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< Back Sunny Thaicharoen Queen Mary University of London iGGi PG Researcher Available for placement Sunny is a passionate esports enthusiast, with a love of MOBA games. His background is in engineering and entrepreneurship, with a Master of Technology Entrepreneurship degree from University College London. He is the creator of YGOscope, a statistical game data platform for a competitive card game, Yu-Gi-Oh. Sunny is an avid player of competitive Dota in his spare time, and is also a keen theme park enthusiast. He is interested in modelling metagames of MOBAs through game data and player research, particularly how players adopt the most effective strategies when changes to the stable gameplay state occurs. A description of Sunny's research: The project focuses on how the META - most effective tactics available - of MOBA games shift during disruption (usually through gameplay updates) between states of ignorance and stability within the player space of these games, to deepen our understanding of how players adapt to the changes that these gameplay updates cause, and why. There is a large degree of variability of how new METAs develops, and currently there is little research on the meta and metagame front. Available research so far has been based on defining the phenomena and resulting effects of gameplay updates, but little modelling has been done to attempt bring these fragmented pieces of knowledge together and attempt to structure them. The study and structuring of this phenomena can be an ideal starting point in understanding how effective strategies develop not only in MOBAs or video games, but any other competitive games such as chess, trading card games or sports. t.thaicharoen@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/thaicharoens/ LinkedIn BlueSky https://github.com/thaicharoens Github Supervisors: Prof. Anders Drachen Dr Jeremy Gow Featured Publication(s): An ecosystem framework for the meta in esport games Themes Esports Game Data Player Research - Previous Next

< Back Michael John Saiger University of York iGGi PG Researcher Available for post-PhD position 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 Michael Aichmüller Queen Mary University of London iGGi Alum My background lies in physics and statistical mathematics with a later specialization in optimization in the fields of Reinforcement Learning (RL) and Causal Inference. My first encounters with RL occurred during my Masters when studying how to create strong policies in perfect information games using algorithms, such as MinMax, MCTS, DQN, and later AlphaZero variants. My favorite game application remains the board game ‘Stratego’. In the meantime I investigated the estimation of causal parents influencing a target variable from interventional datasets for my Master’s thesis. Specifically, how well Deep Learning estimations could replace exponentially scaling graph search methods with approximations requiring only polynomial runtime. A description of Michael's research: My research focuses on the state-of-the-art in game-playing solutions for imperfect information games (think games like Poker, Stratego, Liar’s Dice etc.). I am particularly interested in the application of No-Regret (and related) methods which seek to learn those actions that provided the most benefit (or least regret) compared to the benefit all possible actions provided on average. These methods learn such via iterative play to find a Nash-Equilibrium (NE), a game-theoretic concept comparable to an optimal policy known from Single-Agent RL, but for all partaking players at once. Particularly, variants of Counterfactual Regret Minimization (CFR) remain the state-of-the-art algorithms for computing NEs in 2-player zero-sum games due to their success in tabular form so far. Yet, prohibitive complexity and memory scaling bars them from large-scale applications. Hence, research of recent years seeks to couple CFR (and other No-Regret methods) with function approximation, such as Deep Learning, to scale up the size of applicable games with already notable successes (Deepstack, Libratus, Pluribus, DeepNash). My research seeks to contribute to this endeavour by first analyzing the specifics of established methods and finding ways to introduce Hierarchical RL concepts to No-Regret learning. Please note: Updating of profile text in progress m.f.aichmueller@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/michael-aichmueller/ LinkedIn BlueSky https://github.com/maichmueller Github Supervisor(s): Prof. Simon Lucas Dr Raluca Gaina Themes Applied Games Game AI - Previous Next

< 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 Mastodon http://kisenshi.github.io/ Other links Website https://www.linkedin.com/in/cguerreromero/ LinkedIn BlueSky https://github.com/kisenshi Github 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. David Adger Queen Mary University of London Supervisor Inventing new languages for in-game communications; studying their effects on game play and character development. d.j.adger@qmul.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Creative Computing - Previous Next

< Back - @ Develop:Brighton 2025 - 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. alex.flint@york.ac.uk Email Mastodon https://alexflint.tech Other links Website https://www.linkedin.com/in/alexlflint/ LinkedIn https://bsky.app/profile/alexlflint.bsky.social BlueSky Github 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 Prof. Nick Pears University of York Supervisor Nick Pears is a Professor of Computer Vision in York’s Vision, Graphics and Learning (VGL) research group. He works on statistical modelling of 3D shapes, with an emphasis on the human face and head. The Liverpool-York Head Model and the associated Headspace training set has been downloaded by over 100 research groups internationally, with the Universal Head Model being downloaded by 50 research groups. His most recent work with his PhD students has focused on semantic disentanglement of 3D images and how to make autonomous vehicles safer and more trustworthy when using computer vision systems. He is assessor for many PhDs including construction of generative models for novel video content using adversarial deep learning techniques. nick.pears@york.ac.uk Email Mastodon https://www-users.cs.york.ac.uk/np7/ Other links Website https://www.linkedin.com/in/nick-pears-90970312/ LinkedIn BlueSky Github Themes Creative Computing Game AI - Previous Next

< Back Dr Anthony Constantinou Queen Mary University of London Supervisor Anthony Constantinou’s research is on Bayesian Artificial Intelligence for causal discovery and intelligent decision making under uncertainty. He applies his research to a wide range of areas, including gaming, sports, medicine and finance. He is the founder of the Bayesian Artificial Intelligence research lab at Queen Mary University of London. He is interested in supervising students who are interested in working with machine learning algorithms that discover causal relationships from data (applied to game data), or building intelligent decision-making models using Bayesian networks (applied to game data). Please note that these projects focus on working with game data. Students interested in these projects should have skills that are relevant to: Machine learning for causal discovery Bayesian networks Statistics and probability theory a.constantinou@qmul.ac.uk Email Mastodon https://www.constantinou.info Other links Website https://www.linkedin.com/in/anthony-c-constantinou-728b6b49/ LinkedIn BlueSky Github Themes 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 Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next

< Back Dr Agnieszka Lyons Queen Mary University of London Supervisor Agnieszka Lyons is a linguist and discourse analyst specialising in digitally mediated communication and multimodal communication, particularly across geographic distance. She explores the ways in which users of digital media construct their digitally mediated personae, particularly from the perspective of performance of the embodied selves, entering intersubjective spaces through verbal and non-verbal discourse and creating the feeling of physical and social presence across geographical distance. This can include multimedia sharing, avatar design, textual representation of nonverbal content, and others. She is particularly interested in supervising students with a communication, HCI, social and behavioural sciences background on the following topics: Player experience Player in-game interaction Construction of alternative personae Performance of player identities a.lyons@qmul.ac.uk Email Mastodon https://agnieszkalyons.wordpress.com/ Other links Website https://www.linkedin.com/in/agnieszka-lyons-3831592/ LinkedIn BlueSky Github Themes Player Research - Previous Next

< Back Dr Mihail Morosan University of Essex iGGi Alum Computational Intelligence and Game Balance. (Industry placement at MindArk) Game design has been a staple of human ingenuity and innovation for as long as games have been around. From sports, such as football, to applying game mechanics to the real world, such as reward schemes in shops, games have impacted the world in surprising ways. This process can, and should, be aided by automated systems, as machines have proven to be capable of finding innovative ways to complement human intuition and inventiveness. When man and machine cooperate, better products are created and the world has only to benefit. My research seeks to find, test and assess methods to apply computational intelligence to human-led game balance. Early research has proven that AI can successfully aid game designers in analysing the viability of various game rules and I intend to document this and polish the techniques that will result from my work. To achieve this, I am making use of cutting edge algorithms, powerful AI techniques and novel methods. Most of the current work done involves the use of evolutionary algorithms, as well as statistical analysis and evaluation of intelligent agents in various video games. Programmer (with a focus on optimisation and quick deliverables, mostly due to competitive experience), gamer (games are fun, relaxing and a great social experience), technology consumer (comes with the programmer bit) and all around happy guy stumbling through the world. Once ended up in a management internship at a bank thinking the application was for a programming position. And another time told an interviewer that "buying and eating a burger to solve hunger" is a legitimate problem-solving skill. Somehow received an invitation to the next interview stage. me@morosanmihail.com Email Mastodon Other links Website https://uk.linkedin.com/in/morosanmihail LinkedIn BlueSky Github Featured Publication(s): Automating game-design and game-agent balancing through computational intelligence Lessons from testing an evolutionary automated game balancer in industry Genetic optimisation of BCI systems for identifying games related cognitive states Online-Trained Fitness Approximators for Real-World Game Balancing Evolving a designer-balanced neural network for Ms PacMan Speeding up genetic algorithm-based game balancing using fitness predictors Automated game balancing in Ms PacMan and StarCraft using evolutionary algorithms Themes Design & Development Game AI Player Research - Previous Next

< Back Dan Cooke University of York iGGi PG Researcher Available for placement Dan has a keen interest in the world of finance and how traditional finance interacts with the games industry. He is interested in how criminals use videogame ecosystems for crime and money laundering purposes. He has a background in Accounting and Finance and graduated with a MA in Applied Accounting from De Montfort University in 2019. Outside of his professional life he has an interest in E-Sports and competitive gaming and the content creation and monetisation of these industries. His research interests include money laundering in secondary video game markets, video game monetisation and how users experience with monetisation and secondary markets. A description of Dan’s research: Detecting money laundering in video games through secondary marketplaces Dan’s research has a focus on how criminals can use secondary video game markets for the purposes of money laundering. This includes using internal (developer supported) and external (community ran) systems for the purposes of money laundering. His research aims to identify the scale of the issue and provide ways to identify laundering in these markets as well as investigating safeguards that could be implemented in order to mitigate the risks of money laundering occurring in video game secondary markets. dan.cooke@york.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Supervisor(s): Dr David Zendle Featured Publication(s): Money laundering through video games, a criminals' playground Themes Esports Game Data Player Research - Previous Next