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< Back Helen Tilbrook University of York iGGi Administrator iGGi Admin iGGi Administrator at York helen.tilbrook@york.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes - Previous Next

< 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

< Back Dr Sarah West University of York Supervisor Sarah West is an interdisciplinary researcher and practitioner working to bring diverse voices into research through participatory approaches, including citizen science. Sarah is currently Director of SEI York, a Centre of the Stockholm Environment Institute, a science-to-policy research institute, whose York Centre is at the University of York in the Department of Environment and Geography. She has used citizen science approaches to address topics as diverse as air pollution, biodiversity, parenting, and exploring community responses to Covid-19. Her projects mainly take place in the UK and Kenya. Sarah has spent over a decade designing, running and evaluating citizen science projects, and together with other SEI colleagues has written reports for Defra, UK Earth Observation Framework and journal articles exploring who participates in citizen science, their motivations for participation, and how volunteers can be recruited and retained. She is particularly interested in exploring how different messaging and communication affects participation in citizen science projects. sarah.west@york.ac.uk Email Mastodon https://www.york.ac.uk/sei/staff/sarah-west/ Other links Website https://www.linkedin.com/in/sarah-west-59b82690/ LinkedIn BlueSky Github Themes Accessibility Design & Development Player Research - Previous Next

< Back Guilherme Matos de Faria University of York iGGi Alum I am a Portuguese student with a background in Artificial Intelligence. In 2016 I started attending video game tournaments and learned to analyse my matches and improve from it. When I did my masters in AI, I noticed that I could join my professional skills and my hobbies together to create something relevant to AI and competitive gaming. A description of James' research: I am looking to better understand which actions and decisions have the biggest impact on the outcome of a game. Currently, I am particularly focused on competitive turn based card games. What are the best players doing to win? How can players adapt to improve their chances of success? These are the questions I am hoping to help answer, giving players a better understanding of the game and how to improve. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Themes Game AI - Previous Next

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

< Back Dr Josh Reiss Queen Mary University of London Supervisor Josh Reiss investigates transformative technologies focused around audio production and sound design. He has published more than 200 scientific papers (including over 50 in premier journals and 5 best paper awards), and co-authored two books. His research has been featured in dozens of original articles and interviews on TV, radio and in the press. He is a Fellow and former Governor of the Audio Engineering Society. He co-founded the highly successful spin-out company, LandR, and recently formed a second start-up, FXive. He maintains a popular blog, YouTube channel and twitter feed for scientific education and dissemination of research activities. Prof. Reiss has a strong interest in games research, especially procedural audio content generation. Procedural content generation supports creation of rich and varied games, maps, levels, characters and narrative elements. But sound design has not kept pace with such innovation. Often the visual aspects of every object in the scene may be procedurally rendered, yet sound designers still rely on huge libraries of pre-recorded samples. This approach is inflexible, limited and uncreative. An alternative is procedural audio, where sounds are created in real-time using software algorithms. But many procedural audio techniques are low quality, computational, or tailored only to a narrow class of sounds. Machine learning from the sample libraries, to select, optimise and improve the procedural models, could be the key to transforming the industry and creating procedural auditory worlds. He welcomes the opportunity to supervise students interested in this or related topics. Research themes: Procedural Content Generation Game Audio and Music Game AI Game Design Computational Creativity Player Experience joshua.reiss@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/~josh/index.htm Other links Website https://www.linkedin.com/in/reissjoshua/ LinkedIn BlueSky Github Themes Creative Computing Game AI Game Audio - Previous Next

< Back Rob Homewood Goldsmiths iGGi Alum Personalised Aesthetics for Games The worldwide games industry is a huge market and as the spectrum of people who spend time playing games increases, there is more and more competition to create games that capture the attentions of a wide audience. Whilst games have been traditionally designed with specific cultural demographics in mind, a game that could dynamically match the cultural values of a range of demographics would maximize its potential market. Robert’s research looks at developing techniques for procedurally generating dynamic game assets that can be viewed as being relevant at a ‘per player’ level. He aims to do this by actively profiling a player’s social networks and building up a picture of the cultural references with which they identify. This knowledge could then be used to create game assets that match an aesthetic the player would likely feel comfortable with, allowing a more flexible decoupling between game mechanics and aesthetic during the design process. Designers could then focus on creating interesting game mechanics that could work in a variety of settings and the system would fill in the aesthetic detail based on the requirements of the individual player at run-time. Having studied in five countries, Robert is currently undertaking a PhD at Goldsmiths, University of London where he is part of the EPSRC funded IGGI (Intelligent Games and Games Intelligence) program. He also holds a Bachelor’s degree in Game Design and Production Management from the University of Abertay Dundee which included a year of studies at the George Mason University Computer Game Design Program. He also spent a year studying Serious Games at Masters level at the University of Skövde in Sweden (which has the longest running Serious Games program in the world). Robert has an active interest in the media arts field and has exhibited his work in three countries. Please note: Updating of profile text in progress Email Mastodon Other links Website https://www.linkedin.com/in/robert-j-homewood-36906132/ LinkedIn BlueSky Github Themes Player Research - Previous Next

< Back Yu-Jhen Hsu Queen Mary University of London iGGi PG Researcher I have always been interested in automation specifically within strategy games, starting from civilization 5. I have a background in Artificial Intelligence with a Master of Science degree from Queen Mary, University of London, with a focus on Game AI, Computer Vision and Machine Learning/Deep Learning. My research interests involve Game AI improvement in real-time turned-based games with the help of data science techniques. A description of Yu-Jhen's research: This project has two goals. Firstly, to improve the performance of MCTS (Monte Carlo Search Tree) implementation. Secondly, the goal is focused on building an AI agent that is able to win the game but also provide feedback information/data about it’s decisions to the players and designers. In order to achieve the goal, the plan of the project is to use different data science skills to enable the game AI agent to understand the utility of different actions and decrease the time needed for making decisions. The data collected can also help the game AI agent explain it’s behaviors, hence provided useful information/data for its users and designers. y.hsu@qmul.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/yujhenhsu/ LinkedIn BlueSky Github Supervisors: Dr Diego Pérez-Liébana Dr Raluca Gaina Featured Publication(s): Why Choose You?-Exploring Attitudes Towards Starter Pokémon Tribes: a new turn-based strategy game for AI research MCTS Pruning in Turn-Based Strategy Games. Themes Game AI Game Data - 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 Dr Daniel Berio Goldsmiths iGGi Alum AutoGraff: A Procedural Model of Graffiti Form. (Industry placement at Media Molecule) The purpose of this study is to investigate techniques for the procedural and interactive generation of synthetic instances of graffiti art. Considering graffiti as a special case of the calligraphic tradition, I propose a "movement centric" alternative to traditional curve generation techniques, in which a curve is defined through a physiologically plausible simulation of a (human) movement underlying its production rather than by an explicit definition of its geometry. In my thesis, I consider both single traces left by a brush (in a series of strokes) and the extension to 2D shapes (representing deformed letters in a large variety of artistic styles). I demonstrate how this approach is useful in a number of settings including computer aided design (CAD), procedural content generation for virtual environments in games and movies, computer animation as well as for the smooth control of robotic drawing devices. Daniel Berio is a researcher and artist from Florence, Italy. Since a young age Daniel was actively involved in the international graffiti art scene. In parallel he developed a professional career initially as a graphic designer and later as a graphics programmer in video games, multimedia and audio-visual software. In 2013 he obtained a Master degree from the Royal Academy of Art in The Hague (Netherlands), where he developed drawing machines and installations materializing graffiti-inspired procedural forms. Today Daniel is continuing his research in the procedural generation of graffiti within the IGGI (Intelligent Games and Game Intelligence) PhD program at Goldsmiths, University of London. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Optimality Principles in the Procedural Generation of Graffiti Style SURFACE: Xbox Controlled Hot-wire Foam Cutter The role of image characteristics and embodiment in the evaluation of graffiti Emergence in the Expressive Machine The CyberAnthill: A Computational Sculpture Sketch-Based Modeling of Parametric Shapes Artistic Sketching for Expressive Coding Calligraphic stylisation learning with a physiologically plausible model of movement and recurrent neural networks Sequence generation with a physiologically plausible model of handwriting and Recurrent Mixture Density Networks AutoGraff: Towards a computational understanding of graffiti writing and related art forms Kinematics reconstruction of static calligraphic traces from curvilinear shape features Interactive generation of calligraphic trajectories from Gaussian mixtures Sketching and Layering Graffiti Primitives. Kinematic Reconstruction of Calligraphic Traces from Shape Features Expressive curve editing with the sigma lognormal model Dynamic graffiti stylisation with stochastic optimal control Computer aided design of handwriting trajectories with the kinematic theory of rapid human movements Generating calligraphic trajectories with model predictive control Learning dynamic graffiti strokes with a compliant robot Computational models for the analysis and synthesis of graffiti tag strokes Towards human-robot gesture recognition using point-based medialness Transhuman Expression Human-Machine Interaction as a Neutral Base for a New Artistic and Creative Practice Themes Game AI - Previous Next

< Back Dr Chris Madge Queen Mary University of London iGGi Alum Turning Difficult Scientific Problems into Easy Games: Crowdsourcing Solutions via Gamification The aim of the research is to exploit, on a large scale, the idea introducing game elements in a non-game context (gamification) and make use of a large population of non-expert users to solve scientific problems (crowdsourcing). The proposed research follows the increasingly popular concept of splitting a large, complex task into small easily digestible tasks that lend themselves to division, distribution and game representation. This research will begin by taking advantage of the University of Essex’s expertise in the field of Natural Language Engineering. Multiple games will be created to attempt to encourage people to participate in training natural language models. This will be achieved by splitting these tasks into smaller problems that can be represented as games, and easily solved by players that could not easily be solved computationally. Alongside this, the success of different gamification methods and game design choices will be evaluated to determine their effect on the information gathered and the accuracy achieved. This evaluation will be used to guide the development of future games in the research with a view to producing better quality models for solving natural language problems, and improving gamification. Prior to starting my PhD with IGGI I completed a BSc in Computer Science and MSc in Advanced Computer Science. During both of those I took multiple computer game and AI courses in addition to text analytics and natural language engineering courses. During my BSc I was fortunate to work at Signal Media as an intern on text analytics related problems. Before starting my BSc I worked as a software developer for 5 years, primarily in web application development. I’ve had a passion for games from a very young age and continue to play on PC, mobile and consoles today. Please note: Updating of profile text in progress Email Mastodon Other links Website LinkedIn BlueSky Github Featured Publication(s): Gamifying language resource acquisition Progression in a language annotation game with a purpose Incremental game mechanics applied to text annotation Making text annotation fun with a clicker game The design of a clicker game for text labelling Crowdsourcing and aggregating nested markable annotations Testing TileAttack with Three Key Audiences Experiment-driven development of a gwap for marking segments in text Metrics of games-with-a-purpose for NLP applications Testing game mechanics in games with a purpose for NLP applications TileAttack Novel Incentives for Phrase Detectives Themes Player Research - Previous Next

< 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