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Locations (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. Locations iGGi Queen Mary University of London (QMUL) iGGi QMUL is located at the heart of East London on Queen Mary, University of London's Whitechapel campus. Read More University of York (UoY) iGGi York is located just outside the City of York's centre, on University of York's East Campus. Read More Goldsmiths, University of London (Goldsmiths) iGGi Goldsmiths is located in New Cross, South East London, five miles from central London. Read More University of Essex (UoE) iGGi Essex is located two miles from the historic city of Colchester and set in over 200 acres of beautiful parkland. Read More

< Back iGGi QMUL is located at the heart of East London on Queen Mary, University of London's Whitechapel campus. iGGi QMUL is part of QMUL’s School of Electronic Engineering and Computer Science . While QMUL-based iGGi PGRs can belong to more than one research group, they all by default belong to the Game AI Group (GAIG) . The iGGi/GAIG office space is situated within the Digital Environment Research Institute (DERI) at Empire House, Whitechapel campus. How to reach the iGGi Offices at Empire House, Whitechapel The address for the iGGi office space is 2nd Floor Empire House DERI 67-75 New Road London, Whitechapel E1 1HH Whitechapel campus map Accesibility: Empire House access guide Arriving by Tube The Whitechapel campus is easily accessible via public transport, with the Whitechapel Underground station on London Underground's Elizabeth Line (purple on the Tube map), Hammersmith and City Line (pink on the Tube map), and District Line (green on the Tube map), just a seven minute walk away. When you exit the station, turn right and walk along Whitechapel Road until the next larger junction. Turn left into New Road. Empire House will be located to your right. Please use the Transport for London Journey Planner to help you plan your journey: https://tfl.gov.uk/plan-a-journey/ or their interactive maps showing Underground, Docklands Light Railway (DLR) and bus information Arriving by Bus The Whitechapel campus is based on Whitechapel Road, on the 25 and 205 bus routes, and Empire House is just off Whitechapel Road, on New Road. Cycling/Walking If you are travelling by bike or walking, please use the postcode above and the campus map to help you navigate to the venue. Bike storage facilities can be found in the Empire House Basement. Arriving by car For both our Mile End and Whitechapel campuses, car parking for visitors is not offered due to our central location. Local parking restrictions also apply on weekdays and weekends.We therefore strongly recommend you use one of the alternative transport methods listed above. If you do need to drive to campus, QMUL open day published a list of offsite parking options within easy reach of Whitechapel, including park and ride options. If you are a blue badge holder and require parking on site, please email opendays@qmul.ac.uk . Queen Mary University of London (QMUL) iGGi QMUL Gallery Map depicting QMUL Mile End campus & the iGGi Con 2023 venue location iGGi Con 2023 venue: The Graduate Centre (Mile End campus, QMUL), viewed from Bancroft Road iGGi Con 2023 venue: Ground floor entrance of the Graduate Centre - Mile End campus, QMUL Mile End campus with the Graduate Centre on the left Birds eye view of Mile End campus, QMUL Map depicting QMUL Whitechapel campus with Empire House where all of the iGGi Office space is located Empire House Basement, QMUL (Whitechapel) iGGi office space, Empire House, QMUL (Whitechapel campus) The Blizard Building opposite Empire House, Whitechapel campus (QMUL) Previous Next

< Back Dr Myat Aung University of York iGGi Alum Immersion is a state in which players are engaged to a degree of total absorption that inhibits the ability to correctly report one’s surroundings or time. Present theory on immersion has developed a coherent model that provides sufficient evidence to distinguish itself from other cognitive concepts such as presence, attention, selective attention, absorption and flow. However, immersion research thus far has been hindered by difficulties with taking in-vivo measurements of cognition and physiological responses during videogame play. This presents an ideal opportunity for implementations of neuroimaging methods to carry out such real time measurements of attention, as well as other cognitive processes and their roles in videogame immersion. Using various combinations of neural and physiological methods such as skin conductance, eye tracking, electroencephalography and even functional magnetic resonance imaging, it is now possible to obtain richer data in immersion research. The goal of this project is to apply such methods in order to better define and measure videogame immersion, identify the cognitive processes and hierarchical models that are involved in immersion and ultimately contribute to the literature in videogame immersion. Though neuroimaging is limited by statistical sensitivity, challenging experimental logistics and non-ideal lab environments, they are still presently the best tools available to obtain fine-grain data of attention and the many other cognitive components of immersion. Such knowledge would contribute significantly to a better understanding of effective development of videogames, as well as educational tools. I am an MPsych Psychology graduate from the University of York, having studied Psychology, Cognitive Neuroscience & Neuroimaging for four years. My Master’s research was primarily in vision, attempting to manipulate and record parahippocampal responses to visual stimuli selected parametrically by computer algorithms. During my degree I also spent much of my time researching videogames, studying the literature on the effects of videogame play on sleep, and working with a IGGI PhD student as a lab assistant. Between my degree and my PhD, I have also been working as a data analyst at Digital Creativity Labs researching skill learning in large gaming populations from Riot Games’ League of Legends. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Different rules for binocular combination of luminance flicker in cortical and subcortical pathways Investigating the non-disruptive measurement of immersive player experience The trails of just cause 2: spatio-temporal player profiling in open-world games Predicting skill learning in a large, longitudinal MOBA dataset Themes Game AI - Previous Next

< Back Dr Dino Ratcliffe Queen Mary University of London iGGi Alum Teaching AI agents transferable skills for game playing My research focuses on the ability of an AI agent to be able to evaluate the various skills it would need to master a game, such as in an FPS (first person shooter) like doom. If the agent can learn to cluster actions that may split into strategies such as attacking enemies, gathering ammo/health and avoiding enemy fire this information could then be used in similar games. This information would also provide a base for being to evaluate players on a skill level, giving a much more granular view of their strengths and weaknesses in any of these games. This could then be used for better matchmaking in team games, placing players into teams whose skill sets complement each other. Other applications include being able to guide the player into situations that give them more experience in the areas they are weakest. Dino started a MSci in computer science at the University of Essex in 2011. During the next 4 years, he focused on modules that involved improving technical skills and Artificial Intelligence. He was the winner of the K.F Bowden Memorial prize in two separate years. Dino worked at the London startup Signal Media during the summer of 2014 and continued to work for them part time during my masters year. He graduated with a 1st class degree. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Cross-lingual style transfer with conditional prior VAE and style loss Author's declaration Win or learn fast proximal policy optimisation Domain Adaptation for Deep Reinforcement Learning in Visually Distinct Games Clyde: A deep reinforcement learning doom playing agent Themes Game AI - Previous Next

< Back Dr Raluca Gaina Queen Mary University of London iGGi Outreach Coordinator iGGi Alum + Supervisor Dr Raluca D. Gaina is currently a Lecturer in Game AI at Queen Mary University of London, where she obtained her Ph.D. in Intelligent Games and Games Intelligence in May 2021 (in the area of rolling horizon evolution in general video game playing). She completed a B.Sc. and M.Sc. in Computer Games at the University of Essex in 2015 and 2016, respectively. In 2018, she did a 3-month internship at Microsoft Research Cambridge, working on the Multi-Agent Reinforcement Learning in Malmo Competition (MARLO). She was the track organiser of the Two-Player General Video Game AI Competition (GVGAI) 2016-2019 and was the Vice-Chair for Conferences of the IEEE CIS Games Technical Committee in 2020. Her research interests include general video game playing AI, evolutionary algorithms, and tabletop games. r.d.gaina@qmul.ac.uk Email Mastodon https://rdgain.github.io/ Other links Website https://www.linkedin.com/in/raluca-gaina-347518114/ LinkedIn BlueSky https://www.github.com/rdgain Github Featured Publication(s): PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games The n-tuple bandit evolutionary algorithm for automatic game improvement Population seeding techniques for rolling horizon evolution in general video game playing Automatic Game Tuning for Strategic Diversity Analysis of vanilla rolling horizon evolution parameters in general video game playing General video game for 2 players: Framework and competition General Video Game Artificial Intelligence Playing with evolution Rolling horizon evolutionary algorithms for general video game playing Self-adaptive rolling horizon evolutionary algorithms for general video game playing Rolling Horizon NEAT for General Video Game Playing Frontiers of GVGAI Planning Planning in GVGAI Efficient heuristic policy optimisation for a challenging strategic card game General video game artificial intelligence Optimising level generators for general video game AI 'Did you hear that?' Learning to play video games from audio cues Project Thyia: A forever gameplayer Tackling sparse rewards in real-time games with statistical forward planning methods General video game ai: A multitrack framework for evaluating agents, games, and content generation algorithms The Multi-Agent Reinforcement Learning in Malm\" O (MARL\" O) Competition VERTIGØ: visualisation of rolling horizon evolutionary algorithms in GVGAI General win prediction from agent experience League of Legends: A Study of Early Game Impact Self-adaptive MCTS for General Video Game Playing The 2016 two-player gvgai competition Introducing real world physics and macro-actions to general video game AI Rolling horizon evolution enhancements in general video game playing Learning local forward models on unforgiving games Themes Game AI - 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). n.penaperez@qmul.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github 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 Dr Nathan Hughes University of York iGGi Alum Nathan Hughes is a player experience researcher who focuses on how player make choices within games. Specifically, the work explores open world games such as Skyrim and the Witcher 3, as these games allow players a vast amount of choice with little restrictions on how and when these are made. However, little research has considered these choices, so little is known about how players experience choice in open world games. Therefore, research questions for this work include; why do players choose not to pursue the main quest? What do players choose to do instead? When and how do they make this decision? His background is in psychology, and so asks these questions from a psychological perspective. The aim is to uncover how the process of choosing unfolds, and how this is influenced. In turn, this may allow reflections on how the decision-making process operates - by analysing choices within open world games, a more controlled (but still intrinsically motivating) setting can be studied. ngjhughes@gmail.com Email Mastodon https://faethfulexplorations.wordpress.com Other links Website https://www.linkedin.com/in/nathan-hughes-1035b611b/ LinkedIn BlueSky Github Supervisor Prof. Paul Cairns Featured Publication(s): Clinicians Risk Becoming "Liability Sinks" for Artificial Intelligence Understanding specific gaming experiences: the case of open world games The need for the human-centred explanation for ML-based clinical decision support systems Growing Together: An Analysis of Measurement Transparency Across 15 Years of Player Motivation Questionnaires Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units Growing together: An analysis of measurement transparency across 15 years of player motivation questionnaires Opening the World of Contextually-Specific Player Experiences No Item Is an Island Entire of Itself: A Statistical Analysis of Individual Player Difference Questionnaires Ethereum Crypto-Games: Mechanics, Prevalence, and Gambling Similarities Themes Player Research - Previous Next

< Back Dr Poonam Yadav University of York Supervisor Dr Yadav research is focused on making the Internet of Things (IoT) and edge computing-based distributed systems resilient, reliable, and robust. This is an interdisciplinary research area that requires expertise in system design and integration along with knowledge of sensor systems, wireless networking, and domain and contextual understanding. To achieve resilience and reliability in the area of resource constraints and distributed systems, I focus on coordination and collaboration using interactions among machines, humans and data entities. These interactions could be categorized as machine-to-machine (M2M), machine-to-human (M2H), and human-to-data (H2D), and involve many challenges such as collaborative trust, privacy, legibility and accountability. Dr Yadav is an active reviewer of many top-tier ACM/IEEE IoT and networking conferences and journals. Dr. Yadav leads ACM-W UK professional chapter and is featured as "People of ACM Europe" and among the top ten N2Women Rising Star in Computer networking and communications in 2020. Research themes: E-Sports Use of IoT in Games Gamifications Citizen Science poonam.yadav@york.ac.uk Email Mastodon https://poonamyadav.net Other links Website https://www.linkedin.com/in/pyadav/ LinkedIn BlueSky https://github.com/pooyadav Github Themes Design & Development Esports Game Data - Previous Next

< Back Florence Smith Nicholls Queen Mary University of London iGGi PG Researcher Florence Smith Nicholls is a game AI PhD researcher based in London. They worked as an archaeologist and heritage consultant for 7 years prior to their doctoral research. Building on their heritage background, they have contributed to the field of archaeogaming through experimenting with archaeological approaches to titles such as Elden Ring and Nier: Automata. They coined the term “generative archaeology games” for their doctoral project on the archaeological recording of procedurally generated content. Their work is motivated by contributing to wider research on games preservation, ethics of game AI and procedural narrative. They are also interested in queer approaches to games, having written about queerness and documenting glitches. They are also a freelance narrative designer, previously a member of the writers' room at the indie studio Die Gute Fabrik. During a placement at the British Library they worked on enhanced curation methods for narrative mobile apps, and were commissioned to produce gameplay footage for the Library's Digital Storytelling exhibition. f.c.smithnicholls@qmul.ac.uk Email http://florencesmithnicholls.itch.io/ Mastodon https://florencesmithnicholls.com/ Other links Website LinkedIn BlueSky Github Supervisor(s): Dr Mike Cook Dr Laurissa Tokarchuk Featured Publication(s): The Dark Souls of Archaeology: Recording Elden Ring “That Darned Sandstorm”: A Study of Procedural Generation through Archaeological Storytelling User-centred collecting for emerging formats Permalife of the Archive: Archaeogaming as Queergaming How To Save A World: The Go-Along Interview as Game Preservation Methodology in Wurm Online Archaeological Gameworld Affordances: A Grounded Theory of How Players Interpret Environmental Storytelling Themes Creative Computing Design & Development Game AI Game Data - Previous Next

< Back Océane Lissillour University of York iGGi PG Researcher Available for placement I started my journey as an undergrad in psychology specialising in ergonomics. It was then that I realised that I could study video games for a living. This led me to relocate myself to the south of France to, mostly enjoy the sun, but also undertake my dream MSc in Technological Innovation and Cognitive Psychology. As part of my master’s internship I had the pleasure to work in collaboration with researchers from the CLLE, a laboratory branch of the national research centre. This helped me develop my knowledge and awareness of video games and motivational processes and convinced me that if I could survive the bureaucracy of the French Government I could probably do a PhD. Afterwards, I moved on to work in Aeronautics for a brief time but landed back to academia in 2024 to join the wonderful iGGI community as a postgraduate researcher. A description of Océane's research: My research focuses on the act of taking a regular activity and ‘gamifying’ it by applying mechanics commonly found inside video games (such as points). This technique has been widely applied within research but its psychological aspects have seldom been studied. The aim of this thesis is to assess the efficacy and applicability of this technique, particularly the score element mechanic. It focuses on understanding the functionalisation of numerical values in games as this has not been studied previously in the literature. This research hopes to contribute to the better understanding of the impact of the design of points on motivation and behaviour. It has been proposed in precedent literature that the use of gamification will provide a partial solution to the critical decline in learners’ motivation and engagement the schooling system faces today. oceane.lissillour@york.ac.uk Email Mastodon Other links Website http://www.linkedin.com/in/oceane-lissillour LinkedIn BlueSky Github Supervisors: Dr Abi Evans Prof. Sebastian Deterding Themes Design & Development Player Research - Previous Next

< Back Dr Tara Collingwoode-Williams Goldsmiths iGGi Alum Tara is an IGGI PhD student from Goldsmiths University taking her Mphil/PhD in Intelligent Games/Game intelligence with a focus on Avatar Embodiment and Interaction within Virtual Reality. Before this she graduated with a Bsc in Creative Computing. Over the years, her interdisciplinary profile has enabled her to work as a Technical Support and Researcher with many organisations in relation to her research, such as UCL, Great Ormond Street Hospital, George Mason Serious Games Institute in the United States where she also co-lectured a XR Games Module and, more recently as an Associate Lecturer in Goldsmiths University teaching Unity based XR experience development. Currently, she is contracting for USTech as an Assistant UX researcher at Facebook whilst completing her PhD program. With this rise in demand for Head Mounted Displays (HMDs), so is the need to create Embodied Shared Virtual Environments (ESVE) where users may experience authentic social interactions. Tara’s research presents an exploratory examination of Embodiment - meaning the subjective feeling of owning a virtual representation in VR, and specifically Consistency in Embodiment - relating to how we prioritize and syncronise objective attributes of embodiment (i.e avatar representation) in order to create ESVEs which supports more intuitive social interaction. The goal is to understand how different technical setups could have a psychological impact on participants' experiences in ESVE. This research hopes to inform development of successful social interaction in a variety of applications in VR, ranging from training to gaming. Tara presently holds a position as Lekturer in VR at Goldsmiths, Universtiy of London. tc.williams@gold.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/tara-collingwoode-williams-81141776/ LinkedIn BlueSky Github Featured Publication(s): Delivering Bad News: VR Embodiment of Self Evaluation in Medical Communication Training The impact of self-representation and consistency in collaborative virtual environments G487 (P) Is clinician gaze and body language associated with their ability to identify safeguarding cues? Evaluating virtual reality experiences through participant choices A discussion of the use of virtual reality for training healthcare practitioners to recognize child protection issues A study of professional awareness using immersive virtual reality: the responses of general practitioners to child safeguarding concerns The effect of lip and arm synchronization on embodiment: a pilot study Themes Applied Games Player Research - Previous Next

< Back Dr Sokol Murturi Goldsmiths iGGi Alum AI for game design: learning from designers For my PhD I am investigating how AI can help developers by learning to generate content in a similar fashion to the developers themselves. I envision a framework based on reinforcement learning, where an AI can learn a design policy for some content domain (e.g., FPS maps or platformer levels) by observing human designers. The AI would learn to take particular design actions in certain kinds of content states. Recent research into reinforcement learning has shown it is a powerful framework for developing complex agent behaviours and I believe there is a lot of potential to apply this work to game design. How would a human and artificial designer interact? Assume that an AI has learned to design a specific kind of content, such as a house, by observing human designers at work. A human designer could then partially develop some new content, and ask the AI to suggest some variations on it (see figure below), with both AI and human iterating on the design in a mixed-initiative interaction. The AI could learn from feedback from both the human designer and playtesting. As human feedback may not produce enough data for effective learning, the AI could perhaps extend this with data from simulated playtests. Game design decisions are often made with an expectation of how the player will react, and I could also look at how player models could be incorporated into the AI designer. In a reinforcement learning approach, the state could represent content+player, and the AI could learn to take design actions aimed a specific types of player. Developers could use this framework to develop content targeted at an individual player's style. Moreover, if the AI has learned something about how the human designer creates content, it can then be used live during the game to modify game elements in response to player interaction. Developers could set up modular levels, giving the AI the ability to adapt certain areas with content generated specifically to match the player. smurt001@gold.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next