seminars
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Learning analytics that facilitate meaningful learning experiences
Abstract: The focus of education is shifting from outcomes to processes. How do learners make sense of new challenges, and how can such sense-making be identified and supported? In this talk, I will demonstrate how the use of learning analytics and digital trace analysis, coupled with innovative design and strong theoretical foundations, allows us to… Continue Reading Learning analytics that facilitate meaningful learning experiences
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Robust and Actionable ML via Causality
Abstract: Artificial Intelligence is increasingly deployed in high-stakes fields such as healthcare, where two critical challenges emerge: models must generalize to real-world variations and their predictions must be actionable for decision-makers. The generalization challenge arises when AI is applied to data that differs from its training set, a phenomenon known as distribution shift. The actionability challenge… Continue Reading Robust and Actionable ML via Causality
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Robust and Actionable ML via Causality
Abstract: Artificial Intelligence is increasingly deployed in high-stakes fields such as healthcare, where two critical challenges emerge: models must generalize to real-world variations and their predictions must be actionable for decision-makers. The generalization challenge arises when AI is applied to data that differs from its training set, a phenomenon known as distribution shift. The actionability challenge… Continue Reading Robust and Actionable ML via Causality
people
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بيهار يواخيم
Associate Professor Joachim A. Behar joined the faculty of Biomedical Engineering in 2029 and the faculty of Data and Decision Sciences in 2025. He received his Ph.D. in Biosignal Processing and Medical Machine Learning from Oxford University in 2015. has held a Post-Doctoral position at the Technion during the years 2015-2018 in mathematical modelling. His research… Continue Reading بيهار يواخيم
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