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A Word from The iGGi Director 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. A Word from the Director Welcome to iGGi! Below are a few words about the vision for iGGi, about who funds iGGi and why, and about why i GGi can be a force for good in a sometimes turbulent world. iGGi is short for the “EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence” (EPSRC is short for “Engineering and Physical Sciences Research Council”). You can see why the name iGGi stuck! In , 120 PhD students spend 4 years learning cool stuff and conducting research in topics related to games and the games industry, working with 100 UK games companies . The big vision for iGGi is to inject research innovations and innovative researchers into the games industry. There is a strong economic argument for this, and there are even stronger social and cultural reasons. So where did iGGi come from and what is the vision that allowed us to win £30 million for games research? In the early 2000s, the games research community went through a huge growth spurt (which continues to this day). The economic, social and cultural power of video games meant that politicians and funders could no longer brush games aside as kid’s stuff. An opportunity arose in 2013 with the announcement of a competition for funding around 100 centres for PhD research in a focussed area of science or engineering. While it was clear that the call would be massively oversubscribed and very competitive, games seemed a good fit given the rise and rise of the financial size of the games market and the growing research community. We had more and more friends and contacts in the games industry. And we had shown that games could be funded at scale via projects such as UCT (£1.5 million) and NEMOG (1.2 million). A group of people from across academia and industry, with an interest in games research, came together to submit a bid and form a consortium. Our joint goal was to “make better games” and “make games better”. My role in this (as ‘Principal Investigator’) was as a synthesiser of ideas, as a recruiter of people who shared and refined these ideas, and as a writer and lobbyist who could package them up for referees who almost certainly lacked enthusiasm for games research. So how can we summarise the iGGi vision? The ‘IG’ in iGGi stands for ‘Intelligent Games’ - using research advances to make better games that provide richer, more fun experiences. The ‘GI’ in iGGi stands for ‘Game Intelligence’ - research which uses games to understand and inform people. In more detail: the following two paragraphs, from the 2013 iGGi bid, were probably among the most carefully written of the text in the whole bid document (redrafted dozens of times): Our vision is twofold: Intelligent Games: iGGi PhDs, investigators and collaborators will use research advances to seed the creation of a new generation of more intelligent and engaging digital games, to underpin the distinctiveness and growth of the UK games industry. We will weave technical and creative disciplines: using games as an application area to advance research in areas including artificial intelligence and computational creativity; human-computer interaction; interactive sound, graphics and narrative; robotics, agents and complex systems. The study of intelligent games will be underpinned by new business models and by research advances in data mining (game analytics) which can exploit vast volumes of gameplay data. Game Intelligence: iGGi PhDs, investigators and collaborators will investigate games as a medium to achieve scientific and societal goals, working with user groups and the games industry to produce new genres of games which can yield therapeutic, educational and social benefits and using games to seed a new era of scientific experimentation into human preference and interaction. We will create new games to conduct large-scale analysis of individual behaviour, leading to better understanding in economics, psychology, sociology, biology and human-computer interaction. We will build games which promote physical and mental health and educational achievement, underpinned by advances in mobile technology and data mining. This vision was refined and updated for the 2018 iGGi resubmission, especially given the enormous advances in machine learning and the cultural and social successes of games, but the text above remains a good overview of the high-level iGGi vision. But a vision is relatively static, and now, of course, iGGi is a community of brilliant, fun, caring, intelligent, curious research students, supported by staff and industry partners. So maybe the best way to find out more about iGGi is to read more about a few of them… I look forward to talking about games research with you! Peter Cowling iGGi Director Professor of AI, Queen Mary University of London

< Back Prof. David Beer University of York Supervisor Professor Beer has been researching new and digital media since completing his PhD in 2006. This has included work on social media, mobile devices and algorithms. Over the last decade he has developed work exploring the social implications of data and metrics. His work has explored how automated decision making is impacting upon social connections and has looked at how the data that accumulates about us shaped the way individuals are understood and judged. He has recently conducted a study of the data analytics industry and produced a report into online targeting. His research areas for supervision include: The social power of algorithms Data analytics The power of data and metrics Critical analyses of data visualization The metricisation of everyday life Social media and social media data Online targeting Data harvesting and inequality Research themes: Game AI Game Analytics Game Design Games with a Purpose Computational Creativity Gaming data Algorithms in gaming Gamification and the social world david.beer@york.ac.uk Email Mastodon https://davidbeer.net/ Other links Website LinkedIn BlueSky Github Themes Applied Games Creative Computing Game AI Game Data Player Research - Previous Next

< Back Dr Tony Stockman Queen Mary University of London Supervisor Dr Stockman is an interaction designer/researcher who investigates how technology can enhance accessibility and improve human performance. He is particularly interested in technology to support spatial cognition and wayfinding, health monitoring and improve performance levels in sport and music. This includes the role of games in simulating these domains and supporting skill acquisition and enhanced performance. He is a Board member and former president of the International Community for Auditory Display ( www.icad.org ). He has organised 6 international workshops on a range of HCI topics, and has been on the organising committee of 10 international HCI-related conferences. Topics on which he has recently published include participatory design and prototyping, auditory overviews for route guidance, self monitoring of biological signals and accessible collaborative working. He is particularly interested in supervising students with a Computer Science, Electrical Engineering, HCI, or behavioural sciences background on the following topics: Simulation to support accessibility and skill acquisition in team sports Intelligent audio mostly games to support learning Intelligent Audio or audio-haptic approaches to health monitoring and biofeedback Intelligent systems to support individual or collaborative music making Research themes: Intelligent simulation systems Interaction design for simulated sports Game Audio and Music Game Design Games with a Purpose t.stockman@qmul.ac.uk Email Mastodon Other links Website LinkedIn BlueSky Github Themes Applied Games Design & Development Esports Game AI Game Audio Player Research - Previous Next

< Back Dr Siamak Shahandashti University of York Supervisor Dr Siamak Shahandashti is a Lecturer (Assistant Professor) in Cyber Security Siamak has extensive experience in designing cryptographic solutions to enhance security and privacy for applications such as electronic voting, auctions, and biometric authentication systems. He has also worked on the security and privacy of password managers, IoT devices, mobile phone sensors, contactless payment, and paper fingerprinting. Siamak is interested in designing systems for improving security and privacy that are easy to use and accessible. He is working on designing usable password strength meters and human verifiable cryptographic codes. Siamak is a core member of the York Interdisciplinary Centre for Cyber Security and an expert fellow of the UK Network on Security, Privacy, Identity, and Trust in the Digital Economy (SPRITE+) He is a co-inventor on multiple patents including the first verifiable e-voting system trialled in the UK (patents US15582447, GB1607597) and paper fingerprinting (patent US15972922) with applications in banknote security. He led the design of the broadcast encryption deployed in millions of Thales’s Pay TV products worldwide. Siamak was part of teams who found vulnerabilities and fixed several systems, including the ISO/IEC11770-4 standard for password-based key exchange used in billions of devices, major mobile browser (Chrome, Firefox, Opera, Safari) sensor access policies, and Bitcoin's Payment Protocol used by 100k+ merchants. He is particularly interested in supervising students on the following topics: Using gamification to improve security and privacy in applications such as authentication and human verification Investigating and improving security and privacy in game environments Research themes: Gamification Games with a Purpose Game Security Game Privacy Game Analytics siamak.shahandashti@york.ac.uk Email Mastodon https://www.cs.york.ac.uk/~siamak Other links Website https://au.linkedin.com/in/siamakfs LinkedIn BlueSky Github Themes Applied Games - Previous Next

< 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

< Back Dr Athen Ma Queen Mary University of London Supervisor Athen Ma is an innovator in interdisciplinary approaches to the study of communities and networked ecosystems. She is particularly interested in finding out how the structure and dynamics of communities evolve over time and what kind of mechanics that help underpin cohesion in communities. Her research has been published in world-leading journals, with recent works revealing the organisation of collaborative science in the UK (in PNAS highlight), uncovering how ecological networks rewire under drought (front cover of Nature Climate Change ), and how agricultural ecosystems are resilient to changes in farming management (in Nature Ecology and Evolution ). Online multiplayer games naturally form a platform for social relationships to develop, and deciphering the social structure and dynamics of the communities formed will provide insights into many aspects in games, ranging from users engagement and retention to team formation. For example, matchmaking enables users to find other players who share similar profiles, interests as well as skills and personality; has been seen as an important tool for establishing and maintaining a thriving gaming community. Athen is keen to explore novel ways to use advances in social network analysis to investigate player communities in games across multiple network scales, so as to better understand their formation and evolution. Findings from this research will help identify/predict the type of social interactions that will promote the level of engagement among players and community cohesion, paving the way for designing in-game activities that will foster long-time engagement and retention. athen.ma@qmul.ac.uk Email Mastodon https://sites.google.com/site/athenma2015/ Other links Website LinkedIn BlueSky Github Themes Game Data Player Research - 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 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 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 Dr Zoe Handley University of York Supervisor Zoe Handley is a Senior Lecturer (Associate Professor) in Language Education. She is an interdisciplinary researcher, with a background in language technology, who recognizes the value of quantitative as well as qualitative work in this area. Her earlier work focused on the evaluation of speech synthesis for use in language learning and teaching. Since then she has carried out a systematic review of evidence for the use of technology to support English language learning in primary and secondary schools and supervised a number of theses evaluating applications of technology for language learning. These have typically explored the use of web 2.0 and Computer-Mediated Communication (CMC) technologies. Further to this she is interested in how learners autonomously use technology to support their learning in contexts such as study abroad. Zoe is currently particularly interested in teacher thinking in relation to the integration of technology to support language learning and developing and evaluating training to support teachers in making decisions about what technologies to integrate into their teaching, for what purposes and how. Zoe welcomes applications from PhD students interested in designing and evaluating educational activities that harness the affordances of digital technologies to create conditions and engage learners in processes that are known to support language learning. zoe.handley@york.ac.uk Email https://sites.google.com/york.ac.uk/pivotal-group/about Mastodon https://www.york.ac.uk/education/our-staff/academic/zhandley/ Other links Website https://www.linkedin.com/in/zoe-handley-a730b58/ LinkedIn BlueSky Github Themes - Previous Next

< Back Dr Adrian Bors University of York Supervisor Adrian G. Bors is an Associate Professor at the University of York and has published more than 150 papers in international journals and conferences in the areas of his research interests. He is interested in supervising projects related to the application of novel artificial intelligence methods and computer vision in Game AI. One of the areas of interest is in the modelling of game characters (intelligent agent) continuously learning from their environments, able to transfer their knowledge from one stage to the next, while accumulating the information, like human/animal beings and enabling to continuously adapt to their environments. Another topic of interest is represented by conditional image and video generation for developing game environments. The conditional video/image generation will depend on certain factors that can be pre-established or be the result of self-learning by an (intelligent agent). Most existing games relying on no movement representation lack in representing realistic and continuous movement. In this direction of research, we will aim to generated video which would be consistent with realistic movement of game characters. Specific attention will be paid to modelling the interaction of the generated movement with the environment or other actors (game characters). In another direction of research, Adrian G. Bors will supervise projects in digital watermarking of 3D graphical characters. Codes will be invisible embedded and retrieved from the 3D graphics representations. The code embedded, like the DNA in human/animals, will enable the character to act in specific ways, defining behavioural traits in similarly looking graphics characters. adrian.bors@york.ac.uk Email https://www.researchgate.net/profile/Adrian-Bors Mastodon https://www-users.cs.york.ac.uk/adrian/ Other links Website https://www.linkedin.com/in/adrian-bors-32a3668/ LinkedIn BlueSky https://github.com/AdrianBors Github Themes Game AI - Previous Next

< Back Dr Pengcheng Liu Queen Mary University of London Supervisor Dr Pengcheng Liu is a Lecturer (Assistant Professor) at the Department of Computer Science, University of York, UK. He is an internationally leading expert in robotics, Artificial Intelligence and human-machine interaction. He has been leading and involving in several research projects, including EPSRC, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, HEIF, NHS I4I, NSFC, etc. Several of his research works were published on top-tier journals and leading conferences in the fields of robotics and AI. Before joining York, he has held several academic positions including a Senior Lecturer at Cardiff School of Technologies, Cardiff Metropolitan University, UK, a joint Research Fellowship at Lincoln Centre for Autonomous Systems (LCAS) and Lincoln Institute of Agri-Food Technology (LIAT), University of Lincoln, UK, a Research Assistant and a Teaching Assistant at Bournemouth University, UK. I also held academic positions as a Visiting Fellow at Institute of Automation, Chinese Academy of Sciences, China and Shanghai Jiao Tong University, China. Dr Liu is a Member of IEEE, IEEE Robotics and Automation Society (RAS), IEEE Systems, Man and Cybernetics Society (SMC), IEEE Control Systems Society (CSS) and IFAC. He is member of IEEE Technical Committees (TC) on Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. He has published over 60 journal and conference papers. Dr Liu serves as an Associate Editor for IEEE Access and PeerJ Computer Science. He received the Global Peer Review Awards from Web of Science in 2019, and the Outstanding Contribution Awards from Elsevier in 2017. He was selected as regular Fundings/Grants reviewer for EPSRC, NIHR and NSFC. Dr Liu’s research interest relevant to CDT IGGI include applied games for healthcare and rehabilitation applications, as well as using mixed reality and machine learning for human-machine interactions. He is particularly interested in supervising students with a design, HCI, computer science or behavioural sciences background on the following topics: applied games for healthcare and rehabilitation design for adaptive mixed reality system for physical therapy and neurological rehabilitation design for physical and cognitive behaviour change learning for human intention prediction analysis of mixed reality rehabilitation system with biological signals (EEG, sEMG) pengcheng.liu@york.ac.uk Email Mastodon https://sites.google.com/view/pliu Other links Website https://www.linkedin.com/in/pengcheng-liu-12703288/ LinkedIn BlueSky Github Themes Applied Games Game AI Immersive Technology - Previous Next