< Back Dr Lorenzo Jamone Queen Mary University of London Supervisor I am a Lecturer in Robotics and Director of the CRISP group (Cognitive Robotics and Intelligent Systems for the People) at the School of Electronic Engineering and Computer Science (EECS) of the Queen Mary University of London (QMUL). The CRISP group is part of ARQ (Advanced Robotics at Queen Mary). Since October 2018, I have been a Turing Fellow at The Alan Turing Institute. I am interested in understanding human (and animal) intelligence, by using computational techniques that include computer simulations and real robots. My research topics include: human creativity and creative problem solving, human perception, human-human non-verbal communication, object affordances, tool use, body schema, eye-hand coordination, dexterous manipulation and object exploration, human-robot interaction and collaboration, tactile and force sensing. I am interested in supervising students with an engineering, computer science or behavioural sciences background on the following topics: Creating computational models of human creativity Creating computational models of decisional agents Email l.jamone@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Creative Computing - Previous Next

< Back Alex Flint University of York iGGi PG Researcher Available for placement Alex has an academic background in Psychology and Human-Computer Interaction. Their Master’s dissertation comparing measures of perceived challenge and demand in video games was published at CHI 2023. Alex has previously worked on the Research Operations team at PlaytestCloud and as a freelance Games User Researcher. They are also a Student Video Games Ambassador for UKIE, and regularly volunteer at conferences such as CHI Play and the GamesUR Summit. When they aren’t at their desk, you can find Alex figure skating, playing roller derby, or DJing 80’s rock. Alex’s research focuses on levelling up the narrative testing practices of indie video game developers. Narrative testing is a specialised games user research (GUR) practice that requires resources and knowledge not easily accessible to indie developers, meaning they are often disadvantaged compared to their larger AAA counterparts. Thus, Alex's work proposes the direct study of indie developers to level the playing field by democratising narrative testing best practices and empowering non-research team members to conduct GUR activities. Alex aims to achieve this goal by: 1) Defining narrative testing best practices. 2) Identifying key challenges indie developers face when evaluating narrative. 3) Co-designing and evaluating narrative testing prototype(s). 4) Assessing methods for disseminating GUR knowledge. The successful completion of this work will impact how indie studios conduct narrative testing, ultimately leading to the creation of better games. Email alex.flint@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Alena Denisova Dr Jon Hook Featured Publication(s): Comparing Measures of perceived challenge and demand in video games: Exploring the conceptual dimensions of CORGIS and VGDS Faking handedness: Individual differences in ability to fake handedness, social cognitions of the handedness of others, and a forensic application using Bayes’ theorem Themes Design & Development Player Research - Previous Next

< Back Dr Phoebe Hesketh University of York iGGi Alum Phoebe's PhD explored how people learn to play games through gameplay, online media, and community interaction. At the University of York, Phoebe worked on her skills as a researcher by exploring multiple methodologies and disciplines. She built upon her quantitative research skills from Bristol with qualitative research during their PhD including grounded theory and thematic analysis. She took courses in user-centred design and evaluation and designing for accessible player experiences (through AbleGamers). She participated in game jams and game development courses for experience and technical design. She also gave a talk at DEVELOP 2021 communicating and sharing her research and expertise in how players learn to play games to help designers with their onboarding for their games. She originally studied Engineering Mathematics at the University of Bristol which focused on systems and mathematical modelling and simulation, the mathematics and implementation of AI and Machine Learning systems, programming in object-oriented programming languages such as C++ and Java, and developed ray tracers in computer graphics courses. She also worked on projects in linguistics, logistics, computer vision, and physics. Once completing her PhD, Phoebe moved into the games industry as an AI programmer for several years before looking to return to games and player research. She has set up her own company, Take A Mo, that focuses on helping developers analyse their systems and internal systems to maximise access for players in usability, onboarding, accessibility, and representation. She is a currently carving her niche in the industry. Email phoebe@takeamo.co.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Prof. Sebastian Deterding Dr Jeremy Gow Featured Publication(s): How Players Learn Team-versus-Team Esports: First Results from A Grounded Theory Study Themes Esports Player Research - 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). They are an active part of the games community taking part in game jams and running their own commercially focused game studio working on the debut title Moth Terra. A description of Sarah's research: Sarah’s work takes a research-through-design approach focused on exploring meaning in games and ecogames. Alongside a portfolio of games, their previous work includes running a workshop on Solarpunk vs Grimdark concepts, presenting the Cute Ecologies talk Moth Magic, and contributing to the development of Treescapes: A NERC-Funded Mobile Game exploring the social, cultural, and emotional values of trees. Their work also explores sustainable design approaches to games and interactive experiences. Email sarah.masters@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Featured Publication(s): 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!: https://www.youtube.com/watch?v=_zKcgFluR24 Fatalis - a witchy gardening game: https://www.youtube.com/watch?v=kR_OMidgk14 Previous Next

< Back Callum Deery University of York iGGi Alum Callum is a researcher and game developer investigating how real-time player experience measurement can be used to drive adaptive games. Aiming to embed player experience questionnaires into games in a way that doesn’t break immersion and presence, his PhD is focussed on leveraging the wide range of existing player experience questionnaires to improve games ability to adapt to players. This will involve exploring the states of immersion and presence: What is necessary to maintain them? What experiences can players reflect on without breaking immersion? How do we embed a questionnaire into an in-development game without disrupting the player experience? Email callum.deery@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr James Walker Dr Anna Bramwell-Dicks Themes Accessibility Design & Development Player Research - Previous Next

< Back Lizzie Vialls University of York iGGi Alum Discrete Models and Algorithms to create a more satisfying and strategic opponents For many 4x and Grand Strategy computer games (e.g. Civilisation, Europa Universalis), the player will be playing against one or more AI opponents. For many games, the AI is not clever enough to stand up to a player without being given the ability to "cheat" - ability to spawn in resources, see what the player is doing, etc. This creates an unsatisfactory opponent for a player, as it gives them opponents that fight through "cheating" over strategy or out-manoeuvring the player. The aim for my PhD is to look into the potential uses of SAT and similar to create a more satisfying and strategic opponent for players to play against in these styles of computer games. To this end, I’ll be identifying potential for improvement regarding my proposal, and once I’ve narrowed down the specifics - be it related to improving how SAT solvers can handle problems, or how better to encode AI into SAT - I will be working on ways to improve AI for turn based strategic games. Lizzie Vialls is a recent Computer Science graduate of University of Leicester, having graduated with a 2:1 and a prize for best third year project, which was the project that fueled her interest in SAT. When not searching for an errant semicolon in her code she can be found working with various online gaming communities, hunched over many a tabletop game, or attempting to make friends with the local feline populace. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

< Back Dan Cooke University of York iGGi PG Researcher Available for post-PhD position I have a keen interest in the world of finance and regulation and controls for prevention of crime in video games and wider financial marketplaces. I am interested in how criminals seek to exploit systems to transfer and disguise proceeds of crime or for the use of further crime. I have a background in accounting and finance and graduated with a MA in Applied Accounting from De Montfort University in 2019. Outside of my professional interests I play MMO's daily and am involved in the community for Old School Runescape and Runescape. My research interests include money laundering, secondary marketplaces in video games and user experience. A description of Dan’s research: The focus of my research is on detecting money laundering in video games using outlier detection methods to assess the risk of outliers relative to the data population. I aim to have identified money laundering risk and scale within the steam marketplace data i am working with and identify whether certain games or items have higher risk of being exploited for the purpose of money laundering purposes. My current research is looking at using anomaly scores (how severe of an outlier a data point is) to assess the risk of laundering within certain groups using a multi level grouping analysis. This aims to assess different risk levels per item and game and challenge the assumption that the whole marketplace behaves the same and identify risk variance between groups. Email dan.cooke@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr David Zendle Featured Publication(s): Money laundering through video games, a criminals' playground Themes Esports Game Data Player Research - Previous Next

< Back Dr Miles Hansard Queen Mary University of London Supervisor Miles Hansard is a computer vision researcher, working on geometric and statistical methods for 3D scene understanding and rendering. He is also interested in active 3D sensing technologies, including depth cameras, lidar, and millimetre-wave radar. His recent projects include GPU methods for real-time atmospheric effects, commodity radar localization of UAVs, and grasp planning for robotic manipulation. He has also worked on human perceptual processes, including eye-movements, geometric judgements, and binocular stereopsis. Miles Hansard is a Senior Lecturer in computer graphics, and a member of the Vision Group and Centre for Advanced Robotics, at QMUL. He is available to supervise projects in the following areas: Simulation of complex physical effects (e.g. the motion of cloth, fire, and fluids), using machine learning. Physically plausible character animation in complex environments (e.g. slippery terrain), using machine learning. Email miles.hansard@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Game AI Game Data Immersive Technology - 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. Email kevin.denamganai@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr James Walker Featured Publication(s): CueTip: An Interactive and Explainable Physics-aware Pool Assistant EReLELA: Exploration in Reinforcement Learning via Emergent Language Abstractions Language Model Inversion through End-to-End Differentiation xInv: Explainable Optimization of Inverse Problems 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 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. Email mf1255@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link 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. Damian Murphy University of York Supervisor Damian Murphy is Professor in Sound and Music Computing at the Department of Electronic Engineering AudioLab, University of York, where he has been a member of academic staff since 2000, and is the University Research Theme Champion for Creativity. He started his career in the Performing Arts Department at Harrogate College and has previously held positions at Leeds Metropolitan University and Bretton Hall College. His research focuses on virtual acoustics and he has published over 130 journal articles, conference papers and books in the area. He is a member of the Audio Engineering Society, a Fellow of the Higher Education Academy, and a visiting lecturer to the Department of Speech, Music and Hearing at KTH, Stockholm. Prof. Murphy is also an active sound artist and the Director of the £15m XRStories Creative Industries R&D Partnership exploring interactive and immersive storytelling for the UK’s creative and cultural sectors. He is interested in supervising students with interests in sound design, acoustics and audio signal processing and with a particular focus on: Interactive and immersive audio environments for real-time systems Room acoustics simulation and auralisation Assessment of immersive audio content for gameplay and competitive advantage Interactive/immersive audio storytelling Acoustic scene classification using spatial and spectral feature Audio for immersive environments. Research themes: Game AI Game Audio and Music Games with a Purpose Player Experience Email damian.murphy@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game Audio Immersive Technology - Previous Next

< Back Matt Bedder University of York iGGi Alum Abstraction-Based Monte Carlo Tree Search. (Industry placement at PROWLER.io) Monte Carlo Tree Search is a popular artificial intelligence technique amongst researchers due to the remarkable strength by which it can play many games. This technique was prominently used as the basis for AlphaGo, the AI by Google DeepMind that became the first of its kind to beat professional human players at the game Go. But despite lots of interest from academics into Monte Carlo Tree Search, the technique has seen little use in the games industry - due in part to how it is not fully understood, and due to how complex it is to implement into large games. Matthew’s research is looking into how game abstractions can be used to help implement and optimise Monte Carlo Tree Search into existing commercial video games. Semi-automated methods for domain abstraction are being investigated, with the aim of making it fast and easy for game developers to be able to implement Monte Carlo Tree Search into their products, and to exploit the wealth of academic research into this technique. Matthew is currently studying towards his PhD at the University of York, having previously graduated for the Department of Computer Science with a MEng in Computer Science with Artificial Intelligence. Before starting his PhD, Matthew spent a year at BAE Systems Advanced Technology Centre working on contracts with the European Space Agency, and has performed research into vertebrae models of Parkinson's disease with York Centre for Complex Systems Analysis. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Characterization and classification of adherent cells in monolayer culture using automated tracking and evolutionary algorithms Computational approaches for understanding the diagnosis and treatment of Parkinson's disease Automated motion analysis of adherent cells in monolayer culture Themes Game AI - Previous Next