Lecturer: Terrence Stewart Fields: Computational Neuroscience, Neuroscience, AI
Content
This course provides an overview of computational neuroscience, the science of creating computer simulations of neurons, groups of neurons, and different brain systems, and then comparing the results of these simulations to the behaviour of real brains. This lets us better understand how brains work, and it also has the potential of inspiring new types of Artificial Intelligence systems.
We start by looking at individual neurons and their details, then move to the three major approaches to making large-scale models capable of producing detailed behaviour: Parallel Distributed Processing (PDP++/Emergent), Dynamic Neural Fields (DNF/Cedar), and the Neural Engineering Framework (NEF/Nengo). Python notebooks will be provided for hands-on examples.
Session 1: Individual neurons Session 2: Many neurons in parallel (PDP++) Session 3: Dynamic Neural Fields (DNF) Session 4: The Neural Engineering Framework and Nengo
Literature
Kriegeskorte, N., & Douglas, P. K. (2018). Cognitive computational neuroscience. Nature neuroscience, 21(9), 1148–1160. https://doi.org/10.1038/s41593-018-0210-5
Rumelhart, D., & McClelland, J., (1986). Parallel distributed processing: Explorations in the microstructure of cognition. MIT Press, Cambridge, MA, USA
Schöner, G. (2023). Dynamical Systems Approaches to Cognition. In Sun, Ron (Ed.), The Cambridge Handbook of Computational Cognitive Sciences (2nd ed.). Cambridge University Press.
Stewart, T.C., & Eliasmith, C. (2014). Large-scale synthesis of functional spiking neural circuits. Proceedings of the IEEE, 102(5):881–898.
Lecturer
Terry Stewart is a Senior Research Officer at the National Research Council Canada, and Site Lead of the NRC-University Waterloo Collaboration Centre. His research includes large-scale brain simulation, cognitive modelling, energy-efficient neuromorphic computing, and AI safety.
Lecturer: Mike Ambinder Fields: BCI, Video Games, Neuroscience, AI, ML, Engineering
Content
This course will cover one possible future for video game play. At the moment, video games provide a dynamic experience on several axes, but they remain relatively static with respect to the individual player experience. They are designed for the collective – they do not adapt. With the advent of improved hardware, statistical techniques, and advances in game design, the potential exists to design a new generation of gameplay where the experience is tailored to the individual as a consequence of physiological measurement of internal state. Under this framework; games may become capable of a whole lot more than entertainment.
Dr. Mike Ambinder received a BA in Computer Science and Psychology from Yale University and a PhD in Psychology (Visual Cognition) from The University of Illinois. He spent 15 years at Valve leading research efforts in applied psychology and game design, statistics, machine learning, and AI, economic systems design, and Brain-Computer Interfaces. He is currently the Chief Research Officer of Cognitive Explorations, a design consultancy in the games space, and the Chief Research Officer of August Interactive, a gaming startup with a focus on prosocial behavior change.
Affiliation: Cognitive Explorations, LLC; University of Washington; August Interactive
Lecturer: Timothy Drysdale Fields: Artificial intelligence, education, practical work
Content
This evening talk will reflect on the challenge facing educators, particularly younger educators with many years of teaching ahead of them. The joint pressure of readily-available artificial intelligence affecting the validity of traditional processes, and massification of education reducing the resources available per student, pose a difficult pinch point that is generating demand for authentic, interactive activities but placing a lot of pressure on the available time and space for students to experiment with real equipment in a traditional manner. I\’ll introduce a solution in the form of laboratories in a box, which we have been doing doing at the University of Edinburgh for a number of years, and describe the elements that make these successful for us, how you can adopt a similar approach, the pitfalls to avoid and some fruitful future directions for our communities of educators to explore, in particular in expanding what we do with the data streams to support better learning and in taking our concept of experiments beyond what we are used to doing in traditional laboratories.
Literature
Reid, D., & Drysdale, T. (2024). Student-facing learning analytics dashboard for remote lab practical work. IEEE Transactions on Learning Technologies, 17, 1037-1050. https://doi.org/10.1109/TLT.2024.3354128
D.Reid, J. Burridge, D. Lowe, T. Drysdale “Open-source remote laboratory experiments for controls engineering education,” International Journal of Mechanical Engineering Education. February 2022. doi:10.1177/03064190221081451
T. D. Drysdale, S. Kelley, A.-M. Scott, V. Dishon, A. Weightman, R. J. Lewis & S. Watts “Opinion piece: non-traditional practical work for traditional campuses,” Higher Education Pedagogies, 5:1, 210-222, 2020, DOI: 10.1080/23752696.2020.1816845
G. L. Knight & T. D. Drysdale The future of higher education (HE) hangs on innovating our assessment – but are we ready, willing and able?, Higher Education Pedagogies, 5:1, 57-60, 2020, DOI: 10.1080/23752696.2020.1771610
Lecturer
Prof Timothy Drysdale is the Chair of Technology Enhanced Science Education and Director of Strategic Digital Education in the School of Engineering. His main research activity is in Engineering Education, where he leads the Remote Laboratories group. He and his team have developed an entirely new infrastructure and approach for operating online remote laboratories on traditional campuses (practable.io), winning international awards from the Global Online Laboratories Consortium (Remote Experiment Award 2024) and the Association for Learning Technology / Jisc Award for Digital Transformation in 2023. His prior research activities were in the area of terahertz component design and testing, microwave antennas, and optical plasmonics. He has a long-standing involvement with public outreach in science and engineering, including the Royal Society Summer Science Exhibition, Science Day at Buckingham Palace, and giving the Isambard Kingdom Brunel Award Lecture at the British Science Festival.
Lecturer: Jutta Kretzberg, Katja Hellekes Fields: Personal / professional development
Content
Are you a student? Have you ever considered doing a PhD? Or a career in academia? Does the idea of doing a PhD appeal to you? Or does it seem like hard work, or even a painful experience? Many Master’s students struggle with the decision of whether a PhD would be the right choice for their career. In fact, a significant proportion of PhD students continue to question their decision until they graduate, and sometimes even afterwards. There is no general advice on who should pursue a PhD. Whether to pursue a PhD is a personal decision that depends on factors such as your personality, personal situation, and the job opportunities available. The aim of this workshop is to help you develop a clearer personal perspective on this decision.
This workshop is primarily aimed at Master’s and advanced Bachelor’s students. However, the method of developing your personal perspective can also be applied to future career steps. PhD students, PhD holders and non-PhDs who are willing to share their perspectives are highly welcome!
Session 1: Background information In the first session, we will begin by providing some background information on undertaking a PhD in Germany or Austria. What are the motivations for pursuing a PhD? What skills are gained through a PhD? How can a PhD be structured and funded? How do PhDs differ between disciplines and countries?
Session 2: External perspectives In the second session, we will explore the different stakeholders’ perspectives interactively. What do Master’s students expect from a PhD? What do PhD supervisors expect from their students? What do employers expect from PhD versus Master’s degree applicants? What about the perspective of family and friends? And which personality traits might be useful for pursuing a PhD?
Session 3: Your personal perspective During the third session, you will write down your hopes, neutral expectations and fears relating to a PhD. Working with a fellow participant, categorize these into the groups: ‘tasks/skills’, ‘topics/scientific questions’, ‘working environment’ and ‘personal factors’. Sharing your thoughts and listening to those of your teammate can help you gain a clearer perspective on your career decisions.
Session 4: How to become a PhD candidate? After sharing our conclusions from the previous sessions, we will discuss the practical steps involved in becoming a PhD candidate, such as: How do you choose a topic? How do you find a project and a supervisor? How can you finance the PhD? We will also consider how to balance the demands of your PhD with your personal life – bridging realities of your live and a PhD.
Literature
The European Competence Framework for Researchers: https://research-and-innovation.ec.europa.eu/document/download/7da29338-37bf-4d51-b5eb-a1571b84c7ad_en?filename=ec_rtd_research-competence-presentation.pdf
General information on PhD scholarships (by German Government): https://www.bmbf.de/EN/Research/ScienceSystem/AcademicCareers/DoctoralScholarships/doctoralscholarships_node.html
General information on German academic system & funding for international exchange (DAAD): https://www.daad.de/en/
Largest scholarship organisation in Germany: https://www.studienstiftung.de/en/doctoral-scholarships/doctoral-scholarships
Chris Woolston: “Graduate survey: A love-hurt relationship” Nature 550, 549-552 (2017)
https://www.nature.com/articles/nj7677-549a https://doi.org/10.1038/nj7677-549a (Nature’s survey of more than 5,700 doctoral students worldwide)
Lars Kiewidt, PhD: “To PhD or not to PhD?” (2019) https://medium.com/age-of-awareness/to-phd-or-not-to-phd-4312cdb862c5 (Evaluation of this survey data set concerning PhD student’s motivation, skills and satisfaction across fields in natural sciences.)
Chris Woolston: ‘I don’t want this kind of life’: graduate students question career options
Nature 611, 413-416 (2022) doi: https://doi.org/10.1038/d41586-022-03586-8 (Newest version of nature’s PhD survey, but not open access)
Katie Mitzelfelt, PhD: “To Be or Not To Be a PhD Candidate, That Is the Question” (Association for Women in Science Magazine, 2021): https://awis.org/to-phd-or-not-phd/ (Individual perspectives of 6 persons on their own decision to be or not to be a PhD.)
Charlotte King_: “To PhD or not to PhD, that is the question…” https://www.postgrad.com/blog/to-phd-or-not-to-phd/ (Rather old, but still helpful blog post)
Lecturer
Jutta Kretzberg is professor for Computational Neuroscience and head of the MSc program Neuroscience at University of Oldenburg. She studied applied computer science and biology at University of Bielefeld, where she also did her PhD in Biology. After being a postdoc (and having a baby) in San Diego, California, she came back to Germany to be a junior professor and became a professor some years (and another baby) later. Nowadays, while juggling her family, teaching, research and administration duties, her favorite task is mentoring.
Katja Hellekes, is an experienced academic professional and Coordinator of the Vienna Doctoral School Cognition, Behavior and Neuroscience. She completed her diploma and doctorate at the University of Cologne, specializing in Neurobiology, followed by postdoctoral research at the Institute of Molecular Pathology (IMP) and the University of Freiburg. Alongside her role as Coordinator of the Doctoral Program, Katja Hellekes lectures in cognitive science. With a passion for fostering the growth of early-career researchers, she provides dedicated support to PhD candidates, guiding them through their doctoral journey and helping them transition into independent research roles.
Lecturer: Jennifer Fewell Fields: Biology; Collective Behavior
Content
This course will explore the social organization and collective behavior of social insects from a biological perspective. The social insects are models for coordination and cooperation across small to large scales. Their distributed communication systems have been used extensively as inspiration for applied questions in coordination and collective behavior, from supply chains to robotics and beyond. Is a social insect colony the original collective \”AI\”? – well probably not, but it will be a fun question to explore!
Lecturer
Jennifer Fewell is a President\’s Professor at Arizona State University, where she served as the founding Director of the Center for Social Dynamics and Complexity. She has served also as President of the Animal Behavior Society and the International Union for the Study of Social Insects. She studies social organization and division of labor in social insects, and mechanisms and evolution of social cooperation across a range of species. She received her MS and PhD from the University of Colorado.
Lecturer: Stephane Baele Fields: AI, Political Science, Social Theory, History
Content
This course proposes to hit, for 270 minutes, the “pause” button in the relentless, high-paced development of Artificial Intelligence, to critically think of the political underpinnings and implications of the technology.
Specifically, it seeks to highlight the profound connection between (any) technology and power in order to unpack the various ways through which progress in AI cannot be separated from social and political hierarchies, state power and its often violent contestations, individual freedoms, and the international system.
The three sessions of the course explore this issue by unearthing what we could imagine as the three layers of the power/technology relationship (as applied to AI), from the most superficial to the most fundamental. First, we reflect on the issue – and very idea of – AI (and other technologies) “dual-uses”, using the case of extremist and terrorist uses of AI as a case-study. Second, this allows us to problematise, from various historical perspectives, the strengthening or weakening of state power in the AI “revolution”. Finally, we leverage a couple of classic social theory frameworks to interrogate the very nature and position of technique in society and how AI merely represents the latest stage of a much larger current of modernity.
Session 1: The problem with AI “dual-uses”: AI terrorism and extremism. Session 2: AI, technology, and state power: A historical perspective. Session 3: Questioning technique, progress, and power at the age of the AI “revolution”.
Literature
Baele S. (2026) Generative Artificial Intelligence. In Lakhani S., Macdonald S., Droogan J., Khalil L. (eds.) Routledge Handbook of Online Violent Extremism. London: Routledge.
Baele S., Brace L. (2024) AI Extremism. Technologies, Tactics, Actors. Dublin: VOX-Pol.
Giattino C., Mathieu E., Samborska V., Roser M. (2023) Artificial Intelligence, OurWorldInData.org.
Ellul J. (964) The Technological Society. New York: Vintage Books.
Headrick D. (2009) Technology: A World History. Oxford: Oxford University Press.
Hegghammer T. (2021) Resistance Is Futile. The War on Terror Supercharged State Power. Foreign Affairs 100(5): pp.44-53.
Rassler D., Veilleux-Lepage Y. (2024) The Paradox of Progress: How ‘Disruptive,’ ‘Dual-use,’ ‘Democratized,’ and ‘Diffused’ Technologies Shape Terrorist Innovation. Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis 33(2): 22-28.
Tilly C. (1990) Coercion, Capital, and European States, AD 990-1990. Cambridge, Mass.: Blackwell.
Lecturer
Stephane J. Baele is Professor of International Studies at UCLouvain, Belgium, and Honorary Associate Professor in Security and Political Violence at the University of Exeter, UK. He has written extensively on extremist and violent political actors\’ communications, using in-depth empirical analysis of cases ranging from Islamic State\’s propaganda to white supremacists\’ online forums to offer novel perspectives on radicalization, digital extremism, and linguistic and visual expressions and drivers of violence. Besides academia, he regularly supports counter-terrorism/extremism agencies in various ways and loves to run on wild trails.
Lecturer: Christian Herff Fields: Machine Learning, Signal Processing, Neural Data
Content
This course will cover the field of Brain-Computer Interfaces that decode speech directly from invasive neural activity.
Session one will introduce different measures of invasive neurophysiology and highlight the state of the art in speech BCIs.
Session two, we will look at intracranial data directly and realize a first decoding system.
Session three is dedicated to open challenges and future directions.
Literature
Silva, A. B., Littlejohn, K. T., Liu, J. R., Moses, D. A., & Chang, E. F. (2024). The speech neuroprosthesis. Nature Reviews Neuroscience, 25(7), 473-492.
Lecturer
Christian Herff is an Associate Professor in the Department of Neurosurgery, where he leads the research program on invasive brain–computer interfaces (BCIs). With a background in computer science, he bridges technical innovation and clinical application to drive some of Europe’s most advanced work in neural interfaces. His leadership in the field is reflected in his election to the Board of the BCI Society, where he represents invasive BCI research.
Lecturer: Cosima Prahm, Michael Bressler Fields: Computer Science, Biology, Medicine
Content
In this hands-on course, participants will explore how body and brain signals can be used as inputs for immersive interactive applications or games. After a short introduction to physiology and measurement of muscle activity (EMG), brain activity (EEG), heart activity (EKG) as well as user interface design principles and gamification, we will provide a tutorial on the Unity game engine and prefabs for signal processing and interaction design. Using provided hardware, participants will work in a maximum of 5 small teams consisting of 3-4 people to prototype applications using the Unity Game Engine to integrate physiological signals into XR/VR scenarios. Sessions will be structured as hackathon-style workshops, combining brief input lectures, supervised technical guidance, and plenty of time for experimentation. The course will conclude with team presentations in which groups pitch and demo their applications to fellow IK participants and a small jury. The emphasis is on creativity, collaboration, and gaining hands-on experience in turning physiological signals into novel forms of human–computer interaction.
Provided Hardware: – Meta Quest 3/3S (XR/VR Headset with optical hand tracking) – MyoArmband (EMG Bracelet) – Muse S (EEG Headband) – Polar Belt (EKG Chest Belt)
Description for every course Session:
Session 1: Introduction to physiological signals (EMG, EEG, EKG), user interface design and gamification. Overview of measurement devices, introduction to VR/AR/XR, Hardware setup, Unity tutorial, team formation.
Session 2: Prototyping session I – connecting devices, first experiments with devices, developing creative concepts.
Session 3: Prototyping session II – refining signal integration, debugging, testing interaction concepts.
Session 4: Prototyping session III – polishing prototypes, preparing demos and pitches.
Presentation: Final presentation (short PPT as introduction of the team and the project, followed by a demo)
Cosima Prahm graduated from the Medical University Vienna, Austria, in 2019 with a PhD in Medicine – Clinical Neuroscience. During that time, she was a research assistant at the Clinical Laboratory for Bionic Extremity Reconstruction and Rehabilitation lead by Prof. Aszmann at the Medical University in Vienna, at the Clinical Laboratory for Bionic Limb Reconstruction, Austria. At the University of Tuebingen, Germany, she was head of research of the laboratory for Hand, Plastic, Reconstructive and Burn Surgery while actively conducting research herself in both clinical projects and in the field of TechNeuroRehabilitation, where she also established the working group PlayBionic that focuses on digital health applications. She is now working at the Clinic for Hand, Replantation and Microsurgery, Charité University Medicine, and is the director of the Center for Clinical Research at the occupational trauma hospital Unfallkrankenhaus Berlin.
Affiliation: Charité – University Medicine Berlin Homepage:www.playbionic.org
Michael Bressler finished his Master’s degree in Information Technology at the Vienna University of Technology with a focus on human-computer interfaces and user interface design. After several years in the private sector, he returned to research, where he mainly focuses on computer-assisted rehabilitation, virtual and augmented reality, and serious games for health.
Affiliation: BG Klinikum Unfallkrankenhaus Berlin, Zentrum für Klinische Forschung Homepage:www.michaelbressler.at
With a focus on cybernetics and the free energy principle, this course will cover how philosophers and theoretical biologists have attempted to define the unique organisational properties of living systems, the unique difficulties of identifying invariant properties that individuate an organism over time, and how to understand the nature of mathematical models in light of these challenges.
1. Session one will begin with a brief discussion of Aristotle’s philosophy of biology and his account of animal motion, which will provide context for discussion of the cybernetic account of living systems as feedback control systems. 2. Session two will cover the Free Energy Principle as a contemporary revival of the cybernetic picture and explore some of its limitations as a ‘first principle’ for living systems. 3. Session three will introduce an alternative ‘processual’ perspective on the organism and the discuss the limitations this places on our ability to formally describe the essential features of an individual living system.
Literature
Dupré, J. A., & Nicholson, D. J. (2018). A manifesto for a processual philosophy of biology.
Dupuy, J.-P. (2009). On the origins of cognitive science: The mechanization of the mind. MIT Press.
Nave, K. (2025). A drive to survive: The free energy principle and the meaning of life. The MIT Press.
Lecturer
I am a Leverhulme Trust early career research fellow. My research focuses on developing a realist account of autonomy and agency, grounded in the uniquely metabolic existence of living systems, and upon critiquing the machine concept of the organism in light of this distinctive material instability.
Lecturer: Sarah Hayes Fields: Postdigital Inequalities, Artificial Intelligence, Sociology, Bioinformational Philosophy, Human Data Interaction, Ethics,
Content
This course, under the theme: Societies and Blurred Realities, examines postdigital inequalities , as these arise in different contexts, as a result of technologies that merge physical and virtual spaces, bioinformational data and human and artificial intelligence. Beginning with exploring our own postdigital positionalities (Hayes, 2021), where technology, language and our brains merge in our hybrid environments, we question how AI comes to reflect the values and inequities of the world in which it is created. Our changing digital identities, amid data-centric biology, are considered through research that examines the infrastructuring of educational genomics (Williamson, et. al., 2024).. Amid the uncertainty of AI mediation, our human data interactions and skills are explored to seek greater Agency, Legibility and Negotiability for postdigital inclusion of those who are marginalised (Hayes, et. al., 2023). Finally, we consider creative and innovative cross-sector partnerships that build from the ground in communities. A range of recent examples will be discussed, including citizen research and activism, collective articles, community innovation hubs and examining how universities might be centres of postdigital knowledge and collaboration, contributing to local and regional development by aligning their research with real-world policy needs.
Session 1 will cover: Postdigital positionality, where technology, language and our brains merge Session 2 will cover: Digital identity: what exactly do we mean by this in a bioinformational society? Session 3 will cover: Human Data Interaction, disadvantage, skills in the community, towards Ethtech Session 4 will cover: Creative approaches to address postdigital inequalities and regain ourselves
Literature
Costello, E. (2024). Rewild my heart: With pedagogies of love, kindness and the sun and moon. Postdigital Science and Education, 6(2), 610-626.
Hayes, S., Connor, S., Johnson, M. and Jopling, M. (2023). Human Data Interaction, Disadvantageand Skills in the Community: Enabling Cross-Sector Environments for Postdigital Inclusion. Cham: Springer.
Hayes, S. (2021). Postdigital positionality: Developing powerful inclusive narratives for learning, teaching,research and policy in Higher Education. Leiden: Brill.
Hayes, S., Jandrić, P., la Velle, L. et al. (2024) Postdigital Citizen Science and Humanities: Dialogue from the Ground. Postdigit Sci Educ 7, 188–223. https://doi.org/10.1007/s42438-024-00514-z
Jandrić, P., Ryberg, T., Knox, J., Lacković, N., Hayes, S., Suoranta, J., Smith, M., Steketee, A., Peters, M. A., McLaren, P., Ford, D. R., Asher, G., McGregor, C., Stewart, G., Williamson, B., & Gibbons, A. (2019). Postdigital dialogue.Postdigital Science and Education, 1(1), 163-189. https://doi.org/10.1007/s42438-018-0011-x
Kourkoulou, D., Tzirides, A.-O., Cope, B., & Kalantzis, M. (Eds.). (2024). Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines. Cham: Springer. https://doi.org/10.1007/978-3-031-64487-0.
Kotouza, D. (2025). Genetics for ‘equality’? The politics of knowledge production in educational genomics. History of the Human Sciences, 09526951251314314.
Matthewman S (2011) Technology and Social Theory. Basingstoke: Palgrave Macmillan.
Pangrazio, L., & Sefton-Green, J. (2023). Digital literacies as a ‘soft power’of educational governance. In World Yearbook of Education 2024 (pp. 196-211). Routledge.
Peters, M. A., Jandrić, P., & Hayes, S. (Eds.). (2022). Bioinformational philosophy and postdigital knowledge ecologies. Cham: Springer.
Raffaghelli, J.E., Ferrarelli, M. & Rodríguez, N.L. (2025) Slowness as Postdigital Positionality in the Era of Generative AI: A Conversation. Postdigital Science and Education
Reardon, J. (2019). The postgenomic condition: Ethics, justice, and knowledge after the genome. University of Chicago Press.
Ritzer, G., Ryan, J. M., Hayes, S., Elliot, M., & Jandrić, P. (2024). Epilogue: McDonaldization and Artifcial Intelligence. In D. Kourkoulou, A.-O. Tzirides, B. Cope, & M. Kalantzis (Eds.), Trust and Inclusion in AI-mediated Education: Where Human Learning Meets Learning Machines (pp. 303-321). Cham: Springer.
Williamson, B., Kotouza, D., Pickersgill, M., & Pykett, J. (2024). Infrastructuring educational genomics: Associations, architectures, and apparatuses. Postdigital Science and Education, 6(4), 1143-1172.
Lecturer
Sarah Hayes, PFHEA, is Professor of Education & Research Lead at Bath Spa University. Her PhD was in Sociology, from Aston University, UK, and her research includes linguistic analysis of policy and examining society through a postdigital lens. Sarah wrote: ‘The Labour of Words in Higher Education’ (2019), ‘Postdigital Positionality’ (2021) and co-edited ‘Bioinformational Philosophy and Postdigital Knowledge Ecologies (2022) and the EPSRC funded Human Data Interaction, Disadvantage and Skills in the Community. She has taught Sociology, Education and Computing, and is an Associate Editor for the Springer journal: Postdigital Science and Education.
