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  • Joshua Kritz

    < Back Joshua Kritz Queen Mary University of London iGGi PG Researcher Available for placement Graduated in Applied Mathematics in computer science, however my love for games pushed me to dedicate myself for studying them. This led me to brave many areas of knowledge, such as: psychology, design, education, production and entrepreneurship. My work as a teacher allowed me develop many of these skills in practice, besides invoking a new perspective about the world. On a personal level, I love new experiences that can teach me new knowledge and, most important, I am very open minded and easy to talk to! I believe discussion leads to enlightenment. A description of Joshua's research: Card games, in particular Trading Card Games (TCGs) thrive on using the synergy between the cards to create emergent and interesting gameplay. However, these games usually have hundreds of different cards to create such rich experience, with some older TCGs featuring thousands of different cards. With such a huge amount of different cards playtesting these games present a big challenge. In example a new set of Magic the Gathering takes over 3 years of development to be fully designed. But even considering simpler exemplars like Dominion or Assencion can be difficult to balance, and both games are known to need a few expansions of experience to indeed provide a well balanced experience. One way to make this task faster and easier is to use automated agents to playtest the game exhaustively and provide much needed data. Whilst this would assist card game development, it is not used in practice, the playtesting of card games is still completely done by players. Even with systematic playtesting there is a limit of how much of the possibilities humans can test. However, implementing playtesting of card games have two big challenges, which are the main reason it has not been implemented in practice yet. First: Automated agents are not great when playing a game with too many variables (different cards) Second: The possible combinations of cards used in a deck or set of a single game is huge. My research aim to address the second issue by using a theory of synergy between cards to reduce the search space necessary to properly evaluate a card game. j.s.kritz@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/joshua-kritz-38808379/ LinkedIn BlueSky Github Supervisor: Dr Raluca Gaina Featured Publication(s): A FAIR catalog of ontology-driven conceptual models A Conceptual Model for the Analysis of Investigation Elements in Games A Vocabulary of Board Game Dynamics Unveiling modern board games: an ML-based approach to BoardGameGeek data analysis When 1+ 1 does not equal 2: Synergy in games Towards an Ontology of Wargame Design Themes Applied Games Design & Development Game AI Previous Next

  • Memo Akten

    < Back Dr Memo Akten Goldsmiths iGGi Alum Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression Real-time, interactive, multi-modal media synthesis and continuous control using generative deep models for enhancing artistic expression. This research investigates how the latest developments in Deep Learning can be used to create intelligent systems that enhance artistic expression. These are systems that learn – both offline and online – and people interact with and gesturally ‘conduct’ to expressively produce and manipulate text, images and sounds. The desired relationship between human and machine is analogous to that between an Art Director and graphic designer, or film director and video editor – i.e. a visionary communicates their vision to a ‘doer’ who produces the output under the direction of the visionary, shaping the output with their own vision and skills. Crucially, the desired human-machine relationship here also draws inspirations from that between a pianist and piano, or a conductor and orchestra – i.e. again a visionary communicates their vision to a system which produces the output, but this communication is real-time, continuous and expressive; it’s an immediate response to everything that has been produced so far, creating a closed feedback loop. The key area that the research tackles is as follows: Given a large corpus (e.g. thousands or millions) of example data, we can train a generative deep model. That model will hopefully contain some kind of ‘knowledge’ about the data and its underlying structure. The questions are: i) How can we investigate what the model has learnt? ii) how can we do this interactively and in real-time, and expressively explore the knowledge that the model contains iii) how can we use this to steer the model to produce not just anything that resembles the training data, but what *we* want it to produce, *when* we want it to produce it, again in real-time and through expressive, continuous interaction and control. Memo Akten is an artist and researcher from Istanbul, Turkey. His work explores the collisions between nature, science, technology, ethics, ritual, tradition and religion. He studies and works with complex systems, behaviour, algorithms and software; and collaborates across many disciplines spanning video, sound, light, dance, software, online works, installations and performances. Akten received the Prix Ars Electronica Golden Nica in 2013 for his collaboration with Quayola, ‘Forms’. Exhibitions and performances include the Grand Palais, Paris; Victoria & Albert Museum, London; Royal Opera House, London; Garage Center for Contemporary Culture, Moscow; La Gaîté lyrique, Paris; Holon Design Museum, Israel and the EYE Film Institute, Amsterdam. Please note: Updating of profile text in progress memo@memo.tv Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Top-Rated LABS Abstracts 2021 Deep visual instruments: realtime continuous, meaningful human control over deep neural networks for creative expression Deep Meditations: Controlled navigation of latent space Learning to see: you are what you see Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks Mixed-initiative creative interfaces Learning to see Real-time interactive sequence generation and control with Recurrent Neural Network ensembles Collaborative creativity with Monte-Carlo Tree Search and Convolutional Neural Networks Sequence generation with a physiologically plausible model of handwriting and Recurrent Mixture Density Networks Deepdream is blowing my mind All watched over by machines of loving grace: Deepdream edition Realtime control of sequence generation with character based Long Short Term Memory Recurrent Neural Networks Themes Game AI - Previous Next

  • Florence Smith Nicholls

    < 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

  • Yizhao Jin

    < Back Dr Yizhao Jin Queen Mary University of London iGGi Alum Currently a student at Queen Mary University of London (QMUL), I have delved deep into the realms of artificial intelligence and game design. With a passion for understanding the complexities behind real-time strategy (RTS) games and their dynamic, unpredictable nature, I have committed myself to contribute novel insights to this domain. Research: My primary research area is Hierarchical Reinforcement Learning (HRL) for Real-Time Strategy (RTS) games. RTS games, known for their intricate mechanics and vast decision spaces, present a formidable challenge for traditional AI approaches. By employing HRL, I aim to develop agents that can not only understand the multi-layered tactics and strategies of these games but also learn to adapt to ever-changing game scenarios efficiently. The main objectives of my research are: Better Generalization: To create agents that can seamlessly transition between different RTS games or various maps within the same game without extensive retraining. This involves understanding common strategic threads across multiple game domains. Efficient Training: RTS games are inherently time-consuming due to their vast decision spaces and prolonged gameplay. My research seeks ways to optimize the training process, ensuring that AI agents can learn faster and with fewer computational resources. acw596@qmul.ac.uk Email Mastodon Other links Website LinkedIn BlueSky https://github.com/decatt Github Supervisors: Prof. Greg Slabaugh Prof. Simon Lucas Themes Game AI Previous Next

  • James Goodman

    < Back Dr James Goodman Queen Mary University of London 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. james.goodman@qmul.ac.uk Email Mastodon https://www.tabletopgames.ai/ Other links Website https://www.linkedin.com/in/james-goodman-b388791/ LinkedIn BlueSky Github Supervisors: Dr Diego Pérez-Liébana Prof. Simon Lucas Featured Publication(s): 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 PyTAG: Challenges and Opportunities for Reinforcement Learning in 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

  • Prof Paul Cairns

    < Back Prof. Paul Cairns University of York iGGi Chair Supervisor Paul Cairns is a professor interested in Human-Computer Interaction (HCI) generally and specifically on how games work to produce the experiences that players really value. He has looked extensively at immersion and engagement in games but is also developing new ideas on players experiences of challenge and uncertainty. He has been teaching HCI for over twenty years and is particularly interested in the rigorous application of research methods having co-edited the first book on research methods for HCI and written another about doing better statistics in HCI. He strongly believes in self-explanatory book titles. He is also Scholar-in-Residence at The AbleGamers Charity, based in the USA, through which he is working with players and game developers to inform and advance the development of accessible games. With his colleagues there, he produced the Accessible Player Experiences (APX) design patterns and card deck. He is particularly interested in supervising students with a HCI, behavioural sciences, media or computer science background on the following topics: Understanding player experiences Developing new measures of player experience whether based on self-report, physiological or other instruments Accessible player experiences Using games to understand and inform people’s experiences with other interactive systems Research themes: Accessible Games Games with a Purpose Player Experience paul.cairns@york.ac.uk Email Mastodon https://www-users.cs.york.ac.uk/~pcairns Other links Website https://www.linkedin.com/in/paul-cairns-99a1b32/ LinkedIn BlueSky Github Themes Accessibility Applied Games Game Data Player Research - Previous Next

  • Zoe O Shea

    < Back Zoë O’Shea Goldsmiths iGGi PG Researcher Zoë O’Shea is an Irish freelance games designer and artist, working on her thesis in game design and player psychology. Her previous qualifications include 3D Generalism, and an MA in Digital Game Design and Theory. She is endlessly curious about the meaning and value that technology can bring to the world, exploring the human experience as a core principle of her work. She firmly believes in the importance of creating a more joyful and inclusive world. Zoë has previously worked with a range of clients and companies including A Brave Plan, Surgent Studios, Transport for London (TfL) and LEGO. In 2019, Zoë was awarded a Digital Fellowship from the Royal Shakespeare Company (RSC) in collaboration with Magic Leap. Zoë worked with other creatives for a year to explore the future of theatre and Spatial Computing (Mixed Reality). The programme completed in Feb 2020, through the generous support of Magic Leap, the RSC, their technologists, industry partners, i2 Media Research and the University of Portsmouth. Currently, Zoë is working on completing her thesis while offering consultancy services for games and start-ups looking to expand their knowledge in soft aesthetics, tend & befriend game design and immersive technology. A description of Zoë's research: Tend & Befriend: A New Perspective on Player Psychology in Digital Games Many are familiar with the term "fight-or-flight" - a stress response activated when animals come into conflict with a stressor or threat. Less commonly known is "tend & befriend", an alternative theory of stress response which suggests that engaging with tending and affiliative behaviours under duress can soothe and protect us. This thesis investigates this phenomenon in digital games, with a focus on empirical data and design. Results demonstrate a consistent niche in the games industry for "tend & befriend" centric design and the value in synthesising previous design frameworks to create a intentional and polished experience for players. z.oshea@gold.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/meowmentai/ LinkedIn BlueSky Github Supervisor(s): Prof. Richard Bartle Featured Publication(s): The impact of self-representation and consistency in collaborative virtual environments Themes Design & Development Immersive Technology Player Research - Previous Next

  • Prasad Sandbhor

    < Back Prasad Sandbhor University of York iGGi PG Researcher Available for placement Prasad is a serious game designer and researcher. He has designed digital, tabletop and hybrid games in diverse areas such as education, healthcare, entrepreneurship, social safety, accessibility and sustainability. He is a part of the ‘Play in Nature’ initiative that crafts playful experiences to connect people with nature around them. He also teaches game design and user experience design. As a multidisciplinary design consultant, Prasad has been involved in conceptualising and creating B2C and B2B digital products for Indian as well as international organisations. His professional experience of 8 years in setting and leading design teams has made him proficient in strategic management of design. Prasad has been able to maintain his secret identity as a freelance author too. He writes short stories and essays in his native language, Marathi. A description of Prasad's research: Prasad’s PhD research explores designing games that facilitate the sensemaking of climate actions among university students. It defines ‘sensemaking’ as a structured process aiding the understanding of alternative pro-environmental actions within complex constraints, involving activities like reflection, brainstorming, and critiquing. The primary objective of his work is to identify game elements that impact players’ ability to make sense of climate actions to articulate design and facilitation guidelines for researchers, designers, and educators from climate change education and communication domains. It also aims to explore the transferability of sensemaking from the game into the real world. As a part of his research, Prasad is designing 3 climate change games using user-centred methods and exploratively evaluating them to see how they help players experience and develop sensemaking. He started with ‘Climate Club’, a tabletop role-playing game dealing with climate action-related decision-making challenges within everyday constraints. Its evaluation showed that the use of curated group setup, relatable contexts, problem-solving mechanic, and explicit mention of climate issues enhances sensemaking while group dynamics and asymmetric role-plays may cause hindrance. Combining these with other literature findings, Prasad designed ‘Climate Club 2.0’, a mini-live action role-playing game (LARP) about planning a climate-friendly holiday which is currently under evaluation. prasad.sandbhor@york.ac.uk Email Mastodon https://linktr.ee/prasadsandbhor Other links Website https://www.linkedin.com/in/prasad-sandbhor/ LinkedIn BlueSky Github Supervisor: Dr Jon Hook Featured Publication(s): Radical Alternate Futurescoping: Solarpunk versus Grimdark Climate Club: A Group-based Game to Support Sensemaking of Climate Actions Radical Alternate Futurescoping: Solarpunk versus Grimdark Themes Applied Games Design & Development - Previous Next

  • Dr Mike Cook

    < Back Dr Mike Cook Supervisor Mike is a Senior Lecturer at King's College London where he leads research into automated game design, computational creativity, and the theory and practice of generative systems. mike@possibilityspace.org Email Mastodon https://www.possibilityspace.org/ Other links Website LinkedIn BlueSky Github Themes Creative Computing Design & Development Game AI - Previous Next

  • Dr Changjae Oh

    < Back Dr Changjae Oh Queen Mary University of London Supervisor Changjae Oh joined Queen Mary University of London (QMUL) in September 2019 as a Lecturer at the School of Electrical Engineering and Computer Science (EECS). He was a postdoctoral researcher at QMUL EECS from 2018 to 2019. He received a PhD in Electrical and Electronic Engineering in 2018 at Yonsei University, South Korea. His research expertise spans a range of researches that are based on visual signals, such as image processing, computer vision, and vision-based machine perception, combined with machine/deep learning. Within the topics with IGGI, he is particularly interested in students who want to investigate the topics about vision-based AI perception in a game environment and game engines for real-robot perception. c.oh@qmul.ac.uk Email Mastodon https://eecs.qmul.ac.uk/~coh/ Other links Website https://www.linkedin.com/in/changjae-oh-42a36685 LinkedIn BlueSky Github Themes Applied Games Game AI - Previous Next

  • Dr Guifen Chen

    < Back Dr Guifen Chen Queen Mary University of London Supervisor Dr Guifen Chen is a Lecturer in Neurobiology at QMUL. Her work focuses on the neuronal basis of multisensory integration, spatial cognition and memory. Her lab uses state-of-the-art techniques such as immersive virtual reality and in vivo electrophysiological/probe recording in mice. Her research is currently supported by funding from BBRSC and the Royal Society. Dr Chen completed her undergraduate studies in both biology and computer science at East China Normal University in China. She then pursued PhD in neuroscience, conducting research at both East China Normal University and Boston University in the USA. Following that, she undertook postdoctoral research at University College London in the UK. Her work has been published in high-impact journals such as Nature Communications, eLife, and Current biology. guifen.chen@qmul.ac.uk Email https://orcid.org/0000-0002-5459-660X Mastodon https://www.qmul.ac.uk/sbbs/staff/guifen-chen.html Other links Website https://www.linkedin.com/in/guifen-chen-51039973/ LinkedIn BlueSky https://github.com/annie2013 Github Themes Creative Computing Design & Development Immersive Technology Player Research - Previous Next

  • Laura Helsby

    < Back Dr Laura Helsby University of York iGGi Alum Laura Helsby is a HCI researcher with a background in psychology, currently examining how features of games might be beneficial to wellbeing and mood. She is particularly interested in how people with persistent low mood play and experience games, and what this might mean for their wellbeing. So far, she has conducted one interview study asking people with low mood what they play and why, and one diary study investigating the 'in the moment' effects and motivations for gaming. Future plans involve making more direct measures of the impact of particular games on wellbeing, as well as looking further into the FPS and simulation genres to unpack what about these games might make them appealing to people with persistent low mood. Laura has achieved an MSc in Foundations in Clinical Psychology from Newcastle University and a BSc in Psychology from the University of York. In her spare time, Laura enjoys denying she is a computer scientist at all. Her hobbies include reviewing books professionally, board game nights and of course, playing video games. laura.helsby@york.ac.uk Email Mastodon Other links Website LinkedIn https://bsky.app/profile/laurahelsby.bsky.social BlueSky Github Supervisors: Prof. Paul Cairns Dr Jo Iacovides Featured Publication(s): "Leave our kids alone!": Exploring Concerns Reported by Parents in 1-star Reviews Do People Use Games to Compensate for Psychological Needs During Crises? A Mixed-Methods Study of Gaming During COVID-19 Lockdowns Themes Applied Games Player Research - Previous Next

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