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SUMMARY:Women in Machine Learning Workshop 2026
DESCRIPTION:Image is AI generated.\n\n\n\nConnect\, collaborate\, and shape the future of Machine Learning. \n\n\n\nMachine Learning (ML) is at the forefront of technological development and is transforming fields ranging from healthcare and finance to security and transportation. As its influence on research\, industry\, and everyday life continues to grow\, it is increasingly important that diverse perspectives are represented in shaping its future. \n\n\n\nThe Women in Machine Learning Workshop brings together early career researchers in ML and AI. This workshop is specifically designed for women\, underrepresented gender groups\, and others with an interest in machine learning and increasing diversity in AI research. It creates a space to connect\, exchange ideas\, gain inspiration\, and build a stronger and more inclusive ML community. \n\n\n\nWhether you are new to Machine Learning or already working in the field\, the workshop offers an opportunity to meet researchers and students\, learn from invited speakers\, discuss experiences and ideas\, and discover ongoing research. \n\n\n\nThe workshop is organized as a lunch-to-lunch event and will include invited talks\, research presentations\, demonstrations\, discussions\, networking opportunities\, and a poster session. \n\n\n\nVenuesAda Lovelace\, House B\, Floor 2\, Linköping University MazeMapZero\, Zenit\, Floor 2\, Linköping University  MazeMap \n\n\n\nWho can participate? \n\n\n\nThe workshop is centered on women in Machine Learning and aims to support greater gender diversity in the field. We welcome participants who share this goal\, with a particular focus on women and underrepresented gender groups. \n\n\n\nThe workshop is especially relevant for students\, researchers\, and professionals who are interested in Machine Learning\, Artificial Intelligence\, Computer Vision\, Data Science\, and related technical fields. Participants at all stages\, from those who are new to the field to experienced researchers and practitioners\, are warmly welcome. \n\n\n\nNo specific level of experience is required. Whether you would like to learn\, share your work\, meet others in the community\, or simply explore opportunities in Machine Learning\, we encourage you to join us. \n\n\n\nInvited speakers\n\n\n\n\n\n\n\n\n\n\n\nEricka Johnson\, Deputy Head of the Department of Thematic Studies (TEMA)\, Linköping University\n\n\n\nTitle: GenAI and world-building with synthetic data \n\n\n\nAbstract: Synthetic data is used to assure privacy\, create portable data\, address data imbalances\, and amplify small datasets. But what is synthetic data? What does it represent? And is this even a relevant question? In this talk\, I will show you results from our experiments making synthetic tabular data\, discuss our work with data repositories trying to document it\, and open for a discussion on how domain experts from various fields are using it.     \n\n\n\nBio: Ericka Johnson is Professor of gender and society\, Linköping University\, Sweden\, and director of the Swedish national graduate school for the Wallenberg AI\, autonomous systems and software program – Humanity and Society. Her research focuses on how data represent the worlds and objects they claim to describe\, with a special interest in medical data. She has an interdisciplinary background in sociology\, gender studies\, and science & technology studies. Johnson is the author of several monographs and anthologies\, including How that Robot Made Me Feel (MIT Press 2025)\, and the recent Big Data & Society article (with Lee & Hajisharif) ‘The Ontological Politics of Synthetic Data’\, in which she details intersectional hallucinations. She is a member of the Royal Swedish Academy of Sciences.  \n\n\n\n\n\n\n\n\n\n\n\n\n\nEkta Vats\, Assistant Professor and Vice-Chair of WASP Diversity and Inclusion Group (DIG)\, Uppsala University\n\n\n\nTitle of talk: Teaching Multimodal AI to Know What It Doesn’t KnowAbstract: Modern AI systems increasingly need to reason across several kinds of data at once\, such as text\, images and video\, and to do so reliably in settings where mistakes carry real costs. This talk presents ongoing research on multimodal learning\, covering methods that combine vision and language\, and applications ranging from handwritten text recognition and the recovery of hidden text in historical manuscripts to problems in the life sciences. A recurring theme is trust: a model that confidently gets things wrong is often worse than one that admits it is unsure. We will show how uncertainty quantification can give multimodal models that kind of self-awareness\, and discuss what remains open.Bio: Ekta Vats is an Assistant Professor in Machine Learning and Docent in Computerised Image Processing at the Department of Information Technology\, Uppsala University\, and a Beijer Researcher at the Beijer Laboratory for Artificial Intelligence Research. Her research focuses on multimodal learning\, vision-language models and video-LLMs\, with applications spanning the life sciences and cultural heritage\, including multispectral imaging to uncover hidden texts in old manuscripts. She is a member and vice-chair of the WASP Diversity and Inclusion Group. \n\n\n\n\n\n\n\n\n\n\n\n\n\nLena Klasén\, Adjunct Professor\, Linköping UniversityTitle of talk: Using AI in Forensics \n\n\n\nAbstract: Digitalisation creates new forms of traces and growing volumes of information for criminal investigations. AI can help investigators search and compare digital traces\, forensic reports and witness accounts. Interactive 3D models place this information in the context of the crime scene. This talk follows our work from lidar-based crime scene documentation to interactive digital twins. Modelling human actions and visualising possible sequences of events help investigators and courts examine accounts\, test alternative explanations and understand complex material. A cold-case murder investigation shows how a large language model can support questions about documentary material alongside a 3D reconstruction. It also illustrates how question wording\, source selection and model errors can influence the answers and their interpretation. We examine what responsible AI use requires\, including validation\, traceability\, visible uncertainties and documented human review. The distinction between what AI suggests and what the expert concludes must remain clear. In court\, we must be able to explain what we did\, how we checked the results and why we considered them reliable. \n\n\n\nCV Dr. Lena Klasén: Dr. Lena Klasén is Adj. Professor in Digital Forensics at Information Coding (ICG)\, Department of Electrical Engineering\, Linköping University\, Sweden\, since 2020. She has been Senior Expert at Santa Anna IT Research Institute since May 2026\, and a co-founder of Digital Forensics Sweden. From 2015 to 2018 she was Director of the Swedish National Forensic Centre (NFC) and part of the National Police Commissioner’s strategic and operational top management teams. She then served as Director of Research at the Swedish Police Authority’s Department of National Operations. Dr. Klasén holds a PhD in Image Coding from Linköping University. She has led industrial and research organisations and held senior roles at Saab AB\, the Swedish Defence Research Agency (FOI)\, the Swedish Defence Materiel Administration (FMV)\, the Swedish National Laboratory of Forensic Science (SKL) and the Implementing Committee of the New Police Organisation at the Swedish Ministry of Justice. Her industrial experience includes product portfolio management at Saab\, three patents\, and founding and co-founding several innovative companies. She has served as a forensic expert in major investigations\, including the Waco investigation for the US Department of Justice. She is a Fellow of the Royal Swedish Academy of Engineering Sciences (IVA) and the Royal Swedish Academy of War Sciences. \n\n\n\n\n\nProgram\n\n\n\nWomen in ML programDownload\n\n\n\nContact\n\n\n\nThe workshop is organized by representatives from Linköping University\, in collaboration with WASP Diversity and Inclusion Group. \n\n\n\nFor questions about the workshop\, registration\, or participation\, please contact: \n\n\n\nAmanda Berg\, amanda.berg@liu.se.
URL:https://wasp-sweden.org/event/women-in-machine-learning-workshop-2026/
LOCATION:Linköping University\, Campus Valla\, Olaus Magnus väg\, Linköping\, 583 30\, Sweden
CATEGORIES:Workshop
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DTSTART;TZID=Europe/Paris:20261201T090000
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SUMMARY:Hackathon: AI agents transforming life sciences\, medicine\, and healthcare
DESCRIPTION:Join us on 1 December 2026 for a hackathon focused on developing AI agents for applications in life sciences\, medicine and healthcare. There is a lot happening in the agentic AI sphere right now\, and many people have great ideas or knowledge that can be exchanged. We hope that during this event we can build interesting things together\, share knowledge with each other\, and network. \n\n\n\nThe hackathon is open to members of the SciLifeLab\, DDLS and WASP communities and is jointly organised by SciLifeLab\, WASP Research Arena WARA Medicine and the DDLS Cell and Molecular Biology research area. \n\n\n\nEveryone is welcome to join\, whether you have a specific idea for something to build or you simply want to join and build together with others. In the registration form we will ask you to share interests or propose ideas for a project\, and we will do our best to create teams based on the ideas and interests. If you have already formed a team with which you will work\, you can indicate this in the registration form. There will also be opportunities to form or adjust teams at the beginning of the day.  \n\n\n\nDuring the hackathon\, participants will get API keys to access Claude and open weight models hosted by SciLifeLab. We will also facilitate hosting of your tools on the SciLifeLab Kubernetes cluster if needed.We will start the day with breakfast and pitches of various ideas (pre-submitted or spontaneous). We will end the day with pizza for everyone. We can accept up to 70 participants. If you have questions or suggestions\, get in touch with us: datacentre@scilifelab.se \n\n\n\n\nRegister here\n\n\n\n\nRegister before November 20 (17:00).  \n\n\n\n\n\n\n\nCancellation\n\n\n\nTo help us minimise empty seats and food waste\, please cancel your registration if you are no longer able to attend the event. If a waiting list is active\, this will allow us to offer your place to another participant. Timely cancellations also help us avoid unnecessary costs for refreshments and lunch.If you have questions or suggestions\, please get in touch with us: datacentre@scilifelab.se
URL:https://wasp-sweden.org/event/hackathon-ai-agents-transforming-life-sciences-medicine-and-healthcare/
LOCATION:Samuelssonsalen\, Tomtebodavägen 6\, Karolinska Institutet\, Tomtebodavägen 6\, Stockholm\, 171 65\, Sweden
CATEGORIES:Workshop
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