous Next

< Back Dr Josh Reiss Queen Mary University of London Supervisor Josh Reiss investigates transformative technologies focused around audio production and sound design. He has published more than 200 scientific papers (including over 50 in premier journals and 5 best paper awards), and co-authored two books. His research has been featured in dozens of original articles and interviews on TV, radio and in the press. He is a Fellow and former Governor of the Audio Engineering Society. He co-founded the highly successful spin-out company, LandR, and recently formed a second start-up, FXive. He maintains a popular blog, YouTube channel and twitter feed for scientific education and dissemination of research activities. Prof. Reiss has a strong interest in games research, especially procedural audio content generation. Procedural content generation supports creation of rich and varied games, maps, levels, characters and narrative elements. But sound design has not kept pace with such innovation. Often the visual aspects of every object in the scene may be procedurally rendered, yet sound designers still rely on huge libraries of pre-recorded samples. This approach is inflexible, limited and uncreative. An alternative is procedural audio, where sounds are created in real-time using software algorithms. But many procedural audio techniques are low quality, computational, or tailored only to a narrow class of sounds. Machine learning from the sample libraries, to select, optimise and improve the procedural models, could be the key to transforming the industry and creating procedural auditory worlds. He welcomes the opportunity to supervise students interested in this or related topics. Research themes: Procedural Content Generation Game Audio and Music Game AI Game Design Computational Creativity Player Experience joshua.reiss@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/~josh/index.htm Other links Website https://www.linkedin.com/in/reissjoshua/ LinkedIn BlueSky Github Themes Creative Computing Game AI Game Audio - Previous Next

< 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. 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