Raluca D. Gaina is studying for her Ph.D. in Intelligent Games and Games Intelligence at Queen Mary University of London, in the area of rolling horizon evolution in general video game playing. She completed an internship at Microsoft Research Cambridge in 2018, working on the Multi-Agent Reinforcement Learning in Malmo (MARLO) Competition. Previously, she obtained a B.Sc. and M.Sc. in Computer Games at the University of Essex, in 2015 and 2016, respectively. She finished her first year of Ph.D. at the University of Essex (transfer to Queen Mary) with numerous conference papers and a journal publication. Her research interests include general video game playing AI, reinforcement learning and evolutionary computation algorithms.
Jen is in her third year of the IGGI PhD studying players with disabilities experiences in digital games. When she isn’t at her desk studying or gaming she enjoys long walks by the river, reading, drawing, and playing tabletop RPGs.
Cris is a Spaniard in love with London, where she's been living since 2013. She studied a BE in Computer and Software Engineering at Universidad Autonoma de Madrid (Spain) and worked as a web developer for a couple of years. She took the decision of changing to the world of AI and games and she is one of the IGGI students based in Queen Mary University of London. She tries to keep active outside the sedentary PhD live, mostly walking around the city, cycling and attempting different sports like football and bouldering.
Born in Porto (Portugal) and living in London (UK). I am currently a PhD student in Intelligent Games and Games Intelligence at Queen Mary University of London, with a finished BSc in Computer Games at the University of Essex. Developed a passion for the games industry ever since one of the very first Game Boy Color handheld consoles was placed in my hands and I have spent countless hours playing games since. I am currently researching character believability and how to access it given my curiosity for creating non-player characters with more diverse and adapted personalities that are close to how we, people, play in games. It is my belief that more human-like NPCs would be beneficial if implemented in the right kind of games and enhance the players’ experience. Doing this in a “general” way would also allow this concept to be applied to more than one specific game.
Ivan Bravi has obtained his B.Sc and M.Sc in Engineering of Computer Systems at the Polytechnic University of Milan, Italy. In 2016 he was Visiting Scholar at the NYU’s Game Innovation Lab in New York where, under the supervision of Prof. Julian Togelius, he did research in the field of general videogame playing. Since September 2017 he is an IGGI PhD student at the Queen Mary University of London under the supervision of Prof. Simon Lucas. He has published several academic papers on AI and games. His academic interests are mainly on Artificial Intelligence specifically in Evolutionary Algorithms and Heuristic Tree Search applied to general videogame playing. He's also interested in understanding and analysing game-playing AI behaviors.
Born and raised on the sunny Isle of Wight Charlie recently graduated from Goldsmiths with a BSc Computer Science. Prior coming to Goldsmiths he worked for several years in the video games industry. His research lies at the intersection of affective computing and machine learning with the intelligent design of games, and, in particular, procedurally generated and player adaptive game content. In essence, the main aim of his research is to develop suitable techniques for assessing the player's emotional state by utilising various sources of information, such as e.g., the facial expressions, gestures and non-verbal cues of the player along with the actual game footage (pixel values), and explore ways developers can use these models in automated content systems.
Cristina Dobre has a background in Mathematics and Computing receiving distinction in her undergraduate degree in Computer Science. She was engaged in an exciting work as part of the final year project. It involved data gathering and analysation using Natural Language Processing and Machine Learning techniques to examine the problem of duplicate questions in community-based QA platforms. During her studies, she had various part-time and temporary jobs, including developing software, teaching kids creative coding, MOOC mentoring and editing motion capture data and 3D animations.
I did my undergraduate masters degree at Oxford University, in computer science. During this degree I did two projects relating to the implementation of AI for games, creating agents to play both Go and Starcraft: Brood War. Since graduating in 2015 I have spent the best part of the last 2 years as a software engineer in Bristol at a software consultancy, and a product-based start-up. I’m looking forward to returning to academia and trying my hand at game development.
Diego Perez Liebana is a lecturer in Computer Games and Artificial Intelligence at Queen Mary University of London (QMUL). He achieved a PhD in Computer Science at the University of Essex (2015) on the use of adaptive controllers for real-time games. He has published in Game AI, with interests on Reinforcement Learning, Tree Search and Evolutionary Computation. He organizes several Game AI competitions, such as the General Video Game AI and Multi-Agent Reinforcement Learning in MalmO (MARLO). He has programming experience in the video games industry with titles published for game consoles and PC, and teaches Game Development, AI for Games and AI-assisted Game Design at QMUL.