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< Back Dr Nathan John Queen Mary University of London iGGi Alum After graduating with a MEng in Computer Science from the University of Bristol, Nathan joined the games industry as a programmer, working for Climax Studios, Gaming Corps and Freejam, before moving to a career as a general software engineer, while still developing indie games on the side. His experiences across a range of industries sparked a passion for testing, and left him wondering if there were was to improve the automated testing in game development. Borne from an experiment Nathan had performed training AIs to play his indie game WarpBall, in which he found the agents solved for exploits in the authored AI rather than playing the game well, his research project proposes a novel method for improving the quality of behaviour of human authored agents by pitting them against trained agents and observing what bad behaviours/exploits the trained agents reveal. Authored agents refer to AI agents whose actions are explicitly designed by programmers using traditional techniques such as Utility functions, Behaviour Trees and state machines; trained agents refer to agents whose behaviour is learned by playing many games against the authored agents. n.m.john-mcdougall@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/vethan4/ LinkedIn BlueSky Github Supervisors: Dr Jeremy Gow Dr Laurissa Tokarchuk Themes Design & Development Game AI - Previous Next

< Back Dr David Gundry University of York iGGi Alum Using Applied Games to Motivate Speech Without Bias (Industry placement Lightspeed Research) Eliciting linguistic data faces several difficulties such as investment of researcher time and few available participants. Because of this, many language elicitation studies have to make do with few subjects and coarse sampling rates (measured in months). It would be ideal if a game could crowd-source relevant linguistic data with frequent, short game sessions. To this end, David’s research is looking into how games shape and elicit players’ linguistic behaviour. The established design patterns of gamification do not apply to a domain that lacks a ‘correct’ answer like language or personal beliefs and attitudes. David’s research shows how a player’s strategic goals will systematically bias data collection. It also shows how to design around this. The conclusion: The player’s choice of how to express a given datum must be strategically irrelevant in the game. David can remember the halcyon days when he had the free time to play games. Now he’s doing a PhD and has a one-year-old. He has an background in linguistics. He loves writing expressive code and designing clever little games. He wants to show that research games can be fun, not just effective. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Trading Accuracy for Enjoyment? Data Quality and Player Experience in Data Collection Games Designing Games to Collect Human-Subject Data Validity threats in quantitative data collection with games: A narrative survey Busy doing nothing? What do players do in idle games? Intrinsic elicitation: A model and design approach for games collecting human subject data Themes Applied Games - Previous Next

< Back Dr Fiona McNab University of York Supervisor During a postdoc at the Karolinksa Institute in Stockholm, Fiona investigated working memory and attention, providing empirical support for a role for the basal ganglia in the control of access to working memory and identification of changes in the dopamine system related to working memory training. At The Wellcome Trust Centre for Neuroimaging, UCL, with a Wellcome Trust Career Development Fellowship, she designed the working memory game in the large-scale smartphone study; “The Great Brain Experiment ”, leading to studies of different types of distraction in younger adults as well as in healthy ageing. In 2013 she moved to Birmingham University, where she conducted fMRI and behavioural studies of attention and working memory, and behavioural studies of the effects of competition on working memory. Fiona is now a lecturer in the Department of Psychology at the University of York. She is using fMRI and behavioural studies to investigate what limits working memory, how different types of distractors are successfully ignored and how working memory changes through development, with healthy aging, as well as in certain patient groups. Part of her work uses data from a new set of working memory games, which are currently available to play (York Memory Games, YORMEGA ). She is particularly interested in supervising students on the following topics: Understanding the limitations of working memory and the role of attention using games Understanding age-related changes in cognition using games, Cognitive training using games. Research themes: Game Design Games with a Purpose Player Experience Gamification Games for Cognition Research Games for Cognitive Training fiona.mcnab@york.ac.uk Email Mastodon https://www.york.ac.uk/psychology/staff/academicstaff/fm841/ Other links Website LinkedIn BlueSky Github Themes Applied Games - Previous Next

< Back Sarah Masters University of York iGGi PG Researcher Available for post-PhD position Sarah is an artist, game developer and researcher. They have an MA in Indie Game Development from Falmouth University (Distinction), where they created the city-building card game Eudaimonia. They are an active part of the games community taking part in game jams and setting up their own commercially focused studio. Sarah's work takes a research through design approach making and exploring games as an art form for change, collaborative design, speculative futures including 'ecopunk' and how we design games to meaningfully engage and entertain. Alongside a portfolio of games, their previous work includes running a workshop on Solarpunk vs Grimdark concepts. Their work also explores sustainable design and development practices to create emotional, engaging and meaningful experiences that can be a part of a greener industry and engage in climate change conversation. sarah.masters@york.ac.uk Email https://mastodon.gamedev.place/@sarah https://sarahdotgames.itch.io/ Mastodon https://sarah.games/ Other links Website https://www.linkedin.com/in/sarah-games/ LinkedIn BlueSky https://github.com/Impalpably Github Featured Publication(s): Radical Alternate Futurescoping: Solarpunk versus Grimdark Radical Alternate Futurescoping: Solarpunk versus Grimdark Better Dead than a Damsel: Gender Representation and Player Churn Themes Applied Games Design & Development Player Research Eudaimonia: A solarpunk city-building choice and consequence game - Save the world in eight years!: Fatalis - a witchy gardening game: Previous Next

< Back Dr Siamak Shahandashti University of York Supervisor Dr Siamak Shahandashti is a Lecturer (Assistant Professor) in Cyber Security Siamak has extensive experience in designing cryptographic solutions to enhance security and privacy for applications such as electronic voting, auctions, and biometric authentication systems. He has also worked on the security and privacy of password managers, IoT devices, mobile phone sensors, contactless payment, and paper fingerprinting. Siamak is interested in designing systems for improving security and privacy that are easy to use and accessible. He is working on designing usable password strength meters and human verifiable cryptographic codes. Siamak is a core member of the York Interdisciplinary Centre for Cyber Security and an expert fellow of the UK Network on Security, Privacy, Identity, and Trust in the Digital Economy (SPRITE+) He is a co-inventor on multiple patents including the first verifiable e-voting system trialled in the UK (patents US15582447, GB1607597) and paper fingerprinting (patent US15972922) with applications in banknote security. He led the design of the broadcast encryption deployed in millions of Thales’s Pay TV products worldwide. Siamak was part of teams who found vulnerabilities and fixed several systems, including the ISO/IEC11770-4 standard for password-based key exchange used in billions of devices, major mobile browser (Chrome, Firefox, Opera, Safari) sensor access policies, and Bitcoin's Payment Protocol used by 100k+ merchants. He is particularly interested in supervising students on the following topics: Using gamification to improve security and privacy in applications such as authentication and human verification Investigating and improving security and privacy in game environments Research themes: Gamification Games with a Purpose Game Security Game Privacy Game Analytics siamak.shahandashti@york.ac.uk Email Mastodon https://www.cs.york.ac.uk/~siamak Other links Website https://au.linkedin.com/in/siamakfs LinkedIn BlueSky Github Themes Applied Games - Previous Next

< Back Emily Marriott University of Essex iGGi Alum Automated Story Generation for Games Emily is researching automated story generation for video games, focusing on the use of Planning for real-time, dynamic generation. Ideally, the stories created will reflect choices made by the player during gameplay and will update continually throughout gameplay. The aim of this research is to create a system that could be easily utilised in the development of more adaptive games. This could improve player enjoyment, increase re-playability, and allow for the inclusion or exclusion of content that may only appeal to niche audiences. Emily’s current focus is on investigating story structures and pacing to create a template for generating good stories specifically for games that are consistent, well-structured and interesting. This involves studying the pacing requirements in existing games to establish what these are and how they differ the requirements for film and TV. The system will ideally be integrated with existing game-development tools and provide an easy-to-use interface to make the creation of adaptive games easier and quicker. The eventual goal is a full story-generation system would support both the creation of quests that emerge from story requirements and a game world that fits the environment required for the story. Emily graduated from Glyndŵr University with a BSc in Computer Games Development before completing an MSc in Computer Science at Oxford Brookes University. The substance of the MSc dissertation involved generating dungeon levels and quests using grammars based on the play style the player appeared to favour. Emily enjoys playing both tabletop and computer roleplaying games, especially ones in which player actions can have a dramatic effect on the game’s progression. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Themes Player Research - Previous Next

< Back Dr Madeleine Frister University of York iGGi Alum Madeleine joined the IGGI programme in 2020, after obtaining a master’s degree in psychology and cognitive neuroscience from the Friedrich Schiller University in Jena, Germany. Her PhD focuses on how visual characteristics influence gameplay and player experience. In 2021, she co-founded UX studio Vanilla Noir where she works as an independent designer and developer on website, app and game projects. Video games rely heavily on central aspects of human information processing, including perception, attention, and memory. The human mind is severely limited in the amount of information it can process, and a key factor for successful information processing is resisting distraction. Consequently, most user experience guidelines recommend eliminating any unnecessary information to avoid cognitive overload. Yet, in the case of video games, the presence of task-irrelevant items does not seem to compromise player experience, considering that there is an abundance of popular video games that are very high in visual complexity. On the contrary, inducing demand in the form of perceptual distraction may even be desirable in order to introduce challenge which can in turn increase enjoyment. The current project aims to deepen our understanding of perceptual distraction and its effects on game difficulty and player experience, with a specific focus on perceptual similarity between target and distractor items. mf1255@york.ac.uk Email Mastodon https://vanilla-noir.com Other links Website https://www.linkedin.com/in/madeleinefrister LinkedIn BlueSky Github Supervisors Prof. Paul Cairns Dr Laurissa Tokarchuk Dr Fiona McNab Featured Publication(s): Advancing Methodological Approaches in Affect-Adaptive Video Game Design: Empirical Validation of Emotion-Driven Gameplay Modification Perceptual Distraction and its Effects on Difficulty and User Experience in Digital Games An appraisal-based chain-of-emotion architecture for affective language model game agents Examining the effects of video game difficulty adaptation on performance and player experience Examining the influence of perceptual distraction on performance in a working memory game A data-driven approach for examining the demand for relaxation games on Steam during the COVID-19 pandemic Themes Design & Development Player Research - Previous Next

< Back Prof. Alex Wade University of York Supervisor Alex Wade is a psychologist working in the field of human cognitive neuroscience. He uses a combination of structural and functional brain imaging, electrophysiology, psychophysics and big data analysis to ask how we see, solve problems and make decisions. His most recent work in the domain of video games focuses on what we can learn about global cognitive health and player personality from the analysis of large MOBA datasets in collaboration with Riot games (League of Legends). He is particularly interested in supervising students with a psychology or neuroscience background in the areas of: Using commercial video games to measure cognition and personality How the brain responds to solo- and group gameplay Can we use video games to monitor and modify real-world cognition, behaviour and mental health Research themes: Game Analytics Games with a Purpose Computational Creativity E-Sports Player Experience The neuroscience of gaming alex.wade@york.ac.uk Email Mastodon https://www.york.ac.uk/psychology/staff/academicstaff/alex-wade/ Other links Website LinkedIn BlueSky Github Themes Applied Games Creative Computing Esports Game Data Player Research - Previous Next

< Back Prakriti Nayak Queen Mary University of London iGGi PG Researcher Available for placement Prakriti is a neuroscientist passionate about pushing boundaries at the intersection of technology and biological research. Her journey began with a deep dive into neuroscience during her master’s program, where she explored large-scale imaging data and mastered statistical modelling techniques. Afterward, she pursued a career in scientific editing. She views gaming as an excellent platform to connect different fields, such as computational modelling and behaviour. Prakriti plans to develop a model of player uncertainty to enhance the gaming experience by setting difficulty levels that are enjoyable for each player, making games more accessible for people with limited cognitive capabilities. Additionally, her work has diagnostic applications. A description of Prakriti's research: Navigation and spatial memory are essential cognitive processes that enable individuals to orient themselves in complex environments. Amid the inherent uncertainty of environmental noise and cognitive variability, the brain employs sophisticated strategies to make navigational decisions. This project aims to elucidate the cognitive underpinnings of spatial navigation performance by leveraging gaming data to understand how individuals manage spatial uncertainty. The plan is to adapt a Bayesian ideal-observer model based on visual simultaneous localization and mapping. The model will fit and predict the player’s moment-by-moment movement decisions, given the first-person view and the map of the game environment. Fitting the model to the players' gameplay trajectories will yield parameters indicating each individual's levels of visual, motor, and memory noise. The combination of parameters that best differentiate between players will then be examined. This research has the potential to enhance our understanding of spatial navigation and its underlying mechanisms, as well as improve spatial navigation in games, offering an adaptive gaming experience tailored to individual spatial uncertainty levels. p.nayak@qmul.ac.uk Email Mastodon Other links Website http://www.linkedin.com/in/prakritinayak LinkedIn BlueSky https://github.com/PrakritiNayak Github Supervisors: Dr Guifen Chen Dr Yul HR Kang Themes Accessibility Applied Games Player Research - Previous Next

< Back Dr Michael Saiger University of York iGGi Alum Michael is a game design researcher investigating how we engage players (particularly young people) in the design and development of applied games. He has facilitated co-design workshops across health and education research, designing solutions to research problems. Most recently, he was employed as a game design researcher on an ESRC funded project to design and evaluate a game for teacher recruitment. A description of Michael's research: Michael's research involves the facilitation and involvement of children and young people in the design of mental health games. Through their research, they have co-designed mental health prototypes and explored the factors to impact participation and engagement. Their research has highlighted how there are facilitation barriers and shifts in participant preferences towards how young people want to interact during co-design. michael.saiger@york.ac.uk Email https://linktr.ee/MichaelJohnSaiger Mastodon https://micia1592.wixsite.com/mikethingsbetter Other links Website https://www.linkedin.com/in/mjsaiger/ LinkedIn BlueSky Github Supervisors: Dr Joe Cutting Prof. Sebastian Deterding Dr Lina Gega Featured Publication(s): Use of Technology in Brief Interventions How Do We Engage Children and Young People in the Design and Development Of Mental Health Games Children and Young People's Involvement in Designing Applied Games: Scoping Review What Factors Do Players Perceive as Methods of Retention in Battle Royale Games? Themes Applied Games Design & Development Player Research - Previous Next

< Back Dr Kevin Denamganaï University of York iGGi Alum Available for post-PhD position After graduating as an Engineer from the Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA), France, with two double-degree diplomas, a MEng in Electrical Engineering and Information Science from the Osaka Prefecture University (OPU), Japan, and a MRes in Artificial Intelligence and Robotics from the Université de Cergy-Pontoise (UCP), France, Kevin Denamganaï spent a year accumulating experience as a Robotics & Machine Learning freelancer. He is now putting those skills at use in the IGGI PhD program, that, among other things, gives him the opportunity to reunite with video games. Indeed, it was thanks to a keen interest towards video game creation that he started learning programming around 12. His research interests are about everything psychology, neuroscience, AI, (deep) reinforcement/imitation learning, robotics, and natural/artificial language emergence and understanding as well as human-computer interfaces, challenging the question what are the necessary components of artificial agents to be able to converse with human-beings in an engaging manner and to be able to cooperate with them towards a pre-defined goal, e.g. clearing a level in a given video game. kevin.denamganai@york.ac.uk Email Mastodon https://kevindenamganai.netlify.app/ Other links Website LinkedIn BlueSky https://github.com/Near32/ Github Supervisor(s): Dr James Walker Featured Publication(s): ETHER: Aligning Emergent Communication for Hindsight Experience Replay Visual Referential Games Further the Emergence of Disentangled Representations Meta-Referential Games to Learn Compositional Learning Behaviours A comparison of self-play algorithms under a generalized framework On (Emergent) Systematic Generalisation and Compositionality in Visual Referential Games with Straight-Through Gumbel-Softmax Estimator ReferentialGym: A Nomenclature and Framework for Language Emergence & Grounding in (Visual) Referential Games A generalized framework for self-play training Coupled Kuramoto oscillator-based control laws for both formation and obstacle avoidance control of two-wheeled mobile robots Obstacle avoidance control law for two-wheeled mobile robots controlled by oscillators Themes Game AI - 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 BlueSky https://github.com/ahmedcs Github Themes Creative Computing Design & Development Game AI Game Data Player Research - Previous Next