< Back Dr Cristina Guerrero-Romero Queen Mary University of London iGGi Alum Cris is a versatile Software Engineer with four years of experience in web development across different areas of the tech stack. She studied Software and Computer Engineering at Universidad Autónoma de Madrid (Spain) and is currently completing her PhD at Queen Mary University of London (QMUL); during which she has done two internships at Google. Her research ‘Beyond Playing to Win: Broadening the Study and Use of Gameplaying Agents when Provided with Distinct Behaviours’ is focused on expanding the research on game-playing agents beyond the objective of winning at them. She looks at 1) broadening the scope by diversifying agents goals and heuristics; 2) broadening the vision by proposing a team of agents to assist game development; 3) broadening the usage by eliciting diverse automated gameplay, and 4) broadening the horizon by analysing the strengths of the agents from a Player Experience perspective instead of their performance. Cris is passionate about solving problems and learning. Outside of her work, she enjoys playing video games and TTRPGs. Random facts are that Portal and TLOU are two of her favourite game series and her chosen superpower would be teleportation. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Beyond Playing to Win: Elicit General Gameplaying Agents with Distinct Behaviours to Assist Game Development and Testing Beyond Playing to Win: Creating a Team of Agents with Distinct Behaviours for Automated Gameplay MAP-Elites to Generate a Team of Agents that Elicits Diverse Automated Gameplay Generating Diverse and Competitive Play-Styles for Strategy Games Studying General Agents in Video Games from the Perspective of Player Experience Ensemble Decision Systems for General Video Game Playing Using a Team of General AI Algorithms to Assist Game Design and Testing Beyond playing to win: Diversifying heuristics for GVGAI Themes Design & Development Game AI - Previous Next

< Back Prof. Richard Bartle University of Essex iGGi Co-Investigator Supervisor Richard Bartle is a renowned pioneer in game design and research. He co-wrote the first virtual world, MUD ("Multi-User Dungeon") in 1978, and has thus been at the forefront of the online games industry from its very inception. He is an influential writer on all aspects of virtual world design, development, and management. As an independent consultant, he has worked with many of the major online game companies in the U.K. and the U.S. over the past 30 years. His 2003 book, Designing Virtual Worlds , has established itself as a foundation text for researchers and developers of virtual worlds alike. His Player Type theory is taught in game design programmes worldwide (he appears in examination questions!). His interests are directed mainly virtual worlds, particularly Massively Multiplayer Online Role-Playing Games (MMORPGs, or MMOs), but cover all aspects of game design. He is keen to see AI used for non-player characters in MMOs (his PhD is in AI), and his current work considers the long-term moral and ethical implications of this. They’re maybe not what you might think they were at first glance… Email rabartle@essex.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Design & Development Game AI Player Research - 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 Stefan Stoican University of Essex iGGi Alum Understanding human crowd behaviour via virtual environments: feedback loop between games & research This project uses computer game experiments to explore decision-making in a virtual evacuation simulation. Can one be “saved by the gaze”? Currently, Stefan is investigating how innate social cognition components such as gaze-cuing might inform one’s egress. Do “Us versus Them” scenarios occur? He is also testing how one’s feelings of social identification with the surrounding crowd might modulate one’s risk-taking. Does hoarding prevent herding? Lastly, the project is looking at how cultural differences might affect egress time, when one insists to save personal possessions. More broadly, Stefan’s research concentrates on two key open questions in human crowd behavioural research. Firstly, how do social groups (that the player observes or is a member of) within the simulated crowd of agents affect both individual decision-making and the emergent behaviour of the crowd? Secondly, both empirical and virtual experiments of human crowds have not fully explored the effect of agent or player interactions with underlying landscape features (e.g. layout, signage, debris, large objects and other obstacles, etc). The outcomes of the experimental studies using real human participants will subsequently be used to develop more realistic decision-making and behavioural response algorithms and hence improve the behaviour of simulated agents in follow-on computer games. Stefan’s academic background may lie in Mathematics and Psychology, but his interdisciplinary mindset has constantly pushed him towards games and Computer Science. For his final Mathematics project, he designed an Android app that gamified teaching statistics. As part of his Psychology Masters degree, he investigated the potential benefits of MOBA games such as League of Legends with regard to visual attention. Currently, his extracurricular projects aim to explore video games’ effects on coping with trauma and on one’s perception of vulnerable groups, via commemorative gaming name choices or via in-game refugee storylines, respectively. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Game AI - Previous Next

< Back Prof. Peter Cowling Queen Mary University of London iGGi Director Supervisor Peter Cowling has led teams that have won £45 million for research into games and digital creativity. After decades of experience in novel models and algorithms for AI decision-making, his research is now targeted on finding and promoting promising research directions in AI, games and digital creative technology, to benefit people and wider society. Playful ideas, curiosity and games have a central role! As Principal Investigator, he led the teams which won the grants for IGGI (2014 and 2019) and Digital Creativity Labs (2015). He is a member of the Programme Advisory Board which informs strategy in the Digital Economy area of UK research council funding. He has sat on several research council grant funding prioritisation panels, chairing two. He has presented ideas for the use of games as a tool to influence and understand the human condition at a number of venues, including TEDx and 10 Downing Street. He has published over 100 papers, winning 2 best paper awards at AIIDE. His research technology has over 5 million installs in commercial games – he was invited to talk at GDC about that. He would be interested to supervise students whose research uses games as a tool to gather opinion or promote understanding: to identify research directions and harness the future potential of games, creativity and AI to benefit people and society. He is particularly interested in how games and other curious, creative things can help us to understand a world of complex interacting agents, each living a world created by their own thought (!). Research themes: Research visions for games and AI Game design/development to influence, inform and understand people and society Game AI Email peter.cowling@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Design & Development Game AI - Previous Next

< Back Dr Remo Sasso Queen Mary University of London iGGi Alum I hold a BSc and MSc in Artificial Intelligence at the University of Groningen (NL) and am currently a PhD student at the Queen Mary University of London under the supervision of Paulo Rauber. In addition to my academic work, I have worked as a Machine Learning engineer, and am currently the Head of AI at xDNA, an AI/Cybersecurity-based start-up from the Netherlands. Here I'm leading the initiative Project Aletheia, where we develop AI-driven tools to optimize the workflow of professional fact-checkers, with the overarching goal of ensuring information integrity in the world. Foundation World Models and Foundation Agents for Reinforcement Learning My research focuses on developing reinforcement learning algorithms that are both scalable and sample-efficient through Bayesian methods and model-based approaches, recently with a particular emphasis on Large Language Models (LLMs). My previous research focused on principled, efficient and scalable exploration algorithms for reinforcement learning, e.g. Poster Sampling for Deep Reinforcement Learning (ICML 2023), where we developed a reinforcement learning algorithm that can be considered state-of-the-art in Atari games. Currently I'm particularly interested in the integration of LLMs in the reinforcement learning framework, both as decision-making agents and simulators. My current research, called "Foundation World Models and Foundation Agents for Reinforcement Learning" investigates this integration in-depth and shows that large models show significant potential in various reinforcement learning tasks, ranging from decision-making in stochastic environments to serving as world models. Email r.sasso@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Paulo Rauber Featured Publication(s): Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds On the Limits of Tabular Hardness Metrics for Deep RL: A Study with the Pharos Benchmark VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts Making Connections: Neurodevelopmental Changes in Brain Connectivity after Adverse Experiences in Early Adolescence Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning Simultaneous multi-view object recognition and grasping in open-ended domains Posterior Sampling for Deep Reinforcement Learning Themes Game AI - 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

< Back Luiza Gossian Queen Mary University of London iGGi PG Researcher Available for placement Luiza is a multidisciplinary researcher, game designer and developer interested in translating real world concepts into engaging game mechanics. Her work explores how games can bridge the gap between serious and entertainment design, combining the strengths of both to tackle difficult topics in new and unexpected ways. As an experienced artist, graphic designer and photographer, Luiza uses her visual skills and psychology background to prototype experimental game designs, design game documentation and craft atmospheric experiences. A description of Luiza's research: Luiza’s work explores alternative approaches to serious games that blend the accessibility and engagement of casual game design with the applied foundations of research-driven game development. Using her project Detachment Undone, an abstract arcade game inspired by the ten stages of genocide, she is investigating how to design games about genocide that break away from traditional, narrative-centric approaches and embrace the ludic potential of games. Drawing on theories of intergroup and cultural psychology, she is exploring how these difficult themes can be expressed through mechanics in engaging, effective and informative ways. Email l.gossian@outlook.com Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Jo Iacovides Dr Jeremy Gow Themes Applied Games Design & Development - 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. Email t.broad@gold.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Co-Designing Fashion with AI: A Small-Data Approach to Generative Garment Design Expanding the Generative Space: Data-Free Techniques for Active Divergence with Generative Neural Networks 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 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

< Back Susanne Binder Queen Mary University of London iGGi Manager iGGi Admin iGGi Manager @ QMUL ; alongside David Hull (iGGi Manager @ UoY) , and supported by Shopna Begum , Helen Tilbrook and Oliver Roughton, she's mostly in charge of making things run at iGGi with particular focus on iGGi-QMUL-specific admin iGGi-QMUL-specific student concerns PR, website and social media industry liaison Email s.binder@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes - Previous Next

< Back Dr Martin Balla Queen Mary University of London iGGi Alum Before starting his PhD Martin studied Computer Science at the University of Essex. His main interest is artificial intelligence and its application to all sort of problems ranging from computer vision to game AI. He likes spending his spare time with various activities which mainly involves reading, playing video games and skateboarding. Martin's PhD thesis focuses on Reinforcement Learning agents that can adapt to changes in the reward function and/or changes in the environment. His work investigates how agents can transfer their knowledge to changes in the environment, such as new rewards, levels or visuals. Outside of his main research direction, Martin is involved with the Tabletop games framework (TAG), which is a collection of various tabletop games implemented with a common API with a focus on various game-playing agents (including RL). TAG brings various challenges to RL agents compared to search-based agents, such as complex action spaces, unique observation spaces (various embeddings), multi-agent dynamics with competitive and collaborative aspects, and lots of hidden information and stochasticity. Email m.balla@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): Multi-task Reinforcement Learning for Adaptive Agents Program Committee and Subreviewers Tiny Moves: Game-based Hypothesis Refinement PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games TAG: Pandemic Competition Task Relabelling for Multi-task Transfer using Successor Features TAG: A tabletop games framework Design and implementation of TAG: a tabletop games framework Evaluating generalisation in general video game playing Evaluating Generalization in General Video Game Playing Analysis of statistical forward planning methods in Pommerman Themes Game AI - Previous Next

< Back Dr Timea Farkas Goldsmiths iGGi Alum Timea is a researcher striving to understand how people engage with technologies—broadly defined—in their everyday lives, and how new technologies can enhance people's experiences of play, creative expression, and beyond. She has always been drawn to learning new things, with a background ranging from creative arts through games to science, which allows her to apply an interdisciplinary outlook towards research. She holds an MA in Sonic Arts from the University of Sheffield and has graduated with a First Class (Hons) degree in music composition and technology with a special award for outstanding achievement and collaboration. A description of Timea's research: This research project centres around understanding board game players' relationship with the immersive capabilities of hybrid board games - board games with a digital component - through finding novel interactions which strengthen the sensory elements of tabletop games. By focusing on physical board game pieces as alternative input devices to touch screens, the goal is to explore the design space of analogue-digital hybrids with a player-centric approach. Email farkasmarimba@gmail.com Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Exploring the Design Space of Analogue-Digital Hybrid Boardgames Using a Player-Centric Approach How Boardgame Players Imagine Interacting With Technology The Effects of a Soundtrack on Board Game Player Experience A Grounded Analysis of Player-Described Board Game Immersion Themes Creative Computing Immersive Technology Player Research - Previous Next