< Back Dr Abi Evans University of York Supervisor Abi Evans is a Lecturer in Interactive Media in the Department of Theatre, Film, Television, and Interactive Media at the University of York. Her research is at the intersection of Human-Computer Interaction (HCI) and Learning Sciences, exploring how technology can provide real-time adaptive scaffolding for the skills and processes associated with effective learning in a variety of settings. Abi is particularly interested in supervising students who want to create and evaluate games and immersive experiences for learning or develop approaches for measuring learning in games. Her current project focuses on developing experiences for people who are learning to code, specifically tackling barriers to learning such as imposter syndrome and misconceptions about coding concepts. Abi would also welcome students interested in games for learning in other disciplines and in informal settings as well as traditional academic disciplines. Email abi.evans@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Immersive Technology Player Research - Previous Next

< Back Dr James Goodman Queen Mary University of London iGGi Outreach Coordinator iGGi Alum James has picked up degrees in Chemistry, History, Mathematics, Business Administration and Machine Learning. After a career in Consultancy and IT Project Management he is now finally doing the research he always wanted to. James is interested in opponent modelling, theory of mind and strategic communication in multi-player games, and how statistical forward planning can be used in modern tabletop board-games (or other turn-based environments). With a constrained budget, how much time should an agent spend thinking about it's own plan versus thinking about what other players might be doing to get in the way. How does this balance vary across different games? His secondary research interests are in using AI-playtesting as a tool for game-balancing and game-design. Email james.goodman@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): Dice, Cards, Action! The Analysis, Play and Design of MultiplayerTabletop Board Games with Monte Carlo Tree Search From code to play: Benchmarking program search for games using large language models LLM-based Program Search for Games Seeding for Success: Skill and Stochasticity in Tabletop Games From Code to Play: Benchmarking Program Search for Games Using Large Language Models Skill Depth in Tabletop Board Games Measuring Randomness in Tabletop Games A case study in AI-assisted board game design Following the leader in multiplayer tabletop games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games MultiTree MCTS in Tabletop Games Visualizing Multiplayer Game Spaces TAG: Terraforming Mars Fingerprinting tabletop games AI and Wargaming Metagame Autobalancing for Competitive Multiplayer Games Does it matter how well I know what you’re thinking? Opponent Modelling in an RTS game Weighting NTBEA for game AI optimisation Re-determinizing MCTS in Hanabi Noise reduction and targeted exploration in imitation learning for abstract meaning representation parsing UCL+ Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound Themes Design & Development Game AI - 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 Nuria Peña Pérez Queen Mary University of London iGGi Alum Nuria got her bachelor’s in biomedical engineering in Spain before moving to London. After studying an MSc in Neurotechnology and working in robotic neurorehabilitation at Imperial College London, she discovered the enormous potential of serious games in the field of human-robot interaction. She joined IGGI in 2018. Her PhD research involves studying human motor control and learning during bimanual tasks to investigate how the dynamics of the interaction can serve to develop better training systems. This is done through the development of interactive gaming environments that are compatible with rehabilitation robotic devices. The modelling of the recorded human neuromuscular data allows to explore how to better help patients to restore their motor function. Her work is a collaboration between the Advanced Robotics group at Queen Mary University of London and the Human Robotics group at Imperial College London. As part of her PhD she has worked for the company GripAble, developing games for the assessment and training of hand function (February 2020-August-2020). Email n.penaperez@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr Ildar Farkhatdinov Featured Publication(s): Redundancy Resolution in Trimanual vs. Bimanual Tracking Tasks Dissociating haptic feedback from physical assistance does not improve motor performance Bimanual interaction in virtually and mechanically coupled tasks The impact of stiffness in bimanual versus dyadic interactions requiring force exchange How virtual and mechanical coupling impact bimanual tracking Lateralization of impedance control in dynamic versus static bimanual tasks Is a robot needed to modify human effort in bimanual tracking? Exploring user motor behaviour in bimanual interactive video games Quartz Crystal Resonator for Real-Time Characterization of Nanoscale Phenomena Relevant for Biomedical Applications Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Themes Applied Games - Previous Next

< Back Pilar Zhang Qiu Queen Mary University of London iGGi Alum Pilar is a researcher with a background in Design Engineering. She has a keen interest in user experience and interaction, wearables and the use of cyber-physical systems in the medical field. Her PhD centres around the creation of play assessments for neuromotor conditions in children with cerebral palsy. This gravitates around the idea that better and more objective clinical data can be obtained through gamification of common assessments. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games - Previous Next

< Back Francesca Foffano University of York iGGi PG Researcher Available for post-PhD position Francesca is finalising her PhD at the University of York, specialising in UX, player experience and design. Their work spans game experience (e.g. getting stuck), safeguarding the design's impact on players (e.g. emotional accessibility), design recommendations (e.g. emotional design) and game development (e.g. adaptive games). They primarily use qualitative research and mixed methods to gain an in-depth understanding of the player experience. They are currently open to collaborations with industry and academia for funding applications. A description of Francesca's research: When it comes to emotions in video games, players should feel like they are enthusiastically part of the experience. However, at times, players risk feeling forced or overwhelmed. So, how to design these experiences correctly? Through a dual approach, I explore how to design emotional experiences at their extremes. On the one hand, I examine which design components create recognisable emotional experiences. On the other hand, I examine how design can overwhelm players to the point where they struggle to finish a game, as the design makes it impossible for them to process the emotions presented. Email ff716@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Featured Publication(s): Artificial intelligence across europe: A study on awareness, attitude and trust Disability tax in gacha games: the social cost of hidden expenses. Do Not Play With My Emotions. Design for Emotional Accessibility A Survey on AI and Ethics: Key factors in building AI trust and awareness across European citizens. When Games Become Inaccessible: A Constructive Grounded Theory on Stuckness in Videogames Artificial intelligence across europe: A study on awareness, attitude and trust Investing in AI for social good: an analysis of European national strategies European Strategy on AI: Are we truly fostering social good? Changes of user experience in an adaptive game: a study of an AI manager Themes Player Research - https://www.youtube.com/watch?v=v8xdnkjVL2c Previous Next

< Back Dr Ildar Farkhatdinov Queen Mary University of London Supervisor Dr Ildar Farkhatdinov is a Lecturer in Robotics at QMUL since 11/2016 and a Turing Institute Fellow. He is an internationally leading expert in assistive robotics and human-machine interaction. He is a principle investigator of several projects on wearable robotics, mobility assistance and haptic interfaces (including funding from the UK government on supernumerary robotic limbs and assistive wheelchairs, £500k+). Several of his research works were recognised as the best paper or finalists for best paper awards at leading robotics conferences. Before joining QMUL, he was a postdoctoral research associate at the Human Robotics group of the Department of Bioengineering, Imperial College London (2013-16). He earned Ph.D. in Robotics in 2013 (Sorbonne University, UPMC, France), M.Sc. in Mechanical Engineering in 2008 (KoreaTech, South Korea) and B.Sc. in Automation and Control in 2006 (Moscow University, Russia). He has actively collaborated on a number of large-scale research projects: EPSRC NCNR to create novel robotic solutions for the nuclear industry; EU FP7 BALANCE to develop balance and robotic walking assistance for the elderly; EU FP7 SYMBITRON to develop exoskeleton control for people with spinal cord injury. My research interest relevant to CDT IGGI include serious games for medical applications, as well as using game theory to investigate human-machine interaction. Research themes: Game Design Serious games Virtual reality Game theory Email i.farkhatdinov@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Game AI Immersive Technology Player Research - Previous Next

< Back Prof. Simon Lucas Queen Mary University of London iGGi Co-Investigator Supervisor Simon Lucas is a professor of Artificial Intelligence and Head of the School of Electronic Engineering and Computer Science at Queen Mary University of London where he also heads the Game AI Research Group. He holds a PhD degree (1991) in Electronics and Computer Science from the University of Southampton. He is the founding Editor-in-Chief of the IEEE Transactions on Games and co-founded the IEEE Conference on Games. His research involves developing and applying computational intelligence techniques to build better game AI, use AI to design better games, provide deep insights into the nature of intelligence and work towards Artificial General Intelligence. He is the QMUL lead for the EPSRC-funded CDT in Intelligent Games and Game Intelligence (IGGI). He has supervised more that 15 PhD students to completion, most of them in Game AI. Research themes: Game AI Agents (RL, Monte Carlo Tree Search, Rolling Horizon Evolution) Learning Forward Models Automated Game Design, Procedural Content Generation Game AI for real-world problem solving Email simon.lucas@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

< Back Younès Rabii Queen Mary University of London iGGi PG Researcher Available for post-PhD position Younès is an awarded game designer and generative AI researcher. Their current research is concerned with the relationship between a game's rules, its narrative, and how to build AI systems that can understand these relationships, manipulate them, and invent new ones. Younès also has been a game developer for the past 10 years. They specialize in crafting new forms of play and making it accessible for their peers. Their work has been previously exposed in the French embassies and international conferences like the Game Developers Conference, the Gamedevs of Color Expo and the A MAZE Festival. A description of Younès' research: Younès' research goal is to bring to video games some of the most interesting properties of roleplaying games: their ability to trust every player with building a part of the game, and their ability to generate both new narrative and gameplay on the fly. Younès is working both on the AI techniques needed to allow that, and how to design the social spaces around those games in a way that won't hurt players or abuse creators. For the end of their PhD, Younès is designing a prototype in that new genre, counting among the first games to contain a form of Live Automated Game Design. Email yrabii.eggs@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor(s): Dr Mike Cook Dr Jeremy Gow Featured Publication(s): "Hunt Takes Hare": Theming Games Through Game-Word Vector Translation " Hunt Takes Hare": Theming Games Through Game-Word Vector Translation Why Oatmeal is Cheap: Kolmogorov Complexity and Procedural Generation Revealing game dynamics via word embeddings of gameplay data Themes Creative Computing Design & Development Game AI - Previous Next

< Back Dr Adrián Barahona-Ríos University of York iGGi Alum From 2018 and in collaboration with Sony Interactive Entertainment Europe, Adrián is researching strategies to increase the efficiency in the creation of procedural audio models for video games by using DSP and machine learning approaches. His main research interests, applied to the synthesis of sound effects, are generative deep learning (GANs, RNNs and VAEs) to synthesise raw audio and machine learning to find out the best parameters for a synthesiser to generate a target sound. Adrián has been enthusiastic about sound and more specifically about game audio since he began his studies. By the time he completed an HND in Creative Media Production in Madrid, he started working in the industry as a recording engineer in an ADR studio for the Spanish localisation of video games (such as Fallout 4, Until Dawn or Just Cause 3). He moved from Spain to the UK in 2015 to take a BA (top-up) in Music Production at the Southampton Solent University and an MSc in Sound Design at the University of Edinburgh immediately after. During that journey, he focused his career in procedural audio and explored ways to create models for interactive applications by using different techniques. Email adrian.barahona.rios@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor Dr Tom Collins Featured Publication(s): RESP: Reference-guided Sequential Prompting for Visual Glitch Detection in Video Games Deep Learning for the Synthesis of Sound Effects NoiseBandNet: controllable time-varying neural synthesis of sound effects using filterbanks Sonifying energy consumption using SpecSinGAN SpecSinGAN: Sound Effect Variation Synthesis Using Single-Image GANs Synthesising Knocking Sound Effects Using Conditional WaveGAN Perception of emotions in knocking sounds: An evaluation study Perceptual Evaluation of Modal Synthesis for Impact-Based Sounds Illuminating Game Space Using MAP-Elites for Assisting Video Game Design Themes Creative Computing Game Audio - Previous Next

< Back Igor Dall'Avanzi Goldsmiths iGGi Alum Creation of accessible tools for the use of procedural audio in video games The aim of this research is to investigate and provide new tools to developers for the use of procedural audio into video games. Procedural approaches could address different issues that commonly afflict game audio. In music, generative systems are not only less repetitive, but offer more adaptability as well. For what concerns sound design, they can provide not only variety, but stronger and more realistic support to the interaction with the game world; interaction that is becoming even deeper with the advent of VR Yet, these methods still need improvement on different sides. One is the level of quality that procedural audio needs to achieve to compete with the current aesthetic established by the use of rendered sounds and music in the media. Another is the additional amount of work required by the CPU to render the assets on runtime, and its variable cost). Finally, there is a general lack of user-friendly tools, to link common programming languages for audio to game engines. Software like MaxMsp, Pure Data or SuperCollider is used to design generative audio systems. A more accessible integration of these software could promote generative approaches among sound designers and composers in the field, that today have instead access to tools mainly designed to be used with rendered assets. My plan is to bring on research first by focusing on how a higher degree of quality could be addressed, exploring tools like the above mentioned MaxMsp, Pure Data, low level solutions, and machine learning algorithms. Primary research will be run to confront procedurally generated audio content with rendered one; to understand its impact on the player, and the level of quality needed to deliver a satisfactory experience. The creation of more accessible interfaces and tools dedicated to implement procedural audio in video games will be investigated and undertaken. I like to make noises of all sort and to play with them. For this reason I graduated in Music Production in 2016 and, at the moment of writing, I am finishing my final project for an MSc in Sound and Music for Interactive Games at Leeds Beckett University. Composer and sound designer, in the last year I have been focusing on audio implementation and programming, and I am currently exploring machine learning approaches for procedural audio. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game Audio Player Research - Previous Next