Date | Speaker | Topic | More Detail (click on the link) |
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10/10/2024 | Dr Pablo Arnau González,
University of Valencia, Spain |
Current Challenges and Goals of Algebra and Arithmetic Intelligent Tutoring Systems |
Abstract / BioAbstract: Bio: |
17/10/2024 | Prof. Dr. Jörg Frochte, Bochum University of Applied Sciences, Germany | The Role of Continuous Learning and Explainable AI in Advancing Sustainable AI |
Abstract / BioAbstract: Bio: |
24/10/2024 | Dr. Luca Arnaboldi, University of Birmingham, UK | TBA | TBA |
31/10/2024 | Prof. John Vines, University of Edinburgh, UK | TBA | TBA |
07/11/2024 | Dr. Tehila Mechera-Ostrovsky, University of Munich (LMU), Germany | TBA | TBA |
14/11/2024 | Prof. Ann Blandford, University College London, UK | TBA | TBA |
21/11/2024 | Dr Ana Serrano Mamolar, University of Burgos, Spain | Self-adaptive and context-aware intelligent training systems in sensorised immersive virtual reality environments for occupational risk prevention |
Abstract / BioAbstract: Bio: |
28/11/2024 | AIHS Internal Meeting | TBA | TBA |
04/12/2024 | TBA | TBA | TBA |
11/12/2024 | TBA | TBA | TBA |
Seminars
Weekly Seminars
The AIHS seminar series usually takes place Thursdays 13:00–14:00 in the Scott Logic Lecture
Theatre (MCS 0001) or you can join via Zoom.
For talks or any other questions contact Professor Effie Lai-Chong Law: [email protected]
Year 24/25
Year 23/24
Date | Speaker | Topic | More Detail (click on the link) |
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11/06/2024 | AIHS Group meeting: internal meeting | ||
04/06/2024 | Beatrice Tylstedt and Hannah Westwood | Situational Analysis |
Abstract / BioAbstract: Beatrice Tylstedt is a third year PhD student in Human-Computer Interaction at Uppsala University, and currently a visiting researcher at Durham University. Using qualitative methods and feminist perspectives, she studies FemTech and apps for reproductive health, looking at how technology mediates lived and embodied experiences of menstruation, fertility, and pregnancy. |
28/05/2024 | Dr Edward Palmer | The impact of AI on Education: Resilience of Assessment Tasks |
Abstract / BioAbstract: Whilst the goal of the session is to open discussion and explore issues together it will be framed by discussion of courses developed for staff and students, the impact of AI on course design and the development of a framework to evaluate how the resilience of assessment tasks can be quickly evaluated. Results of staff and student surveys will be shared as well as the pilot results of the application of the resilience framework. Bio: He is working on projects investigating the role of narrative and storytelling as part of community education on men’s health, the long-term impact of COVID on students, parents and institutions, the use of discussion forums in teaching and the role of personalisation of learning on student outcomes. Edward is the convener of HERGA, a community of over 1000 education practitioners in South Australia and serves on the academic board for SAIBT. He is on the state board for the premier education group in Australia, HERDSA. |
21/05/2024 | Prof. David Messinger | Multispectral and Hyperspectral Imaging for Cultural Heritage Studies (video) Passcode: xDWb%8fi |
Abstract / BioAbstract: |
14/05/2024 | Prof Aniko Ekart | How can we have a good future with Artificial Intelligence? |
Abstract / BioAbstract: Bio: |
07/05/2024 | Prof Ju-Ling Shih | Personality, Behavior, and Strategies: The Interdisciplinarity and Dynamic of Complex Board Games (video) Passcode: 9wPVF1.n |
Abstract / BioAbstract: This presentation has two main parts: The first part introduces “Game Design and Technological Applications,” elucidates the core concepts of game design and its multifaceted variations. It explores the dynamic interconnections and interdependencies among learners, which foster students’ inquiry, negotiation, decision-making, and interaction. The second part addresses “Dynamic Behavior and Multimodal Analysis,” which delves into the research aspects, methods, and issues related to factors such as students’ personalities that impact their dynamic behaviors, social relationships, and problem-solving strategies. This presentation highlights the transformative potential of these experiences for educational purposes and fostering a deeper understanding of the dynamics involved in students’ engagement and behavior. Bio: |
30/04/2024 | Mohamed Khamis | Protecting Users in Virtual Realms: Security, Privacy, and Safety in the Metaverse (video) Passcode: x6jP5%w& |
Abstract / BioAbstract: |
23/04/2024 | AIHS Group meeting: internal meeting |
Date | Speaker | Topic | More Detail (click on the link) |
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12/03/2024 | Dr. Juan Boubeta-Puig | Complex Event Processing: Fundamentals, Applications and Challenges |
Abstract / BioAbstract: |
05/03/2024 | AIHS Group meeting: internal meeting | ||
27/02/2024 | EquiAI Session: Speaker: Renée Cummings |
Bias in AI: why does it matter? |
Abstract / BioAbstract: |
13/02/2024 | Anna-Grace Linton | Using weakly supervised text classification on patient reported free text comments.(video) Passcode: N9vXh^iA |
Abstract / BioAbstract: |
06/02/2024 | AIHS Group meeting: internal meeting | ||
30/01/2024 | Dr Brian Bemman | AI, Humanities, and Health |
Abstract / BioAbstract: |
23/01/2024 | Dr Miriam Sturdee | The Odd One Out: Realising the Value of Creative and Unusual Methods in HCI & Computer Science |
Abstract / BioAbstract: |
16/01/2024 | Dr Chen Wenli | Computer-Supported Collaborative Argumentation: Technological and Pedagogical Design. |
Abstract / BioAbstract: |
09/01/2024 | AIHS Group meeting: internal meeting |
Date | Speaker | Topic | More Detail (click on the link) |
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05/12/2023 | AIHS Group meeting: internal meeting | ||
28/11/2023 | Dr. Paddy Ross | Can children ignore what they hear? A look at developmental trajectories of emotion recognition in children. |
Abstract / BioAbstract: |
21/11/2023 | EquiAI Session: Multiple Speakers | Future of AI governance. (video) Passcode: t6dvtFX& |
Abstract / SpeakersAbstract: Session 1, AI Governance Now (13:00-14.30) Session 2, The Future of AI Governance: emergent challenges, risk and opportunities (14:45-16.15) Speakers: |
14/11/2023 | Dr Amir Atapour-Abarghouei | Vision, Language and Beyond: Understanding the World through Learning.(video) Passcode: 9n9?#E=S |
Abstract / BioAbstract: |
07/11/2023 | AIHS Group meeting: internal meeting | ||
31/10/2023 | Prof Simon Dixon | AI Models for Understanding Jazz |
Abstract / BioAbstract: Bio: |
24/10/2023 | Dr Antonio Bucchiarone | Let me adjust to the challenge! Approaches to personalized and gamified learning. (video) Passcode: 3+N8Ci.0 |
Abstract / BioAbstract: |
17/10/2023 | Dr Stuart James | Interacting with Cultural Heritage from the smallest fragments to city monuments. (video) Passcode: =Rbp+D5B |
Abstract / BioAbstract: |
10/10/2023 | Prof Ting-Chia | Simultaneously Improving Computational Thinking and Foreign Language Learning: Interdisciplinary Media With Plugged and Unplugged Approaches. (video) Passcode: 9A=Ng7!J |
Abstract / BioAbstract: As for international academic service and leader missions, Dr. Hsu has organized and lead many international conferences (e.g., GCCIL2017, SETE 2019, GCCCE2021), workshops (e.g., TELL, CUMTEL, CTE-STEM), panel (e.g., ICWL2013/ICCE2019), sub-conferences (e.g., GCCE, ICCE, CTE) or main-conferences (e.g., GCCIL2017/ SETE2019/ CTE2020/ GCCCE2021/ ICFULL2022), and also served as a guest editor for some international journals (e.g., IJMLO, RPTEL, IJOPCD, IRROLD, Substantiality) and an assistant editor-in-chief and associate editor of Frontiers in Psychology (Educational Psychology Division). She was the chair of The Special Interest Group (SIG) on Technology Enhanced Language Learning (TELL) under the Asia-Pacific Society for Computers in Education (APSCE) from 2018 to 2019. She was the chair of The Special Interest Group (SIG) on Technology Enhanced Language Learning (TELL) under the Information and Computer Education Division in the Ministry of Science Technology in Taiwan from 2019 to 2020. She was also the Chair of The Special Interest Group (SIG) on Classroom, Ubiquitous and Mobile Technology Enhanced Learning (CUMTEL) under the Asia-Pacific Society for Computers in Education (APSCE), 2020-2021. She is currently also the Co-Chair of The Special Interest Group (SIG) on Computational Thinking-Science, Technology, Engineering, Mathematics Education (CTE-STEM) under the Asia-Pacific Society for Computers in Education (APSCE), 2022-2023. In highlight of her social impact, as a Computer Education major, Dr. Hsu is both outstanding in the research on technology-enhanced learning and active in the research on information and technology education. She has the experience of teaching from secondary schools to universities. These professional training and work experiences are related to and contribute to her position as an expert and a scholar in educational technology and computational thinking research. |
03/10/2023 | AIHS Group meeting: internal meeting |
Year 22/23
Date | Speaker | Topic | More Detail (click on the link) |
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27/06/2023 | Bias in AI Talk | TBD |
Abstract / BioAbstract: |
22/06/2023 | Prof Peter Brusilovsky, University of Pittsburgh | Human-Centered AI in AI-ED (video) Passcode: P7?LwEmP |
Abstract / BioAbstract: |
20/06/2023 | Prof Per Ola Kristensson, Cambridge | Design Engineering for AI Engineering (video) Passcode: iD=6Rb+c |
Abstract / BioAbstract: |
13/06/2023 | AIHS Group meeting: Department research Away Day | ||
06/06/2023 | AIHS Group meeting: internal meeting | ||
30/05/2023 | Bias in AI Network: Speakers: Dr Lauren Martin – Associate Professor of Political Geography at Durham University Dr Davy Smith – Chief Innovation Officer at Tintra. |
The use of novel technologies in Financial and Humanitarian aid Contexts and issues of Inclusion and Access (video) Passcode: XK@pj3=w |
Abstract / BioTalk 1 – Abstract: Bio: Tintra is an early-stage banking infrastructure start-up which is mission driven to bring genuine financial and social inclusion to emerging markets through the development and application of culturally informed artificial intelligence and decentralised technologies. Through in-depth, locally situated cultural research, and by working alongside governments and regulators globally, Tintra’s aim is to provide a global banking infrastructure which is free from harmful bias. |
23/05/2023 | Prof Ana Cavalcanti, York University | Humans in RoboStar (video) Passcode: 2*uC2r8# |
Abstract / BioAbstract: |
16/05/2023 | Dr Mark Gotham, AIHS, Durham University | Chromatic chords in theory and practice (video) Passcode: aB!*6sV9 |
Abstract / BioAbstract: This talk reports on a long-term project addressing each of those three issues. First is a comparison of the terms typically taught in English- and German-speaking classrooms as an example of diverge (despite a substantially shared history). Second, is the proposal of tiered definitions for terms. Rather than attempting to force a single “definitive” version, this instead provides a framework for the choices needed for any clear definition. Notable examples include the many criteria needed for any robust definition of “modal mixture”. Third is a survey of the usage of these chromatic chords with a computational corpus study of human harmonic analysis across 2,000 analyses of 1,500 works (https://github.com/MarkGotham/When-in-Rome). This provides some indication of how significant each chord is to the repertoire at hand, and some insight for reviewing how they are weighted in our curricula. That data also enables pro-active benefits for open educational resources, notably the “Harmony Anthology” for the Open Music Theory textbook that enables free, interactive exploration of these chords and their contexts (https://viva.pressbooks.pub/openmusictheory/chapter/anthology-harmony/). |
09/05/2023 | Prof Helen Petrie, York University | Technology to support older people living independently: robots and drones (video) Passcode: q2#*Ee6f |
Abstract / BioAbstract: Bio: |
02/05/2023 | AIHS Group meeting: internal meeting |
Date | Speaker | Topic | More Detail |
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21/03/2023 | AIHS meeting Cancelled (presentation re-scheduled) | ||
14/03/2023 | AIHS Group meeting: internal meeting | ||
07/03/2023 | AIHS Dr Mike Schutz | Calculating musical emotion: Exploring best practices for automated analysis of musical structure |
Abstract / BioAbstract: Although simple musical features (i.e., pitch/timing) can be easily measured, more complex features required for empirical research can be difficult to quantify. For example, mode is a crucial feature, yet a composition’s mode might not match its key signature. In such cases, researchers often rely on expert raters. Yet experts can meaningfully disagree about seemingly simple questions. For example, some theorists argue the opening of Beethoven’s Third Symphony is in E-flat major; others that it is in C minor (Byros, 2012). How can we reliably evaluate musical features such as mode while accounting for meaningful differences in individual perspectives? To address this challenge, we developed a new technique-Distributed Music Analysis, combining music theorists’ expertise with recommended practices for reducing noise in decision-making. Five music graduate students completed a three-phase procedure rating the modality of 381 eight-measure excerpts of keyboard literature. In Phase 1, they independently evaluated each excerpt (in a unique order) on a scale from 1 (“entirely minor”) to 7 (“entirely major”), while recording noteworthy structural features. In Phase 2, raters reviewed each others’ notes and evaluations for a selection of 12-20 excerpts, before discussing as a group and updating their ratings confidentially (with additional notes on any changes). In Phase 3, raters independently reviewed personalized packets grouped by rating (e.g., all excerpts they evaluated as “1”), with a final opportunity for adjustment. Throughout this process, they developed personalized rubrics articulating their categorization approach. This process produced a rich data set of “continuous modality” evaluations useful as a cue for perceptual experiments. I am now working with Tuomas Eerola (Music) as an IAS Fellow to use these expert evaluations as “ground truth” for improving algorithms for computing modality in audio files. This talk will outline the procedure, outcome, and applications of this novel approach to musical analysis of value to music cognition and music information retrieval. Bio: Michael Schutz is Professor of Music Cognition/Percussion at |
28/02/2023 | Shauna Cocannon | Breaking Down Bias in AI: Navigating Strategies for More Equitable Systems ( online ONLY) |
Abstract / BioAbstract: A number of distinct methods have emerged for addressing harmful bias in AI systems. These encompass a spectrum of approaches such as toolkits and benchmarks to recognize and assess specific categories of bias, through to high-level guidance and methodologies that promote ethical design and development of systems. However, each approach has its own set of strengths and limitations. For example, technically-focused efforts often require a narrow operationalization of bias, while high-level guidance can be too broad and difficult to apply in practice. Additionally, algorithmic audits, ethical checklists, and benchmarks require careful scrutiny during adoption, and attentiveness to how their scope is designed and communicated is crucial for responsible use. Overemphasizing outcome-based measurements or recommended thresholds may also risk overshadowing the importance of procedural fairness and conducting continuous evaluations. How then to navigate the range of options available? This session will provide an opportunity to collectively explore some of the strengths and limitations of existing approaches, identify barriers to adoption, and consider what is needed to move the development of more equitable AI systems forward. |
14/02/2023 | CANCELLED (Strike) | TBA: |
AbstractTBA |
21/02/2023 | CANCELLED (Strike) | TBA: |
AbstractTBA |
07/02/2023 | AIHS Group Monthly Meeting | TBA: |
AbstractTBA |
31/01/2023 | Bias in AI Network
Catherine Breslin |
Deploying Real-World Speech Technology |
Abstract:
Bio: Catherine is an AI Consultant at Kingfisher Labs Ltd. in Cambridge. She has both commercial and academic experience of automatic speech recognition, natural language understanding and human-computer dialogue systems, having previously worked at at Cambridge University, Toshiba Research, Amazon Alexa, and Cobalt Speech.
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24/01/2023 | Dr Rafael Ferreira Mello (CESAR University) and Dr Isabela Gasparini (Santa Catarina State University), Brazil,) | Title 1: Enhancing Instructors’ Capability to Assess Open-Response Using Natural Language Processing and Learning Analytics. Tite 2: Educational games to promote the development of computational thinking in children, both neurotypical and with intellectual disabilities |
About Rafael Ferreira MelloRafael Ferreira Mello has a Ph.D. in computer science with research interests that span learning analytics and natural language processing. He is a lecturer and researcher at the CESAR University in Brazil, where he holds the position of Chair of Education Technology Adoption and Data Analytics. In the last few years, Dr. Mello has supported adopting Learning Analytics techniques and tools in several institutions in Brazil. One recognition of his contributions is that Dr. Mello is the leading researcher at two national-level projects, funded by the Brazilian Ministry of Education, aiming the development of (i) natural language processing and learning analytics techniques to enhance students’ written productions and (ii) Learning Analytics Dashboards to support decision-making regarding the national education plan. Moreover, he has worked on several multinational research projects involving institutional and organizational partners in Europe, Australia, and Latin America. He has published in the leading international journals and conference proceedings in the fields of his research. He also served as an assistant editor and reviewer for several journals and conferences, including the International Learning Analytics & Knowledge Conference, the Journal of Learning Analytics, Computers and Education, the British Journal of Educational Technology, and Internet and Higher Education.Research Title: Enhancing Instructors’ Capability to Assess Open-Response Using Natural Language Processing and Learning Analytics
Abstract About Isabela Gasparini Isabela Gasparini received her Ph.D. degree from the Federal University of Rio Grande do Sul (UFRGS – Brazil) with a sandwich period at TELECOM Sud Paris (France). She is an Associate Professor at the Department of Computer Science at the Santa Catarina State University (UDESC), where she is involved in Human-Computer Interaction and Technology-Enhanced Learning fields, with a special interest in adaptive e-learning systems, gamification, learning analytics, recommender systems, infoviz, context-awareness, and cultural issues. She has a Productivity Scholarship in Technological Development and Innovative Extension from CNPq (National Council for Scientific and Technological Development – Brazil) and currently, she is a Counselor of the Brazilian Computer Society (2021-2025). She was the editor-in-chief of the Brazilian Journal of Computers in Education (2019-2021), and coordinator of the Special Human-Computer Interaction (IHC) committee of SBC (Brazilian Computer Society) (2019-2021). She was a member of the special informatics in education committee of SBC (2019-2021). In 2021 she was the Program Chair of the XV Women in Information Technology – WIT 2021, a scientific event supported by the Brazilian Computer Society. Research Title: Educational games to promote the development of computational thinking in children, both neurotypical and with intellectual disabilities Summary: |
17/01/2023 | Dr David Vallejo Fernández | A Journey through Immersive Systems for Remote Rehabilitation |
Abstract: The physical rehabilitation of individuals suffering from neurological diseases is of vital importance for them to regain mobility, improve independence, and achieve a higher level of autonomy. Telemedicine solutions, specifically those designed for remote rehabilitation, have attempted to address the global issue posed by the growing number of patients with neurological diseases and the shortage of clinical staff available to support traditional rehabilitation techniques. In this presentation, Dr. Vallejo will discuss the various software prototypes that he and his team have designed and developed in the context of remote rehabilitation. These prototypes utilize natural user interfaces to facilitate interaction with the systems, gamification techniques to engage patients in the rehabilitation process, and artificial intelligence to automate tasks such as recommendations or adaptations of physical routines for individual patientsShort Bio: David Vallejo holds a PhD in Computer Science (awarded Summa Cum Lauda) by the University of Castilla-La Mancha (UCLM), Spain, where he also graduated with honors and was awarded with the ‘Best Undergraduate Project’ due to his work on distributed rendering of complex 3D scenes. In 2007 he began his academic career as a Lecturer in the Department of Information Technologies and Systems. Since then, he has taught on programming-related areas, such as data structures, algorithms and complexity, computer graphics, operating systems, concurrent programming, and video games development. Currently, he is an Associate Professor at UCLM, where he also served as Academic Director in the General Secretary from 2016 to 2021. He is a member of the Artificial Intelligence and Representation (AIR) research group and his research focused on the practical application of Artificial Intelligence. Within this context, he is interested in e-health, distributed AI, augmented reality, and electronic commerce. Since 2016, he is President and Co-Founder of Furious Koalas, a start-up providing high-quality services for applications in the areas of gamification, serious games, simulation, and computer vision.
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10/01/2023 | Lunch together! | TBA: it will be announced; but possibly it will be in the Botanical Gardens or in the Building (if weather too wet) |
AbstractTBA |
Date | Speaker | Topic | More Detail |
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29/11/2022 | Prof Helen Petrie, University of York, UK | Technology to support older people living independently: robots and drones. CANCELLED |
Abstract and BioAbstract: The population of most societies is ageing rapidly, with more older people and fewer younger people to care for the older people. Older people want to remain in their own homes as long as possible, and overall this is a less expensive option than specialist accommodation, but comes with a number of challenges. Numerous technologies are being promoted as alternatives or supplements to human care for older people in their own homes, particularly instrumented smart home technologies and robots. An option which may have some advantages but which has been less explored is the use of small drones. This talk will discuss a number of studies with older people about the use of robots and drones to support them in living independently, the potential of these technologies and older people’s attitudes towards them. Bio: Helen Petrie Phd AFBPsS CPsychol FRSA Professor Emerita of Human Computer Interaction Department of Computer Science University of York Deramore Lane Heslington East York YO10 5GH |
22/11/2022 | Prof Bjorn Schuller, Imperial College London, UK and University of Augsburg, Germany (online) | Speak Softly Love (video) Passcode: Vg5pkQ3$ |
Abstract and BioLending AI the Human Touch Artificial Intelligence needs to communicate with us and understand us – ideally in the “human way”. This brings artificial socioemotional competency, charisma, and empathy into play. Here, we shall look at the latest developments in modelling these skills from the spoken language perspective. This includes self-supervised learnt transformers for recognition of emotion and beyond from a user’s voice and words. It further includes using deep models for affective speech synthesis including the generation of mixed emotions. The talk will include examples from an industrial perspective. It will also touch upon real-world usage implications such as fairness or the provision of embedded solution. Bio: Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany. He is Full Professor of Artificial Intelligence and the Head of GLAM at Imperial College London/UK, Full Professor and Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg/Germany, co-founding CEO and current CSO of audEERING – an Audio Intelligence company based near Munich and in Berlin/Germany, independent research leader within the Alan Turing Institute and Royal Statistical Society Lab’s Data, Analytics and Surveillance Group, as part of the UK Health Security Agency, and permanent Visiting Professor at HIT/China amongst other Professorships and Affiliations. Previous stays include Guest Professor at Southeast University in Nanjing/China, Full Professor at the University of Passau/Germany, Key Researcher at Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. He is a Fellow of the IEEE and Golden Core Awardee of the IEEE Computer Society, Fellow of the BCS, Fellow of the ISCA, Fellow and President-Emeritus of the AAAC, and Senior Member of the ACM. He (co-)authored 1,200+ publications (50k citations, h-index=100+), is Field Chief Editor of Frontiers in Digital Health and was Editor in Chief of the IEEE Transactions on Affective Computing amongst manifold further commitments and service to the community. His 30+ awards include having been honoured as one of 40 extraordinary scientists under the age of 40 by the WEF in 2015. He served as Coordinator/PI in 15+ European Projects, is an ERC Starting and DFG Reinhart-Koselleck Grantee, and consultant of companies such as Barclays, GN, Huawei, Informetis, or Samsung. |
15/11/2022 | Dr Antonio Garcia-Domingues, York University, UK | Automating instructor feedback for teaching introductory programming (video) Passcode: #F+LavV6 |
Abstract and BioFirst-time programmers need timely and effective feedback to surpass the hurdle of learning to “think in code” while also tackling the technical complexity of a programming language. Delivering feedback on time at scale in a way that accommodates both teacher and student circumstances can be challenging, given the increasingly large cohorts in Computer Science courses: this is especially the case in the first year of their courses, where students start with a broad range of prior experience. This motivated our adoption of automated testing approaches for assessment and feedback: failed tests can guide the student to the underlying issues without having to wait for a teacher to look at their code. However, these tools are generally limited in the type of feedback they can produce, require the use of version control systems, or are embedded into industrial project management solutions with significant complexity. We have developed AutoFeedback, a web-based system targeted at providing instructor-written feedback to first-year programmers on their code submissions in a simple manner, with the ability for module staff to quickly refine tests and feedback based on the student experience. In this talk, I will discuss the design of AutoFeedback and our experiences using it for the 2020-21 and 2021-22 editions of the CS1OOP module at Aston University. Feedback from students has been positive, with more consistent participation levels observed over the year after introducing AutoFeedback, and students requesting its addition to other modules. The experience has also raised some caveats about test design to support automated feedback, the architecture needed for scalability, and how to write understandable feedback templates. Bio: Dr. Antonio Garcia-Dominguez is a Lecturer at the Department of Computer Science of the University of York, and a member of the Automated Software Engineering research group. Antonio’s main research interests are model-driven software engineering (with lines of work on scalability of MDSE and on runtime models for explainability), software testing (specifically, search-based testing and metamorphic testing), and computer science education. In addition to over 60 peer-reviewed publications in international conferences, journals, and book chapters, Antonio is a core contributor in several related open source projects. These include the MuBPEL mutation testing framework for WS-BPEL, the GAmera tool for evolutionary mutation testing, the Eclipse Epsilon model management languages and tools, the Eclipse Hawk model indexing framework, and the AutoFeedback automated code feedback system. |
08/11/2022 | Dr Ivana Dusparic, Trinity College Dublin, Ireland (online) | Reinforcement Learning for city-scale applications: Adapting in large-scale heterogeneous dynamic environments (video) Passcode: 7W8bX1B! |
Abstract and BioAbstract: RL has seen major breakthroughs in the recent years and is extensively investigated in a range of practical applications, including those within smart cities. However, existing algorithms still fall short of being suitable for a wider use in such complex environments. My research focuses on developing techniques that enable the use of RL for optimization in large-scale adaptive systems, for example, smart grid, communication networks, and intelligent mobility. These city-scale infrastructures share properties with many other large-scale systems, i.e., are characterized by distributed control, heterogeneity, presence of multiple and often conflicting goals, reliance on diverse sources of information, and above all the need for continuous adaptation. In this talk I will discuss a range of techniques we have developed for enabling RL use in such environments, in particular multi-agent multi-objective optimization, adaptation in non-stationary environments, online transfer learning , state space adaptation, and explainability of RL-based systems. I will conclude the talk by discussing further challenges in enabling RL deployments in self-adaptive systems, including further development of algorithms to ensure seamless lifelong adaptivity and highlighting the need for explainability and software testing techniques for RL-based applications. Bio: Ivana Dusparic is an Associate Professor in the School of Computer Science and Statistics, and a recently elected Fellow of Trinity College Dublin. She is currently a co-director of Science Foundation Ireland Centre for Research Training in AI, Principal Investigator of the Smart Networking in the Era of AI collaboration between Trinity College Dublin and Tsinghua University, and a co-PI in ClearWay, a newly funded project on Advancing Deep Reinforcement Learning and Swarm Intelligence for intelligent mobility. She is active in promoting AI-enabled sustainability, as a member of the management committee of the European COST network on Wider Impacts of Autonomous Vehicles, a member of the Royal Irish Academy’s Computer Science and Engineering Committee, and a member of the steering committee of Future Cities: The Trinity Center for Smart and Sustainable Cities. |
01/11/2022 | AIHS staff meeting. | ||
25/10/2022 | Dr Charles Morisset, Newcastle University | Security and Privacy of Smart Buildings (video) Passcode: T*r8U19m |
AbstractBuilding are becoming increasingly smart to improve their efficiency and occupant comfort. However, the interconnection and ubiquity of sensors in a shared place raises some privacy and security questions, such as the risk for occupant behaviour to be continuously tracked or for the building to be compromised by attackers. In this talk, we’ll present some of the core challenges to answer these questions, illustrating them with a real-world example (the Urban Sciences Building at Newcastle University) and discuss some concrete approaches to address these challenges. |
18/10/2022 | Dr Jan Deckers, Newcastle University (F2F) | AI in health care: hurdles and opportunities (video) Passcode: BXiS3&r$ |
Abstract and BioPatients and health care staff must trust the decisions that they make about their own health and the health of others. Human decision-making is flawed as people do not always know all the facts that are relevant for decision-making, may not be able to interpret facts, and may not be able to evaluate them appropriately. AI systems may be able to help human decision-making by gathering more facts that are relevant, and by helping with the interpretation and the evaluation of data. Thus, they may help in increasing trust in decision-making and promote good health care. However, health care may also be undermined by AI. This presentation sketches four significant hurdles that must be overcome to ensure that AI systems do not undermine health care before providing some suggestions as to how AI systems might be designed and used to promote good health care. Bio: Jan Deckers lectures in bioethics at Newcastle University. He started his work there in 2001. He is from Belgium and obtained a PhD from St Andrews University on ecological ethics. Koji Tachibana studies philosophy and applied ethics at Chiba University, Japan. He started his work there in 2022. He obtained a PhD from the University of Tokyo on ancient Greek philosophy. |
11/10/2022 | Dr Shauna Concannon, CS Durham University (F2F) | Interactional and ethical consideration for the responsible design of conversational systems (video) password =$0L9Ev! |
Abstract and BioConversational interfaces are increasingly commonplace and dialogue agents are used to perform a variety of functions previously performed by humans. Recent work in dialogue systems has begun to explore how human-like character traits and personas can be embedded within dialogue agents in order to support more human-like and naturalistic human-machine interactions. In this talk I will present work examining the integration of empathetic strategies in chatbots and explore some of the practical, ethical and societal implications that arise when developing increasingly ‘human-like’ agents. I will consider some key challenges for the responsible design of conversational systems and highlight how an interactionally focused approach might be usefully applied. Bio: I am an interdisciplinary researcher, combining approaches from linguistics, psychology , HCI and data science, both applying and studying the use of computational approaches to understand how knowledge is linguistically encoded in an increasingly technologically mediated society. My PhD examined how disagreement is managed in computer-mediated dialogue in the Cognitive Science and Computational Linguistics research groups at Queen Mary, University of London. Prior to joining Durham, I held postdoctoral positions at the Universities of Newcastle, York and Cambridge, working on human-data-interaction, human-machine-communication and feminist approaches to data science. |
04/10/2022 | AIHS ALL staff meeting. F2F Room RH001 (Rowan House – the building is a minute walk across the pond). | Meeting ALL AIHS members(staff, postdocs and PhD students. etc). Hibrid (f2f and Zoom) |
Year 21/22
Date | Speaker | Topic | More Detail |
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29/07/2022 | Oleg Sychev, Assoc. Prof., Volgograd State Technical University | Generating Automatic Feedback for Online Learning: From Completion Hints to Explaining Domain Law Violations and Asking Questions |
AbstractPerforming assessments and receiving feedback about their correctness and the errors made is an important part of the learning process. Practice with feedback converts knowledge into skills. Students who have trouble grasping material from texts can discover it from practice in a controlled environment if their errors are shown and explained to them. To achieve this effect, feedback must be informative: if a student gets stuck, they must be able to find their error and continue solving the exercise using the provided feedback. Automatic feedback on simple, routine tasks lets teachers concentrate on developing higher-level skills; it is critical for MOOCs where teachers’ time is not enough to give feedback to every student. So my talk will be about different kinds of feedback that can be calculated from the student’s answer. We started from simple string completion hints to short-text answer questions where answers were templated by regular expressions. The feedback is the correct beginning of the answer (up to the first wrong character), the next correct character, or the next correct word (token), leading to the nearest completion. This alone increased students’ engagement with e-learning tools, especially for the students who gained little from lectures and reading, sometimes leading to the “Eureka” effect when the student discovered the rules they couldn’t get from explanations. Our next model, the basis of CorrectWriting software, was used to teach syntax: writing correct tokens in the correct order. The feedback is error messages about misplaced, omitted, and extraneous tokens and hints on how to fix them the model relies on the teacher to provide the descriptions of tokens’ syntactic roles. CorrectWriting was used to teach programming languages and English natural language. Our new generation of intelligent formal models aims to automate developing comprehension of concepts when introducing students to new subject domains. They use simple exercises exposing the properties of the studied concepts, and, using closed-answer questions, are able to link every wrong step from a student to breaking some domain law, providing explainable feedback about errors as soon as they are made. Having detailed information about the laws student got right and the laws the student got broken repeatedly provides good grounds to study adaptation techniques, especially because the problem’s properties (the laws and concepts it requires to solve) can be formally deduced instead of relying on teacher’s expertise. These models can also solve tasks for the students, so only problem description (both in human-readable and formal forms) is needed. This makes creating worked examples (or demonstrating particularly hard steps) easy and opens the way to mine a large question base from existing open-source code. Mining and generating questions will allow solving another important problem, taking the burden of exercise creation from teachers and providing a practically unlimited supply of problems with any necessary properties. Another important feature of this approach is follow-up questions, trying to make the student think about their errors and determine the exact fault reason. We developed a set of follow-up questions for the experimental domain and are starting to develop methods of their automated generation. While these exercises are relatively small and easy for now, they leverage question generation and solving to a new level and later can be adapted to more complex tasks. |
23/06/2022 | Prof Yulan He, University of Warwick | Learning from COVID-19: from Debunking to Vaccine Attitude Detection (video) |
AbstractTBC |
16/06/2022 | Dr. Simone Stumpf, University of Glasgow | Making AI more understandable, interactive and human-centric |
AbstractAlthough the interdisciplinary field of Music Information Retrieval (MIR) is relatively young, with the first international flagship conference (ISMIR) being held in 2000, the term itself in fact dates back to the 1960s (Kassler 1966). Yet, insofar as researchers retell the history of their discipline in the margins of their work, such distant starting points are frequently forgotten or overlooked. This talk draws on my doctoral research into the history of computational approaches to music to better understand the connections between MIR as it is practised today and the intellectual commitments of its early pioneers, including those who sought to design pre-digital information retrieval systems to organise the world’s recorded music. This talk comes at a moment in MIR, as in so many areas of applied computer science, when practitioners are exploring questions of fairness, ethics, and bias in the computational systems they describe in their research. Their work is likely to benefit from deeper connections with the history of computing, and the history of musicology. Therefore, I will briefly describe some general proposals for how relevant historical context can be supplied in the dissemination of new computational or “AI” models of cultural data, along the lines of the recently proposed Datasheets for Datsets (Gebru et al. 2020 [2018]) and Model Cards for Model Reporting (Mitchell et al. 2019). |
09/06/2022 | Dr. Leandro Minku, University of Birmingham | Overcoming the Challenge of Limited Labeled Data in Data Stream Learning (video) |
AbstractThe volume and incoming speed of data have increased tremendously over the past years. Data frequently arrive continuously over time in the form of streams, rather than forming a single static data set. Therefore, data stream learning, which is able to learn incoming data upon arrival, is an increasingly important approach to extract knowledge from data. Data stream learning is a challenging task, because the underlying probability distribution of the problem is typically not static, but suffers changes over time. Such challenge is exacerbated by the fact that, even though the rate of incoming examples may be very large, only a small portion of these examples may arrive as labeled examples for training due to the high cost of the labelling process. In this talk, I will discuss novel data stream learning approaches and research directions to tackle this and other challenges posed by real world applications. Bio: Dr. Leandro L. Minku is an Associate Professor at the School of Computer Science, University of Birmingham (UK). Prior to that, he was a Lecturer in Computer Science at the University of Leicester (UK). He received the PhD degree in Computer Science from the University of Birmingham (UK) in 2010. Dr. Minku’s main research interests are machine learning in non-stationary environments / data stream mining, online class imbalance learning, ensembles of learning machines and computational intelligence for software engineering. Among other roles, Dr. Minku is Associate Editor-in-Chief for Neurocomputing, Senior Editor for IEEE Transactions on Neural Networks and Learning Systems, and Associate Editor for Empirical Software Engineering Journal and Journal of Systems and Software. He was also the General Chair for the International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2019 and 2020), and Co-chair for the Artifacts Evaluation Track of the International Conference on Software Engineering (ICSE 2020). |
26/05/2022 | Dr Eamonn Bell , CS Durham University | Looking back to move forward: the pre-histories of Music Information Retrieval (video) |
AbstractAlthough the interdisciplinary field of Music Information Retrieval (MIR) is relatively young, with the first international flagship conference (ISMIR) being held in 2000, the term itself in fact dates back to the 1960s (Kassler 1966). Yet, insofar as researchers retell the history of their discipline in the margins of their work, such distant starting points are frequently forgotten or overlooked. This talk draws on my doctoral research into the history of computational approaches to music to better understand the connections between MIR as it is practised today and the intellectual commitments of its early pioneers, including those who sought to design pre-digital information retrieval systems to organise the world’s recorded music. This talk comes at a moment in MIR, as in so many areas of applied computer science, when practitioners are exploring questions of fairness, ethics, and bias in the computational systems they describe in their research. Their work is likely to benefit from deeper connections with the history of computing, and the history of musicology. Therefore, I will briefly describe some general proposals for how relevant historical context can be supplied in the dissemination of new computational or “AI” models of cultural data, along the lines of the recently proposed Datasheets for Datsets (Gebru et al. 2020 [2018]) and Model Cards for Model Reporting (Mitchell et al. 2019). |
12/05/2022 | Neil Walkinshaw | Embracing Uncertainty when Reasoning about Software Behaviour video |
Abstract>Software systems are large, complex, and often evolve |
05/05/2022 | Prof Jane Cleland-Huang | Towards Human Machine Teaming in Emergency Response with small Unmanned Aerial Systems |
AbstractThe use of autonomous small Unmanned Aerial Systems (sUAS) to support emergency response scenarios, such as fire surveillance and search and rescue, offers the potential for huge societal benefits. However, designing an effective solution in this complex domain represents a wicked design problem, requiring the system to carefully balance sUAS autonomy and human control. While traditional “Human-on-the-Loop” (HoTL) systems, support this to some extent, technological advances in autonomic computing, are enabling a more advanced form of collaboration, referred to as Human Machine Teaming (HMT). HMT emphasises autonomy of both the human and the machine through their interactions, partnership, and teamwork. As such, HMT capitalizes upon the respective strengths of both the human and the machine, whilst simultaneously compensating for each of their potential limitations. In this talk, Professor Cleland-Huang will first describe the DroneResponse System, under development at the University of Notre Dame, and will then discuss the open challenges and preliminary solutions that are being taken in order to transition DroneResponse from a HoTL to an HMT environment. |
Date | Speaker | Topic | More Detail |
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17/03/2022 | Professor Roger K. Moore | Embodied versus Disembodied Conversational Agents: Two communities, one agenda?(video) |
AbstractRecent years have seen tremendous growth in the |
10/03/2022 | |||
03/03/2022 | Vincent Croset | Single-cell transcriptomics uncovers a novel role for glia in thirst-directed behaviours (video) |
AbstractThirst emerges from a range of cellular changes that |
24/02/2022 | |||
17/02/2022 | Dr. Patricia Muller, Biosciences, Durham University | p53 and metals; p53 protein unfolding and selection of p53 mutations in cancer (video) | |
10/02/2022 | Alan Dix, Professor and Director of the Computational Foundry, Swansea University | Digital Thinking seeing the world with digital eyes | |
03/02/2022 | Ann Blandford FHEA, Professor of Human-Computer Interaction at University College London | AI, computation and interaction: Explorations in healthcare | |
27/01/2022 | Seiji Isotani, Professor in Computer Science, Sao Paolo University, Brazil | Towards the Design of a Public Policy to evaluate educational technologies using evidence and AI | |
20/01/2022 | EPSRC New Horizons pitching to peers | ||
13/01/2022 | Martin j. Cann, Professor in BioSciences, Durham | Computational approaches to understand the impact of carbon dioxide on biological systems |
AbstractCarbon dioxide (CO2) is one of the most important |
Date | Speaker | Topic | More Detail |
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09/12/2021 | Bobby Lee Townsend Sturm JR, Associate Professor of Computer Science at KTH | Traditional Machine Music Learning |
AbstractBriefly, I will summarise and demonstrate my work |
02/12/2021 | Dr. Wayne Holmes, UCL | ||
25/11/2021 | Santawat Thanyadit, postdoctoral research associate in computer science and human-computer interaction at the Department of Computer Science, Durham University | MiniTutor: An Adaptive Avatar MR System to Improve Students’ Attention | |
18/11/2021 | Mohammad Mousavi | Model learning for evolving systems |
AbstractModel learning is a technique to learn behavioural models based on theory of automata (finite |
11/11/2021 | Tim Menzies | The Bleeding Edge (the next 10 years of SE analytics) |
Abstract“Are you up to date? Are you aware of the technologies that will define the next decade of Will this be an interesting talk? Can you skim these slides beforehand For answers to all these questions, and more, please come to my talk. ABSTRACT: Are you up to date? Are you aware of the technologies that will define the next decade of Will this be an interesting talk? Can you skim these slides beforehand For answers to all these questions, and more, please come to my talk. ” |
28/10/2021 | Lieck Robert | Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks |
AbstractRecursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars |
14/10/2021 | Simon Woodhead | Eedi and the NeurIPS Education Challenge Dataset |
AbstractAbstract: In 2020 the most popular competition at NeurIPS was the education challenge. We |
Date | Speaker | Topic | More Detail |
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24/06/2021 | Lenka Schnaubert | Cognitive awareness in digital and social learning environments |
AbstractDigital and social learning environments provide various opportunities to learn and interact |
10/06/2021 | Jim Ridgway, School of Education, Durham University | Firing up the Epistemological Engine |
Abstract” Conceptions of knowledge, ways of knowing, and uses for knowledge, are in a state of flux. We (Alexandra Cristea, Craig Stewart and Jim) have some IAS funding to begin work on the |
20/05/2021 | Filipe Dwan Pereira, postdoctoral researcher, Computer Science, Durham | Title: Towards AI-human hybrid online judges to support decision making for CS1 stakeholders |
AbstractAbstract: Introductory programming (also known as CS1 – Computer Science 1) may be complex |
06/05/2021 | Elad Yacobson, Weizmann Institute, Israel | Encouraging Teacher-sourcing of Social Recommendations Through Participatory Gamification Design |
AbstractTeachers and learners who search for learning materials in open educational resources (OER) |
25/02/2021 | Dr. Giora Alexandron, Weizmann Institute, Israel | What does your digital footprint say about you? (Machine Learning to understand Human Learning) |
AbstractThe high-resolution learner activity data that modern online learning environments collect |
18/02/2021 | Prof Tanja Mitrovic, Professor of Computer Science, Cantenbury University, New Zealand | Investigating the effect of voluntary use of an intelligent tutoring system on students’ learning |
AbstractNumerous controlled studies prove the effectiveness of Intelligent Tutoring Systems (ITSs). |
11/02/2021 | Noor Hasimah Ibrahim Teo | Ontological Approach for Automatic Question Generation |
AbstractA question is a powerful tool that is widely used in everyday activities for a different |
26/11/2020 | Konstantinos Nikolopoulos | Forecasting for big data: Does suboptimality matter? |
Abstractraditionally, forecasters focus on the development algorithms to identify optimal models and |
19/11/2020 | Daniela Romano, UCL; now Professor at De Montfort University | From Bio to BCI: extending human physical and mental capabilities |
Abstract“Imagine a world where we can think about moving a robotic arm and it happens. Play a video |
19/11/2020 | Kiran J. Fernandes | Using Gamification to create value in Business Models |
AbstractGamification is defined as using the motivational potential of digital game design to |
12/11/2020 | Timofeeva, Yulia, Professor of Computer Science, Warwick University | Computational modelling of neurotransmitter release |
Abstract“Abstract: |
05/11/2020 | Dr. Lada Timotijevic, Surrey University | Developing responsible governance for an e-infrastructure: the case study of the Determinants and Intake “Richfields” Data Platform |
AbstractBig data provides immense opportunities to radically alter the way in which science is done, |
21/10/2020 | Dr. Susanne Lajoie, Department of Educational & Counselling Psychology, McGill University, Canada |
Application of Cognitive Theories to the Design of Advanced Technologies for Learning. |
AbstractPsychological theories can inform the design of technology rich learning environments (TREs) |
08/10/2020 | James Sprittles | Computational Modelling of Free Surface Nanoflows |
Abstract“Understanding the behaviour of liquid-gas interfaces at the micro and nano scale is key to a As the characteristic scales of interest become comparable to microscopic scales, for a gas The majority of my talk will consider the influence of thermal fluctuations, which are seen If time permits, I will overview our work on capturing gas kinetic effects to predict the ” |
16/07/2020 | Yonina Eldar | From compressed sensing to deep learning: tasks, structures, and models |
Abstract“The famous Shannon-Nyquist theorem has become a landmark in the development of digital |
09/07/2020 | Jennifer Badham | Using agent-based modelling for COVID-19 social interventions |
AbstractAgent-based models represent the system being modelled in a specific way. In this seminar, I |
02/07/2020 | Tingwei Chen, visiting Professor, China | Time-Aware Attention Based Deep Neural Networks Model for Sequential Recommendation |
Abstract“Recommendation systems aim to assist users to discover most preferred contents from an In order to solve those problems, we propose two new models, named Dynamic Memory Preference |
25/06/2020 | Julita Vassileva, Professor in Computer Science, University of Saskatchetwan, Canada | Persuasive Technologies for Behaviour Change: Personalization and Ethical Issues |
Abstract“Persuasive Technologies (PT) apply strategies for influencing people’s choices and |
23/04/2020 | Jan Deckers, Newcastle | Should we develop AI systems to enhance human morality? |
AbstractAs the use of genetic biotechnology to make human beings more moral is dangerous, the |
02/04/2020 | Joseph P. Bullock | Using neural networks for high dimensional function interpolation and extrapolation |
AbstractIn many physical and theoretical calculations, multivariable functions, with non-trivial |
26/03/2020 | Christian Richardt | Towards reconstructing and editing the visual world |
Abstract“Abstract:I will be talking about some of my recent work on reconstructing and editing the ” |
12/03/2020 | Hubert Shum, Northumbria University | Human Movement Understanding for Visual Computing |
AbstractDue to the advancement in human motion/surface capturing technology and the availability of |
10/03/2020 | Harald Koestler | Whole-program Code Generation within ExaStencils |
Abstract“This work presents the ExaStencils code generation pipeline aimed at the development of CFD |
27/02/2020 | Eike Mueller, Bath | Fast semi-implicit DG solvers for fluid dynamics: hybridization and multigrid preconditioners |
Abstract“For problems in Numerical Weather Prediction, time to solution is A good spatial discretisation is equally important. Higher-order We show how this issue can be overcome by constructing a non-nested [1] Kang, Giraldo, Bui-Thanh (2019): “”IMEX HDG-DG: a coupled implicit [2] Cockburn, Dubois, Gopalakrishnan, Tan (2014): “”Multigrid for an HDG [3] Gibson, Mitchell, Ham, Cotter, (2018): “”A domain-specific language |
13/02/2020 | Marek Tokarski, Durham | Enabling Student Enterprise, Innovation and Creativity |
Abstract“This talk will give an overview of key opportunities provided by Careers & Enterprise to |
16/01/2020 | Joe Bullock, Dept Physics | Mapping Risks and Biases in AI Systems onto Human-Level Harms |
AbstractThe use of AI across academia, industry and the public sector is widespread. Inn addition, |
05/12/2019 | Gregoire Payen-de-la-Garander | Workshop on using massive data on the NCC NVidia cluster. |
Abstract“Focus on: |
07/11/2019 | Andreas Vlachidis, UCL | Using dates as contextual information for personalized cultural heritage experiences |
Abstract“Semantics can be engaged to promote reflection on cultural heritage by means of dates ” |
24/10/2019 | Charles Murray | Lazy Stencil Integration in multigrid algorithms |
AbstractMultigrid algorithms are among the most efficient solvers for elliptic partial differential |
10/10/2019 | Dave Braines, IBM | Conversational Explanations – Explainable AI through human-machine conversation |
Abstract“Explainable AI has significant focus within both the research community and the popular (for more details such as speaker bio and intended audience please refer to the CogSIMA 2019 |