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< Back Dr Søren Riis Queen Mary University of London Supervisor Søren Riis has more than 15 years of experience in teaching computability, complexity and the art of creating fast efficient algorithms. He has a strong interest in reinforcement learning and generative adversarial networks (GANs) related to strategy games. Riis has been actively involved in computer chess, and is listed on the wiki of influential people in chess programming https://www.chessprogramming.org/ Søren Riis is a strong player of strategy games including Chess, Shogi, Go and Bridge at an internal level. He has worked as a consultant for an AI company and is involved in applying deep learning for the card game of bridge. For the last 5 years he has been working on technical projects related to machine learning and reinforcement learning. He has practical experience and interest in scientific computing on super computers, and in creating C and C++ libraries to run from within python. Søren Riis is particularly interested in supervising students with a strong technical and/or maths background. Aptitude for strategy games with an interest in one the following ares is an advantage. Games requiring inductive reasoning combined with exploration. Hidden identity games (Werewolf, Resistance/Avalon, Mafia etc) Using GANs to sample realistic scenarios during gameplay Deep Reinforcement Learning in multi-agent strategy games Building and analysing games for investigating evolution of communication. Research themes: Game AI Game Design Game Creativity Games and mathematics s.riis@qmul.ac.uk Email Mastodon https://www.eecs.qmul.ac.uk/profiles/riissoren.html Other links Website https://www.linkedin.com/soren-riis-13602117/ LinkedIn BlueSky Github Themes Creative Computing Game AI Game Data - Previous Next

< Back Peyman Hosseini Queen Mary University of London iGGi PG Researcher Peyman is interested in using his computer science knowledge to support society's well-being. Raised in a family where almost everyone’s work is somehow related to mathematics and its applications, he became passionate about algorithms and combinatorics from an early age. This prompted him to pursue an undergraduate degree in computer engineering with a focus on IT and AI. This background led him to start his PhD at IGGI on building more powerful yet efficient Natural Language Processing models for analysing textual data, a rich and abundant source of gaming feedback. A description of Peyman's research: Peyman's research focuses on advancing deep learning architectures for natural language processing and building tools on top of state-of-the-art models. To contribute to the fundamental understanding and practical application of deep learning in natural language processing, focusing on efficiency and effectiveness, he pursues two main objectives: Designing more efficient models that match or surpass state-of-the-art performance with fewer parameters. Systematically analyzing language models to develop solutions that enhance their effectiveness for end-users, such as game studios. His recent accomplishments towards these goals include: 1. Developing novel attention mechanisms: 1.1 Optimized Attention: 25% parameter reduction 1.2 Efficient Attention: 50% parameter reduction 1.3 Super Attention: 25% parameter reduction with significant performance improvements in language and vision tasks 1.4 All mechanisms demonstrate comparable or superior performance to standard attention across various inputs. 2. Designing and training Hummingbird , a proof-of-concept small language model using Efficient Attention, available on HuggingFace. 3. Conducting a study on large language models' limitations in analyzing lengthy reviews for basic NLP tasks. Proposed solutions offer substantial performance improvements while reducing API costs by more than 90%. s.hosseini@qmul.ac.uk Email Mastodon https://peymanhosseini.net/ Other links Website https://www.linkedin.com/in/peyman-hosseini1 LinkedIn BlueSky https://github.com/Speymanhs Github Supervisors: Dr Ignacio Castro Prof. Matthew Purver Featured Publication(s): Cost-Effective Attention Mechanisms for Low Resource Settings: Necessity & Sufficiency of Linear Transformations Efficient solutions for an intriguing failure of llms: Long context window does not mean LLMs can analyze long sequences flawlessly Brain Drain Optimization (BRADO) Algorithm to Solve Multi-Objective Expert Team Formation Problem in Social Networks You Need to Pay Better Attention: Rethinking the Mathematics of Attention Mechanism GeoPos: A Minimal Positional Encoding for Enhanced Fine-Grained Details in Image Synthesis Using Convolutional Neural Networks Lon-ea at SemEval-2023 Task 11: A Comparison of Activation Functions for Soft and Hard Label Prediction GRACER: Improving the Accuracy of RACER Classifier Using A Greedy Approach Themes Game AI Player Research - Previous Next

< Back Dr Cristina Dobre Goldsmiths iGGi Alum Cristina Dobre has a background in Mathematics and Computing receiving distinction in her undergraduate degree in Computer Science. My current focus is on the nonverbal cues that influence and shape the social interaction in immersive VR environments. More broadly, I'm investigating autonomous agents (or virtual humans) in social settings in terms of non-verbal interactions with users. I'm interested in the underlying mechanics of social interaction that help developing an emphatic and engaging virtual human. At the moment, I'm working on ML models based on multimodal datasets to detect various social cues (such as gaze) or various human-defined social attitudes (such as engagement) in social interactions in VR. I'm also interested in generating more complex behaviour for virtual characters (NPCs) that will improve the user's experience with the NPCs in a social VR setting. Designing communication and other social interactions in immersive VR can be a challenging task, and aspects on this are addressed in my research. The findings from these studies can help game designers and game developers determine the appropriate non-player character's non-verbal (and verbal) behaviour in games, especially in VR games. Along with its applications in the games industry, the findings would be useful for other applications such as designing multi-modal human-machine interactions and other systems for medical purposes, for social anxiety disorders therapy, simulations, training or learning. cristina.dobre@uni-a.de Email https://hci.social/@ShesCristina Mastodon Other links Website https://linkedin.com/shesCristina LinkedIn BlueSky https://www.github.com/shesCristina Github Featured Publication(s): Social Interactions in Immersive Virtual Environments: People, Agents, and Avatars Rolling Horizon Co-evolution in Two-player General Video Game Playing Using machine learning to generate engaging behaviours in immersive virtual environments More than buttons on controllers: engaging social interactions in narrative VR games through social attitudes detection Nice is Different than Good: Longitudinal Communicative Effects of Realistic and Cartoon Avatars in Real Mixed Reality Work Meetings Immersive Machine Learning for Social Attitude Detection in Virtual Reality Narrative Games Direct Gaze Triggers Higher Frequency of Gaze Change: An Automatic Analysis of Dyads in Unstructured Conversation Themes Game AI Immersive Technology - Previous Next

< Back Dr Shanxin Yuan Queen Mary University of London Supervisor Dr Shanxin Yuan is a Lecturer in Digital Environment at Queen Mary University of London. He has rich expertise in deep learning, low level computer vision, and 3D digital modelling of humans from photographs. His PhD thesis focused on 3D hand pose estimation, his work is well recognized in the academia and is also deployed into commercially launched mass market mobile phones. His current research on digital humans focuses reconstructing, modelling, and rendering digital twins. He is interested in super-realistic immersive gaming, body/hand pose and facial expression retargeting, and behaviour analysis with avatars. For the new project in 2023, we are interested in working on human facial expression estimation, high-res realistic face reconstruction and rendering, face re-enactment, and face augmentation. The aim of the project is to build an editable super-realistic 3D human face model that can express novel expressions, views, shapes, and appearance, from multiple sources of input, such as images, sounds, and key points. The related techniques include deep learning, computer vision, natural language processing, and neural rendering. shanxin.yuan@qmul.ac.uk Email Mastodon https://shanxinyuan.github.io/ Other links Website https://www.linkedin.com/in/shanxin-yuan-4859b656/ LinkedIn BlueSky Github Themes Applied Games Creative Computing Game AI Immersive Technology Player Research - Previous Next

< 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 Dr Anna Bramwell-Dicks University of York Supervisor Anna Bramwell-Dicks has an interdisciplinary background which started in Electronics and Music Technology before taking a sideways move to the field of Human-Computer Interaction research. She likes to combine her underlying interest in sound and music with applied psychology and creativity. She is very interested in research involving multimodal interaction (e.g. using audio, haptics, smell and/or proprioception as well as visuals within interfaces) particularly where audio is used to affect user’s behaviour or experiences. She is also very interested in accessibility research and any research in the application area of mental health and mental illness. As a lecturer in Web Development and Interactive Media, based in TFTI, Anna is always interested in work that involves designing and evaluating novel and interesting user experiences, particularly where that leads to the option to create fun, engaging, accessible experiences. She likes to work across a range of application areas ranging from learning environments to e-commerce to escape rooms and cultural exhibits! Anna is keen to work with students who want to design and develop gamified systems to support people with disabilities, physical or mental illness. Or, those who are also interested in multimodal experiences. Research themes: Accessibility Multimodal and multisensory systems Research methods anna.bramwell-dicks@york.ac.uk Email Mastodon Other links Website https://www.linkedin.com/in/anna-bramwell-dicks-2b941a28/ LinkedIn BlueSky Github Themes Accessibility Applied Games Design & Development Game Audio Player Research - 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 Karl Clarke Queen Mary University of London iGGi PG Researcher Available for placement Karl Clarke is a PhD researcher focused on how virtual environments influence social interaction. He was born in England, grew up in the Middle East, and returned to the UK for university. He holds a Bachelor's and a Master's degree in Audio Technology. During the COVID-19 lockdown, he began exploring virtual reality after getting access to a headset, which led to a shift in focus toward social VR. He is now part of the Intelligent Games and Game Intelligence (iGGi) doctoral programme, where his research looks at how spatial layouts and group behavior are shaped by virtual environments in free-standing social settings. Outside of his research, Karl runs SONAR, a music group hosted in VRChat that uses social VR for live performance and shared listening experiences. Through this project, he has independently learned game development skills in 3D modelling, scripting, and a small amount of graphics programming. He is currently looking to collaborate with VR studios or social platforms working on immersive and social experiences. karl.clarke@qmul.ac.uk Email Mastodon https://linktr.ee/llamahat Other links Website https://www.linkedin.com/in/karl-clarke-york/ LinkedIn https://bsky.app/profile/llamahat.bsky.social BlueSky Github Supervisors: Themes Design & Development Immersive Technology Player Research Previous Next

< Back Dr Yongxin Yang Queen Mary University of London Supervisor Dr Yongxin Yang is a lecturer in financial technology at Queen Mary University of London, UK and he is also a part-time professor in finance at Southwestern University of Finance and Economics, China. His research is in the area of meta learning and its interactions with other machine learning paradigms like reinforcement learning. He has broad interests in applied machine learning, esp. for finance problems, for example, portfolio optimization and financial derivatives pricing. For the project of meta reinforcement learning, we want to explore the learning algorithms that can transfer an existing RL agent into a new task (e.g., a new game episode) with the minimal effort on retraining it. For the project of AI Economist, we are going to create a multi-agent system, where each agent behaves like a human being who will interacts with the environment and other agents (e.g., produce and trade), then we study how a certain policy (e.g., monetary and tax) affects the economy. yongxin.yang@qmul.ac.uk Email Mastodon https://yang.ac/ Other links Website LinkedIn BlueSky https://github.com/wOOL/ Github Themes Applied Games Game AI Game Data - Previous Next

< Back Prof. Sebastian Deterding iGGi Responsible Innovation Lead Supervisor Sebastian Deterding is a designer-researcher working on playful, gameful, motivational, and eudaimonic design. His work asks how we might re-design the socio-technical rule systems we live in to enable a good life for all. He is founder of the Gamification Research Network, and co-editor of The Gameful World (MIT Press, 2015). An internationally recognised leader of gamification research, he is frequently invited to keynote and speak at venues like Lift, Interaction, GDC, Games Learning Society, Google, IDEO, and MIT, and his work has been covered by The Guardian, The New Scientist, the Los Angeles Times, arte, and EDGE Magazine among others. As a senior research fellow at the Digital Creativity Labs, Sebastian works on the intersection of AI, machine learning, and design for augmented creativity: how can we create systems that learn to automatically adapt and serve optimally engaging content to users, and serve optimally supportive design suggestions and tutorials to creators? He is particularly interested in supervising students with a design, HCI, or behavioural sciences background on the following topics: understanding and designing for uncertainty, curiosity, and epistemic emotions in games applied games for decarbonisation and climate adaptation design for behaviour change Self-determination theory and games Research themes: Game Design Games with a Purpose Computational Creativity Player Experience Gamification sebastian.deterding@york.ac.uk Email Mastodon https://codingconduct.cc Other links Website LinkedIn BlueSky Github Themes Applied Games Creative Computing Design & Development Player Research - Previous Next

< Back Dr Jeremy Gow Queen Mary University of London iGGi Training Coordinator Supervisor Jeremy Gow is a game AI researcher with a focus on computational game design, exploring ways in which AI can help us understand players and games, enhance the game development process, and contribute to the creation of game content. He has been a lecturer at EECS and a member of the Queen Mary Game AI group since 2018. He has a background in artificial intelligence and human-computer interaction research, and a PhD in AI from the University of Edinburgh. He is particularly interested in supervising students with a game development or AI background on the following topics: Automated playtesting and QA AI-based game development tools Modelling player experience AI for the design of agents and procedural generators Computational creativity in games Research themes: Game AI Game Analytics Game Design Computational Creativity jeremy.gow@qmul.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Creative Computing Design & Development Game AI Game Data - 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