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< Back Dr Diego Pérez-Liébana Queen Mary University of London iGGi Industry Liaison Supervisor Born in Madrid (Spain) and living in London (United Kingdom), I am a Senior Lecturer in Computer Games and Artificial Intelligence at Queen Mary University of London. I hold a PhD in Computer Science from the University of Essex (2015) and a Master degree in Computer Science from University Carlos III (Madrid, Spain; 2007). My research is centered in the application of Artificial Intelligence to games, Tree Search and Evolutionary Computation. At the moment, I am especially interested on General Video Game Playing and Strategy games, which involves the creation of content and agents that play any real-time game that is given to it, and research in Abstract Forward Models. I have recently been awarded with an EPSRC grant on Abstract Forward Models for Modern Games. I am author of more than 100 papers in the field of Game AI, published in the main conferences of the field of Computational Intelligence in Games and Evolutionary Computation. I have publications in highly respected journals such as IEEE TOG and TEVC. I have also organised international competitions for the Game AI research community, such as the Physical Travelling Salesman Competition, and the General Video Game AI Competition, held in IEEE (WCCI, CIG) and ACM (GECCO) International Conferences. I also experience in the videogames industry as a game programmer (Revistronic; Madrid, Spain), with titles published for both PC and consoles. I worked as a software engineer (Game Brains; Dublin, Ireland), where I oversaw the development of AI tools that can be applied to the latest industry videogames. I am particularly interested in supervising students with background on applications of Tree Search or Evolutionary Algorithms for strategy games. Research Themes: Game AI Rolling Horizon Evolutionary Algorithms. Monte Carlo Tree Search Statistical Forward Planning methods. Strategy Games. diego.perez@qmul.ac.uk Email Mastodon https://diego-perez.net Other links Website https://www.linkedin.com/in/diegoperezliebana/ LinkedIn BlueSky https://github.com/diegopliebana Github Themes Game AI Game Data - Previous Next

< Back Dominik Jeurissen Queen Mary University of London iGGi PG Researcher Hey, I'm Dominik Jeurissen, and I'm passionate about both software engineering and machine learning, with a particular interest in fully autonomous agents that do not rely on absurd amounts of data. My focus areas include reinforcement learning, unsupervised learning, and the emerging capabilities of large language models. I earned my MSc in Artificial Intelligence from Maastricht University and my BSc in Computer Science with a focus on Applied Mathematics from RWTH Aachen. During my undergraduate studies, I worked as a software engineer at INFORM GmbH, contributing to their supply management software, add*ONE. A description of Dominik's research: My PhD is a collaboration with Creative Assembly , focusing on researching AI for complex strategy games, such as Total War. With the recent emergence of Large Language Models (LLMs), I’m exploring their potential to enhance game-playing agents. LLMs can instantly recall knowledge on almost any topic (though not without occasional errors), perform basic reasoning, and are easily configured for a wide range of text-based tasks. These abilities make them especially promising for game development, where machine learning agents often struggle due to constantly changing game environments. d.jeurissen@qmul.ac.uk Email https://commandercero.github.io/ Mastodon Other links Website https://www.linkedin.com/in/dominik-jeurissen/ LinkedIn https://bsky.app/profile/dominikjeurissen.bsky.social BlueSky https://github.com/CommanderCero Github Supervisors: Dr Diego Pérez-Liébana Dr Jeremy Gow Featured Publication(s): Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Generating Diverse and Competitive Play-Styles for Strategy Games PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games Automatic Goal Discovery in Subgoal Monte Carlo Tree Search Game state and action abstracting monte carlo tree search for general strategy game-playing Portfolio search and optimization for general strategy game-playing The Design Of" Stratega": A General Strategy Games Framework Themes Design & Development Game AI Game Data - Previous Next

< Back Dr Jon Hook University of York Supervisor Jon Hook is a Senior Lecturer (equivalent to an Associate Professor) in Interactive Media in the Department of Theatre, Film, Television and Interactive Media at the University of York. His research is situated in the field of Human-Computer Interaction (HCI) and explores the design and development of new interactive media content forms and tools to support their creation. This research combines his deep interest in new forms of interactive technology and media with empirical, theoretical and methodological perspectives, in the human-centred design of novel interfaces and interaction techniques for a broad range of artistic and everyday creative practices. His current research is focused on the design and development of new forms of responsive and immersive media content, with a particular interest in data-driven storytelling. He was recently the principal investigator of the EPSRC funded Perspective Media: Personalised Video Storytelling for Data Engagement project. He also a co-investigator of the InnovateUK WEAVR: Pioneering Fully Integrated Cross-Reality Spectator Experiences in Esports and Beyond immersive experiences demonstrator and the Digital Creativity Labs – a £4m EPSRC, AHRC and InnovateUK funded research centre exploring impact-driven research in the creative industries. He was also previously Co-I of the AHRC Within the walls of York Gaol: Memory, Place and the Immersive Museum the AHRC Digital Creativity for Regional Museums: Immersive Experiences Smart Commissioning Toolkit. He is especially interested in supervising students who’d like to do HCI research that involves making and evaluating new interactive media experiences. Some example topic areas that he might be the right supervisor for include, but aren’t limited to: Games to support broader data engagement and literacy Data-driven storytelling in, and about, games The intersection between games and interactive documentary film Responsive and interactive video storytelling in games The space where theatre and games converge Cultural heritage engagement using games Research themes: Game Design Games with a Purpose E-Sports Player Experience jonathan.hook@york.ac.uk Email Mastodon https://www.jonhook.co.uk Other links Website https://www.linkedin.com/in/jonathan-hook-641b597/ LinkedIn BlueSky https://github.com/jonathanhook Github Themes Applied Games Esports Player Research - 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. adrian.barahona.rios@gmail.com Email Mastodon https://www.adrianbarahonarios.com/ Other links Website https://www.linkedin.com/in/adrianbarahona LinkedIn BlueSky https://github.com/adrianbarahona Github Supervisor Dr Tom Collins Featured Publication(s): 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

Partners (All) iGGi is a collaboration between Uni of York + Queen Mary Uni of London: the largest training programme worldwide for doing a PhD in digital games. iGGi Partners We are excited to be collaborating with a number of industry partners. iGGi works with industry in some of the following ways: Researcher Industry Knowledge Exchange - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the researcher and their industry partner. Researcher Sponsorship - for some of our researchers, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - iGGi industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! Check out our Industry Info page here to see these types of collaboration described in more detail. There are many ways for our industry partners to work with iGGi. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. 22 Cans AI and Games Autistica BT BetaJester Limited BiG BlitzGame Studios Bossa Studios British Broadcasting Corporation BBC British Games Institute (BGI) CBT Clinics COMIC Research Carnegie Mellon University Cooperative Innovations Creative AI Creative Assembly Die Gute Fabrik Digital Catapult Dubit Limited Durham University ESL UK Electronic Arts (EA) Enigmatic Studios Falmouth University Fluttermind LLC

< Back Prof. Anders Drachen Supervisor Anders Drachen, PhD, (born 1976) is a Professor at the Department of Computer Science, with Digital Creativity Labs and Weavr at the University of York (UK). His work in games research is focused on user behavior, user experience and audience engagement and the application of data science, information systems modelling, business intelligence, design and Human-Computer Interaction in these domains. His research and professional work are carried out in collaboration with companies across the Creative Industries, from big publishers to indies. He is recognized as one of the most influential people in his domains of work and have authored over a hundred publications with international colleagues across industry and academia. Having lived and worked on four different continents, Anders Drachen has had the mixed pleasure of fending off three shark attacks in Africa and Australia. He is also the youngest Dane in history to publish a cooking book – dedicated to ice cream. Research themes: Data Science, Analytics, Machine Learning in Interactive Media Big Data, behavior- and social media analytics in the Creative Industries Data Mining and Business Informatics in the Creative Industries Data-Driven Storytelling and Audience Engagement Games User Research and User Experience in Games Data-Driven Design and Development Human-Computer Interaction Esports and Sports Analytics Behavioral/Market Analytics and Business Intelligence Entrepreneurship in the Creative Industries Blockchain and Cryptocurrencies anders.drachen@york.ac.uk Email Mastodon https://www.andersdrachen.com Other links Website https://www.linkedin.com/in/drachen/ LinkedIn BlueSky Github Themes Design & Development Esports Game Data Player Research - Previous Next

< Back David Hull University of York iGGi Manager iGGi Admin I have worked at the University of York since October 1995, almost all of it in the Department of Computer Science. My various roles have included Laboratory and Facilities Manager, Technical Manager and, most recently, Project Manager. Outside work, I have been a change-ringer for almost 50 years, and am currently a member of the band that rings the bells weekly at York Minster. I am also an accredited teacher of bellringing. I do parkrun most weeks, alongside the occasional 10k and half marathon, like to watch cricket, and play the clarinet and piano. iggi-admin@york.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes - 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. miles.hansard@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/~milesh/ Other links Website LinkedIn BlueSky Github Themes Design & Development Game AI Game Data Immersive Technology - Previous Next

< Back Dr Ivan Bravi Queen Mary University of London iGGi Alum Ivan Bravi has obtained his B.Sc and M.Sc in Engineering of Computer Systems at the Politecnico di Milano, Italy. From January to July 2016 he was Visiting Scholar at the NYU’s Game Innovation Lab in New York, under the supervision of Prof. Julian Togelius. Since October 2017 he's an IGGI PhD student at Queen Mary University of London under the supervision of Simon Lucas. Ivan has published several workshop and conference papers in different venues such as IJCAI, Evostar, CIG, FDG, AAAI and CoG. Automatic playtesting of games can significantly streamline the process of designing, developing and releasing a game. It is also a possible application of Artificial General Intelligence (AGI): having a set of flexible algorithms that can play games regardless of their type decouples the two problems (playtesting and developing AGI algorithms) advancing both independently. When it comes to developing new AGI algorithms for game-playing a crucial characteristic is the ability of expressing different behaviours. Most of the research has focused on peak performance game-playing agents, this research project instead focuses on producing agents that are able to show different playing styles (behaviours) with no explicit domain information embedded in the algorithm. Behavioural expressivity arises from the parameterisable components of an algorithm. In classical Statistical Forward Planning (SFP) it is very straightforward to adjust these, e.g. how far ahead it's planning. A very important component of SFP algorithms is the heuristic function used to evaluate the quality of game states. Being able to define heuristics in a game-agnostic manner is a key element in maintaining the algorithms generally. i.bravi@qmul.ac.uk Email Mastodon Other links Website LinkedIn BlueSky https://github.com/ivanbravi Github Supervisor(s): Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): Evaluating and Enhancing Gameplay Behavioural Expressivity of Planning-Playing Artificial Intelligence for Automatic Playtesting Self-adaptive MCTS for General Video Game Playing Rinascimento: Playing Splendor-Like Games With Event-Value Functions Rinascimento: searching the behaviour space of Splendor Rinascimento: using event-value functions for playing Splendor Learning local forward models on unforgiving games Rinascimento: Optimising statistical forward planning agents for playing splendor A local approach to forward model learning: Results on the game of life game Game AI hyperparameter tuning in rinascimento Efficient evolutionary methods for game agent optimisation: Model-based is best Shallow decision-making analysis in general video game playing Evolving UCT alternatives for general video game playing Evolving game-specific UCB alternatives for general video game playing Themes Game AI 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. phoebe@takeamo.co.uk Email Mastodon http://www.takeamo.co.uk Other links Website https://www.linkedin.com/in/phoebe-hesketh/ LinkedIn BlueSky Github 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 Dr Ignacio Castro Queen Mary University of London Supervisor Ignacio Castro is Lecturer in Data Analytics at Queen Mary University of London. His work sits at the intersection between economics and networks. His interest spans from online social networks and moderation to the macroscopic evolution of the Internet. He has been an investigator on three major grants that hold over £6 million in funding. His work appears in top tier journals and conferences including Web Conference, ACM SIGCOMM, ACM SIGMETRICS, ACM IMC, ICWSM, and IEEE/ACM Trans. on Networking. He is interested in supervising students with a background in social network analysis, NLP and/or machine learning. i.castro@qmul.ac.uk Email https://mastodon.social/@ignactro Mastodon https://icastro.info/ Other links Website https://www.linkedin.com/in/ignacio-de-castro-arribas-44a48117/ LinkedIn BlueSky Github Themes Applied Games Game AI Game Data Player Research - Previous Next

< Back Dr Piers Williams University of Essex iGGi Alum Partial Observability as a game mechanic There is a wide variety of different types of games, each providing its own unique challenge to artificial intelligence. Not all games provide full access to the environment, creating interest and difficulty by hiding particular pieces of information from the player. Other types of game expect teamwork from the players rather than being solely adversarial. Some games use both restrictions, and it is this type of game that this thesis concentrates on. Piers graduated from the University of Essex with an MSc in Computer Science. His interests lie in the field of Artificial Intelligence and in particular Multi-Agent Systems. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Hexboard: A generic game framework for turn-based strategy games Evaluating and Modelling Hanabi-Playing Agents Monte carlo tree search applied to co-operative problems The 2018 hanabi competition Artificial intelligence in co-operative games with partial observability Ms. Pac-Man Versus Ghost Team CIG 2016 Competition Cooperative games with partial observability Themes Game AI - Previous Next