Alessandro Vinciarelli (Director, Member of the Supervisors Team)
Alessandro (http://www.vinciarelli.net) is Full Professor at the School of Computing Science and Associate Academic at the Institute of Neuroscience and Psychology. His main research interest is Social Signal Processing, the computing domain aimed at modelling, analysis and synthesis of nonverbal behaviour in human-human and human-machine interactions. Alessandro develops approaches that detect nonverbal behavioural cues (facial expressions, vocalisations, gestures, etc.) in data collected with multiple sensors and then apply Artificial Intelligence methodologies for making sense of the cues in terms of social and psychological phenomena (e.g., personality, conflict, cognitive and mental issues, etc.). He has published more than 150 works that have attracted several thousands of Scholar citations (https://scholar.google.co.uk/citations?hl=en&user=XOnfkHIAAAAJ). Besides being the Director of the UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents, Alessandro is or has been Principal and co-Investigator of more than 15 national and international research projects, including a European Network of Excellence of which he has been the coordinator (the SSPNet, 2009-2014), a H2020 funded project (MuMMER, 2016-2020), and the EPSRC funded School Attachment Monitor (2015-2019) and Socially Competent Robots (2016-2020). In addition, he has been General Chair of more than 25 international events, including the IEEE International Conference on Social Computing (2012) and the ACM International Conference on Multimodal Interactions (2017). Last, but not least, Alessandro has an established record of collaboration with industrial partners. In particular, he is Scientific Advisor of Neurodata Lab (http://www.neurodatalab.com) and co-founder of Klewel (http://www.klewel.com), a knowledge management company featured as an exemplary impact story by IEEE Multimedia (https://ieeexplore.ieee.org/document/7331162).
Monika Harvey (Co-Director, Member of the Supervisors Team)
Monika Harvey is a Reader at the School of Psychology at the University of Glasgow. Prior to joining Glasgow, she was a Senior Lecturer at the University of Bristol, having obtained a degree in Psychology from the University of Bielefeld (Germany), followed by a PhD in Visual Neuropsychology from St. Andrews University (UK). Her research interests fall in the area of cognitive neuroscience, especially in the relative contribution of the two main cortical visual streams (dorsal and ventral) towards perception and action. Beyond its relevance to informing brain function and the idea that visual processing is split into two separate but interrelated systems, her work has health applications in particular in relation to stroke rehabilitation. In addition, her research speaks to and informs ease and constraints in our interactions with socially intelligent artificial agents. Dr Harvey has previous experience in managing Doctoral Training Centres, holding a position as Associate Director in the Scotland wide ESRC funded Scottish Graduate School of Social Sciences (SGSSS) Doctoral Training Partnership (DTP) (now a partner of SOCIAL).
Stacy Marsella (Co-Director, Member of the Supervisors Team)
Stacy Marsella is a Professor in the Institute of Neuroscience and Psychology and director of the Centre for Social, Cognitive and Affective Neuroscience. Prior to joining the University of Glasgow, he was a professor at Northeastern University in the College of Computer and Information Science with a joint appointment in Psychology and, prior to Northeastern, a research professor in the Department of Computer Science at the University of Southern California and a research director at the Institute for Creative Technologies (ICT). Professor Marsella’s multidisciplinary research is grounded in the computational modeling of human cognition, emotion and social behavior as well as the evaluation of those models. Beyond its relevance to understanding human behavior, the work has seen numerous applications, including health interventions, social skills training and large-scale social simulations of disaster response. This more applied work has been facilitated by his team’s development of frameworks for large-scale social simulations as well as techniques and tools for creating virtual humans, facsimiles of people that can engage people in face-to-face social interactions. Professor Marsella received an ACM SIGART career award for his contributions to agent research and a Royal Society Wolfson Research Merit Award. He served on the board of the International Foundation for Autonomous Agents and Multiagent Systems and is on the steering committee for Intelligent Virtual Agents. He is a fellow of the Society of Experimental Social Psychologists, a member of the Association for the Advancement of Artificial Intelligence and a member of the International Society for Research on Emotions.
Dale Barr (Member of the Supervisors Team)
Dale Barr is a Senior Lecturer in the Institute for Neuroscience and Psychology. His main areas of interest are psycholinguistics, statistical methodology, and cognitive science. Most of his work consists of empirical investigations into the cognitive representations and processes underlying spoken dialogue. He has published work on various topics, including pragmatics, perspective-taking, lexical processing, cultural evolution, speech rhythm, disfluency, and multimodal signaling. Much of his recent work has focused on how language users manage to integrate linguistic and situational information (such as interlocutors’ beliefs and goals) within the constraints of real-time dialogue. His work uses a variety of methodologies, from behavioral and neuroimaging techniques such as visual-world eyetracking, EEG, and MEG, to computational modeling and Monte Carlo simulation. He has also contributed to statistical methodology, developing techniques for time-series analysis of visual-world eyetracking data, and developing insights into statistical methodologies though Monte Carlo simulation. In his teaching, he has worked to develop a curriculum promoting reproducible data analysis, and has developed software applications to make statistics teaching more effective. He has been Associate Editor of the journal Behavior Research Methods since 2014.
Lawrence Barsalou (Member of the Supervisors Team)
Lawrence Barsalou is Professor of Psychology at the University of Glasgow, performing research in the Institute of Neuroscience and Psychology. He received a Bachelors degree in Psychology from the University of California, San Diego in 1977 (George Mandler, advisor), and a Ph.D. in Cognitive Psychology from Stanford University in 1981 (Gordon Bower, advisor). Since then, Barsalou has held faculty positions at Emory University, the Georgia Institute of Technology, and the University of Chicago, joining the University of Glasgow in 2015. Barsalou’s research addresses the nature of human conceptual processing and its roles in perception, memory, language, thought, social interaction, and health cognition. A current theme of his research is that the conceptual system is grounded in multimodal simulation, situated conceptualization, and embodiment. Specific topics of current interest include the roles of conceptual processing in emotion, stress, abstract thought, self, appetitive behavior, and contemplative practices. His research also addresses the dynamic online construction of conceptual representations, the development of conceptual systems to support goal achievement, and the structure of knowledge. Barsalou’s research has been funded by the US National Science Foundation and other US funding agencies. He has held a Guggenheim fellowship, served as the chair of the Cognitive Science Society, and won an award for graduate teaching from the University of Chicago. Barsalou is a Fellow of the American Association for the Advancement of Science, the American Psychological Association, the Association for Psychological Science, the Cognitive Science Society, the Mind and Life Institute, and the Society of Experimental Psychologists. He is a winner of the Distinguished Cognitive Science Award from the University of California, Merced.
Stephen Brewster (Member of the Supervisors Team)
Stephen Brewster, FRSE, is Professor of Human Computer Interaction in the School of Computing Science (http://mig.dcs.gla.ac.uk). He leads the Multimodal Interaction Group, part of the Glasgow Interactive Systems Group. His research focuses on multimodal HCI, or using multiple sensory modalities and control mechanisms (particularly audio, haptics and gesture) to create a rich interaction between human and technology. His work has a strong experimental focus, applying perceptual research to practical situations. His main research topics include interaction with mobile devices; physical and mental health applications; multimodal emotional engagement; accessibility; wearable devices and in-car interaction. He holds an ERC Advanced Grant in the area of AR and VR in autonomous vehicles. He is a Member of the ACM SIGCHI Academy and an ACM Distinguished Speaker.
Matthew Chalmers (Member of the Supervisors Team)
Matthew Chalmers is a professor in the School of Computing Science at the University of Glasgow, UK. His work focuses on data visualisation and analytics, data ethics and ethical systems design, and mobile and ubiquitous computing. He borrows from philosophy, biology and other disciplines in order to feed into the design and theory of such systems. His background is in Computer Science: a BSc (Hons) at U. Edinburgh, then a PhD at U. East Anglia in ray tracing and object-oriented toolkits for distributed memory multiprocessors. He was a researcher in Xerox’ labs, before setting up an information visualisation group at UBS Ubilab, in Zurich. He then had a brief fellowship at U. Hokkaido, Japan, before starting at U. Glasgow in 1999. His (other) current projects include an EPSRC NetworkPlus on ethical systems design (Human Data Interaction, https://hdi-network.org), an ONR project on fast data visualisation, and a university-funded pilot project on ethically tracking mental health via phone sensor data. His own web site is at http://www.matthewchalmers.net.
Emily Cross (Member of the Supervisors Team)
Emily is a Professor of Social Robotics and social neuroscientist based at the Institute of Neuroscience and Psychology at the University of Glasgow, where she directs the Social Brain in Action Laboratory. Using intensive training procedures, functional neuroimaging, brain stimulation, and research paradigms involving dance, acrobatics and robots, she leads a team who explores questions concerning how we learn via observation, motor expertise, and social influences on human-robot interaction. She and her team are particularly interested in how prolonged experience with robots changes how we perceive and interact with these artificial agents at brain and behavioural levels, and how these relationships are manifest across the lifespan and in different cultures. These are the primary questions she and her team are exploring as part of the ‘Social Robots’ project, an ERC starting grant for which Emily serves as PI. Emily received a BA in psychology and dance from Pomona College (USA), an MSc in cognitive psychology from the University of Otago (NZ) as a Fulbright Fellow, and a PhD in cognitive neuroscience from Dartmouth College (USA). She completed postdoctoral training at the University of Nottingham (UK) and the Max Planck Institute for Human Cognitive and Brain Sciences (Germany), and was previously an assistant professor at Radboud University Nijmegen (NL) and a professor at Bangor University (Wales). Her research has been funded by an eclectic mix of national and international organisations, including the NIH (USA), the Netherlands Organisation for Scientific Research, the Economic and Social Research Council (UK), the Ministry of Defence (UK), the Leverhulme Trust (UK) and the European Research Council.
Ravinder Dahiya (Member of the Supervisors Team)
Ravinder Dahiya (www.rsdahiya.com) is Professor of Electronics and Nanoengineering and Engineering and Physical Sciences Research Council (EPSRC) Fellow in the School of Engineering at University of Glasgow. He is the Director of Electronic Systems Design Centre (ESDC) and the leader of Bendable Electronics and Sensing Technologies (BEST) group. His group conducts fundamental research on high-mobility materials based flexible electronics and electronic skin, and their application in robotics, prosthetics and wearable systems. Prof. Dahiya has published more than 250 research articles, 4 books, and 12 patents filed/granted. He has given more than 120 invited/plenary talks. He has led many international projects (> £20M) funded by European Commission, EPSRC, The Royal Society, The Royal Academy of Engineering, and The Scottish Funding Council. He is Distinguished Lecturer of IEEE Sensors Council and is on the Editorial Boards of Scientific Reports (Nature Group), and IEEE Sensors Journal. He is also the editor of Cambridge Elements on Flexible and Large Area Electronics. He was the Technical Program Co-Chair (TPC) for IEEE Sensors Conference in 2017 and 2018. He is the General Chair of 2019 IEEE International Conference on Flexible and Printable Sensors and Systems (IEEE FLEPS) and IEEE ICECS 2019. Prof. Dahiya holds EPSRC Fellowship and in past he received Marie Curie Fellowship and Japanese Monbusho Fellowship. He has received several awards and most recent among them are: 2018 Elektra award for best university research in the UK, 2016 IEEE Sensor Council Technical Achievement Award, the 2016 Microelectronic Engineering Young Investigator Award (Elsevier) and 2016 Scottish 40UNDER40.
Jeff Dalton (Member of the Supervisors Team)
Dr. Jeff Dalton is Lecturer in the School of Computing Science at the University of Glasgow. He conducts research on search-oriented conversational AI and knowledge-aware information retrieval. His research is at the intersection of natural language processing and search, in particular automatic methods to construct knowledge graphs and their application in retrieval. Specialized application domains include: health and biomedical, travel and food, digital heritage, science and engineering, and history. He completed his PhD at the University of Massachusetts Amherst with James Allan in the Center for Intelligent Information Retrieval. Before Glasgow, he worked in Google Research on the Knowledge Discovery (Knowledge Vault), Pasteur Health Research, and the Google Assistant Response Ranking team in the Assistant Natural Language Understanding group. He organizes the Search-oriented Conversational AI workshop series. He is the lead organizer for the TREC Conversational Assistance Track (CAsT) (http://treccast.ai) and previously organized the TREC Complex Answer Retrieval track. His research on conversational search systems is funded by a Google Faculty Research Award, 2018.
Lisa DeBruine (Member of the Supervisors Team)
Lisa DeBruine runs the Face Research Lab and the KINSHIP project, a 5-year, €2M ERC Consolidator Grant to study “How do humans recognise kin?” Her empirical research focuses on kinship and how social perception of morphology affects social behaviour. Specifically, she is interested in how humans use facial resemblance to tell who their kin are and how people respond to cues of kinship in different circumstances. She is also interested in meta-science topics such as teaching computational skills for reproducible research, large-scale collaboration (especially the Psychological Science Accelerator), and developing web-based resources for increasing reproducibility in data collection and stimulus generation.
Mary Ellen Foster (Member of the Supervisors Team)
Dr Mary Ellen Foster (http://maryellenfoster.uk/) is a Senior Lecturer in the School of Computing Science, and an Associate Academic of the Institute for Neuroscience and Psychology. Her main research goal is to build, deploy, and evaluate artificial characters—mainly robots—that people can interact with using natural, face-to-face conversation. Within this space, her primary research interests include human-robot interaction, social robotics, embodied conversational agents, conversational interaction, and natural language generation. She is the coordinator of the MuMMER project, a European Horizon 2020 project in the area of socially aware human-robot interaction. She obtained her PhD from the University of Edinburgh in 2007, and has previously worked at the Technical University of Munich and Heriot-Watt University.
Rachael Jack (Member of the Supervisors Team)
Rachael Jack is a Reader (Associate Prof) at the Institute of Neuroscience & Psychology, University of Glasgow. Her research has produced significant advances in understanding facial expression of emotion within and across cultures using a novel interdisciplinary approach that combines psychophysics, social psychology, dynamic 3D computer graphics, and mathematical psychology. Most notably, she has revealed cultural specificities in facial expressions of emotion; that four, not six, expressive patterns are common across cultures; and that facial expressions transmit information in a hierarchical structure over time. Together, Jack’s work has challenged the dominant view that six basic facial expressions of emotion are universal, which has led to a new theoretical framework of facial expression communication that she is now transferring to digital agents to synthesize culturally sensitive social avatars and robots. Jack’s work has featured in several high-profile scientific outlets (e.g., Annual Review of Psychology, Current Biology, Psychological Science, PNAS, TICS). She is currently funded by the European Research Council (ERC) to lead the research program Computing the Face Syntax of Social Face Signals, which will deliver a formal model of human social face signalling with transference to social robotics. Jack is recipient of the American Psychological Association (APA) New Investigator award, the Social and Affective Neuroscience Society (SANS) Innovation award, and the British Psychological Society (BPS) Spearman Medal. She is also Associate Editor at Journal of Experimental Psychology: General and Journal of Experimental Social Psychology and committee member for the conferences of the Society for Affective Sciences (SAS), IEEE Automatic Face & Gesture Recognition, and the Vision Science Society (VSS).
Ben Jones (Member of the Supervisors Team)
I study the effects of facial and vocal cues on perceptions and behaviours. I am particularly interested in how these cues influence attractiveness, trustworthiness and dominance. I am currently leading the first study by the Psychological Science Accelerator, a distributed network of 400 labs from across the world who conduct democratically selected studies. This project investigates possible cultural differences in social judgments of faces. My previous research has been funded by the ERC and ESRC.
Alice Miller (Member of the Supervisors Team)
Dr Alice Miller is a Senior lecturer who has supervised 14 PhD students since 2007. She has expertise in formal verification, notably the detection and exploitation of symmetry for model checking, and combinatorial search. Her formal verification research includes probabilistic modelling for UAV strategy generation and using abstraction and embedded C code to model a biologically inspired reinforcement learning algorithm. Earlier work in this area includes model checking techniques for concurrent software, induction and abstraction, and symmetry reduced model checking for non- probabilistic and probabilistic systems. Recent research in combinatorial search includes proving optimality results for problems in graph theory using symmetry breaking and Boolean Satisfiability solving.
Lars Muckli (Member of the Supervisors Team)
Lars Muckli is Professor of Visual and Cognitive Neurosciences, and Director of fMRI at the Centre for Cognitive Neuroimaging (CCNI), in Glasgow and Co-chair of 7T-Imaging Center of Excellence (ICE) MRI. He has worked for 20 years in the field of fMRI and multi-modal brain imaging. His work focuses on brain imaging of cortical feedback, investigation of layer specific fMRI, and multi-level cross –species computational neuroscience. His lab was previously funded by ERC consolidator grant on ‘Brain reading of contextual feedback and predictions’. Since 2016, Lars is member of the Human Brain Project (HBP), leading a work package on rodent and human neuroscience on ‘Context-sensitive multisensory object recognition a deep network model constrained by multi-level, multi-species data’. Lars is now member of the HBP board as co-lead for System & Cognition Neuroscience. The Human Brain Project (https://www.humanbrainproject.eu/en/) is one of the two largest scientific projects ever funded by the European Union (€500 million), and creates a research infrastructure for Neuroinformatics, Brain Simulation, High Performance Analytics and Computing, Medical Informatics, Neuromorphic Computing and Neurorobotics.
Gethin Norman (Member of the Supervisors Team)
Gethin Norman is a Senior Lecturer in Computing Science at the University of Glasgow and previously a senior post-doctoral researcher at the University of Oxford. A focus of his research is the theoretical underpinning of quantitative formal methods, particularly for systems exhibiting probabilistic and real-time behaviour, and he has published over 100 papers in this area. He is a key contributor to the probabilistic verification tool PRISM – the most widely-used software tool for verification of probabilistic systems. He has developed many of PRISM’s modelling case studies across a wide range of application domains, finding several faults and anomalies. These included a number of real-world protocols and were taken from a wide range of application domains including autonomous systems, communication and multimedia protocols, power management systems, reliability models and security. Probabilistic verification provide a means of producing quantitative guarantees on the correctness of a system (e.g. “the control software can always safely stop the vehicle with probability at least 0.99, regardless of the actions of other road users”), where the required behavioural properties are specified precisely in quantitative extensions of temporal logic. It also adresses the closely related problem of strategy synthesis constructing an optimal strategy that guarantees a property is satisfied. His recent work has focused on stochastic game-models which arise when modelling autonomous systems, due to the presence of both competitive and collaborative behaviour and uncertainty in the environment.
Esther Papies (Member of the Supervisors Team)
Dr Esther Papies is a Senior Lecturer in the Institute of Neuroscience and Psychology, where she heads the Healthy Cognition Lab. Esther obtained her PhD in Social Psychology 2008 at Utrecht University in the Netherlands. Her work focuses on health behaviour and behaviour change in daily life, especially with regard to healthy and sustainable food and drink choices. She develops tools that help people make healthy choices in unhealthy environments, for example by delivering personalized, situated reminders of health goals, or through flexible self-regulation strategies based on mindfulness. She is currently involved in interdisciplinary work that explores the use of virtual agents in digital health interventions.
Marios Philiastides (Member of the Supervisors Team)
Dr. Marios Philiastides is a Reader at the Institute of Neuroscience and Psychology and the Centre for Cognitive Neuroimaging at the University of Glasgow. He received his MSc degree in Electrical Engineering from Stanford University in 2003 and his doctoral degree in Biomedical Engineering from Columbia University in 2007. Dr. Philiastides’ research group is interested in the neurobiology of human decision making. More specifically, his lab is involved in characterising the neural correlates of perceptual, value-based and social decision making, including reinforcement-guided learning and reward-related activity in the dopaminergic system in health and disease. He uses a multimodal approach, which combines various forms of neuroimaging and interventional techniques (EEG, fMRI, simultaneous EEG/fMRI, MEG, TMS/tDCS) along with computational modelling and multivariate data analysis techniques to expose the relevant brain networks and the mechanistic details of the underlying neural computations. The computational techniques used in his lab are motivated by classical problems in signal processing, machine learning and statistical pattern recognition and are designed to expose distributed neural representations and decipher how information flow through “networks” can lead to changes in behaviour. In addition, his lab is involved in the development of (neuro)physiologically-informed Artificial Intelligence (AI) systems to enable collaborative decision making between humans and artificial agents. This work draws directly from new insights gained through the lab’s main theoretical and experimental interests in order to exploit neural and systemic physiological information, together with affective cues from facial features and posture/gait to infer latent cognitive and emotional states of humans interacting with AI agents in collaborative decision-making tasks using immersive VR technology. His research is supported by generous contributions from a number of external sources including grants from the BBSRC, ESRC, EPSRC, MRC, the British Academy and the Royal Society.
Frank Pollick (Member of the Supervisors Team)
Frank Pollick is interested in the psychology of human interaction with AI. He also has a broad interest in human cognition and multisensory perception, especially as it relates to how the brain turns observations of others into an understanding of their intentions and emotions. He is currently working with Qumodo on research to optimise performance of human-AI teams. This research investigates the calibration of trust between humans and AI as well as ways to use AI to mitigate psychological impact in individuals who analyse distressing imagery as part of their job. His methodological approaches include the techniques of psychophysics, functional Magnetic Resonance Imaging (fMRI), realtime fMRI neurofeedback and transcranial Direct Current Stimulation (tDCS). In collaboration with researchers in computing science he has used these techniques to explore information need (Best Paper Awards at SIGIR 2016 and ECIR 2013), perception of humanoid robots, multisensory warning signals for drivers (Best Paper Award at AutoUI 2014) and motion sickness in mobile VR environments. Finally, he is interested in ways that development and expertise influence how the world is experienced and has performed research using dancers, drummers, CCTV operators and individuals with autism to understand the neural bases of differences in how these individuals perceive the world.
Philippe Schyns (Member of the Supervisors Team)
Philippe G. Schyns, FRSE, Wellcome Senior Investigator, was trained at Brown University and MIT, is the founding Director of both the Centre for Cognitive Neuroimaging and the Institute of Neuroscience and Psychology and at University of Glasgow. His research analyses the information processing mechanisms of the brain. His key contributions include establishing the functional role of diagnostic features in framing the brain as a dynamic information processing organ that strategically senses the external world and flexibly produces categorization behaviour.
Rosalind Searle (Member of the Supervisors Team)
Prof. Rosalind H. Searle holds the chair in HRM and Organisational Psychology at the Adam Smith Business School at the University of Glasgow. She is a Chartered Occupational Psychologist and a Fellow of the British Psychological Society (BPS). She has a PhD from Aston University, and an MBA. Her research focuses on organisational trust and HRM, trust and controls, change and counterproductive work behaviours. She is co-editor for the Routledge Companion to Trust (2018) and serves on editorial boards of Journal of Management, Journal of Trust Research, and International Perspectives in Psychology: Research, Practice, Consultation (IPP). Her research appears in leading international journals (e.g. Human Resource Management, Journal of Organisational Behavior, International Journal of HRM, and Long Range Planning) and in commissioned research for regulators (e.g. Professional Standards Authority), government (e.g. Welsh Audit, Scottish and English Governments) and private organisations (e.g. energy sector).
Sabina Siebert (Member of the Supervisors Team)
Sabina Siebertis Professor of Management at the Adam Smith Business School, University of Glasgow, UK, and conducts research in the area of management and organisation studies. She employs a range of qualitative methodologies including discourse analysis, narrative analysis and organizational ethnography. Sabina has published in various journals such as Organization Studies, Academy of Management Journal, Sociology, and Work Employment and Society. She was the Editor-in-Chief of the European Management Journal. In her research inspired by Science and Technology Studies, she has been studying the ways in which technologies have been used to manage trust and distrust in organizations. As a Visiting Professor at the University of Gothenburg, Sweden, Sabina is participating in research program Managing Digital Transformations, which also includes preparation of new courses on the potential role of AI in management of contemporary organizations.
Jane Stuart-Smith (Member of the Supervisors Team)
Jane Stuart-Smith’s research expertise is in sociophonetics, the production and perception of speech with specific reference to how speech functions in society to construct and reflect personal, social, and regional identities, from individual speakers to larger social and cultural communities of speakers. To date she has (co)managed 12 externally-funded projects on different aspects of speech and society resulting in 85 publications in print, including on the social mechanisms underpinning sound change (e.g. the Sounds of the City project), accent and ethnic identity (e.g. ‘Glaswasian’), and articulatory phonetics and social variation (e.g. the Dynamic Dialects project). Stuart-Smith has a specific interest in social interaction and speech accommodation, especially in contexts such as experiencing pre-recorded broadcast speech from e.g. TV, film, social media, without direct human interaction: she directed the first systematic investigation on the influence of the TV on speech (published in Language, 2013), and led the innovative Brains in Dialogue PhD project (Solanki, 2017), on speech and neural processing during collaborative talk. Stuart-Smith also led the collaboration with researchers at the Clinical Audiology, Speech and Language Research Centre, Queen Margaret University Edinburgh, to construct Seeing Speech, an online resource visualising speech production, which has attracted over 3million hits since 2014. Stuart-Smith currently (co)supervises 6 PhD students. Since 1999, she has (co)supervised 12 completed PhDs (100% completion rate), nine of which are/have been funded by competitive application to the ESRC, the Arts and Humanities Research Council, or the Glasgow University collaborative Kelvin-Smith scheme. Stuart-Smith’s research and contribution to increasing the public understanding of speech in society was recognized with a Fellowship to the Royal Society of Edinburgh in 2018; she is currently the Deputy Chair of the REF2021 panel for Modern Languages and Linguistics.
Mary Roth (CDT Candidate)
I am a recent Psychology graduate from the University of Strathclyde, Glasgow. To me, conducting research has always been the most interesting part of my degree. I find that people and minds are the most complex and fascinating phenomena one could study, and throughout completing my degree I have been very passionate about learning more about the mechanisms underlying our cognition, emotion, and behaviour.
Grounded in the work on my dissertation, my current research interests include the psychology of biases, heuristics, and automatic processing. In this PhD programme I will work on the project “Robust, Efficient, Dynamic Theory of Mind” with Stacy Marsella and Lawrence Barsalou.
Being part of the SOCIAL CDT programme, I look forward to contributing to the emerging interdisciplinary junction between psychology and computer science. Coming from a psychological background, I am excited to apply psychological research to the development of more efficient and dynamic models of social situations.
Rhiannon Fyfe (CDT Candidate)
I am a PhD student with the SOCIAL CDT. My MA is in English Language and Linguistics from the University of Glasgow. My current area of research is the further development of socially intelligent robots with a hope to improve Human-Robot Interaction, through the use of theory and methods from socially informed linguistics, and through the deployment in a real-world context of MuMMER (a humanoid robot, based on the SoftBank Robotics’ Pepper robot). During my undergraduate, my research interests included looking at the ways in which speech is practically produced and understood, which different social factors have an effect on speech, which different conversational rules are applied in different social situations, what causes breakdowns in communication and how they can be avoided. My dissertation was titled “Are There New Emerging Basic Colour Terms in British English? A Statistical Analysis”, which was a study into how the semantic space of colour is divided linguistically by speakers of different social backgrounds. The prospect of developing helpful and entertaining robots that could be used to aid child language development, the elderly and the general public drew me to the SOCIAL CDT. I am excited to move forward in this research.
Andrei Birladeanu (CDT Candidate)
I am part of the first cohort of SOCIAL CDT students and am working with Professor Emily Cross and Dr Mary Ellen Foster. I did my undergraduate degree in Psychology at the University of Aberdeen finishing up with a thesis examining interoceptive abnormalities underlying social anxiety. The project integrated findings from social dynamics, neuroscience, and philosophy allowing me to see the benefits of interdisciplinary work firsthand. My research interests revolve around the mechanisms behind human-human and human-machine interaction and the project I am working on aims to understand and improve the interaction between humans and artificial agents. I also have a keen interest in theoretical Cognitive Science, especially in the sub-field of philosophy of mind and issues around representation, dynamical systems theory, and computational models of the mind.
Emily O’Hara (CDT Candidate)
My name is Emily O’Hara and I am a current PhD student in SOCIAL, the CDT program for Socially Intelligent Artificial Agents at the University of Glasgow. My doctoral research focuses on the social perception of speech, paying particular attention to how the usage of fillers affect the percepts of speaker personality. Within the frames of artificial intelligence, the project aims to improve the functionality and naturalness of artificial voices. My research interests during my undergraduate degree in English Language and Linguistics included sociolinguistics, natural language processing, and psycholinguistics. My dissertation was entitled “Masked Degrees of Facilitation: Can They be Found for Phonological Features in Visual Word Recognition?” and was a psycholinguistic study of how the phonological elements of words are stored in the brain and accessed during reading. The opportunity to integrate my knowledge of linguistic methods and theory with computer science was what attracted me to the CDT, and I look forward to undertaking research that can aid in the creation of more seamless user-AI communication.
Salman Mohammadi (CDT Candidate)
I’m a PhD student in the SOCIAL CDT working on Deep Reinforcement Learning and its application to Brain Computer Interfaces. This kind of work revolves around augmenting human decision making processes using AI, by exposing latent neural states correlated with decision making processes to humans in real-time.
Prior to this, I completed my BSc in Computing Science at the University of Glasgow. My honours dissertation was on deep learning methods for learning different compositional styles in classical piano music, and I conducted a user-study which evaluated AI-generated piano music in different styles. As part of a summer scholarship with the School of Computing Science, I’ve been extending this work and researching the wider field of deep variational inference and representation learning for variational auto-encoder models, which focuses on automatically discovering latent and semantically meaningful low dimensional representations of high dimensional data.
In my PhD I’m looking forward to progressing state-of-the-art reinforcement learning and working in the intersection between artificial intelligence and neuroscience. I hope to contribute to research that augments human intelligence with artificial intelligence to create entirely new modes of thought and expression for humans.