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AI Lund Lunch seminar: Tracing Industrial Change Over Time: Harmonizing Industry Classifications in Swedish Register Data for Machine Learning
“A Chip Odyssey” – how Taiwan became the world leader in semiconductors
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Sharing session: "The Upheaval"
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Mindful Image and Unique Beauty produced by Inês Paiva and Natalie Schäfer
Mindful Image and Unique Beauty produced by Inês Paiva and Natalie Schäfer
LU-TBI lab - Lunds laboratorium för neurokirurgisk hjärnskadeforskning
Traumatisk hjärnskada (THS) är en vanlig orsak till död och kvarstående handikapp och idag saknas effektiva behandlingar. Vår forskargrupp använder experimentella och kliniska tekniker att studera THS, från de allra svåraste skadorna till de mer milda skadorna som kan ses exempelvis efter hjärnskakning inom idrotten. Hjärnans egen förmåga till läkning är begränsad efter THS och ett viktig mål för Traumatic brain injury (TBI) is a common cause of death and disabilities and current treatment options are limited. The research group uses experimental and clinical approaches to study TBI, from the most severe brain injuries to the milder sport-related concussions. The brain´s own capacity for repair is poor and one research aim is to enhance brain recovery and repair following injury. TBI is al
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Maryam Hashempour - Final Attachment
Perceptual Engineering: How can we engineer human perception? - fika-to fika in Lund
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Protein kinase C (PKC) plays a prominent role in immune signaling, and the paradigms for isoform selective signaling are beginning to be elucidated. Real-time microscopy was combined with molecular and biochemical approaches to demonstrate a role for PKC-epsilon in Fcgamma receptor (FcgammaR)-dependent phagocytosis. RAW 264.7 macrophages were transfected with GFP-conjugated PKC isoforms, and GFP m
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Maryam Hashempour - Final Attachment
Machine Learning and Formal Methods
10 juni 2026 12:00 till 17:00 | Seminarium The adoption of Artificial Intelligence (AI) and Machine Learning (ML) presents several challenges, among which the lack of trust in the decisions made by such systems remains a major concern. Formal methods have historically provided the foundation for rigorously verifying software systems, and they could play a key role in fostering trust in AI/ML techn
https://www.lu.se/evenemang/machine-learning-and-formal-methods - 2026-07-01
