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About

Isabelle Bloch is a leading researcher at the intersection of artificial intelligence, spatial reasoning, and medical imaging, with a particular focus on handling uncertainty and imprecision. Her foundational work in belief functions introduced novel methods for decomposing conflict as a distribution on hypotheses, a key contribution to the theory of evidence that has garnered 19 citations. In robotics, Bloch pioneered the use of fuzzy mathematical morphology and fuzzy spatial relations for robot mapping, demonstrating how approximate sensor data can be reliably represented and reasoned over—work that has accumulated 26 citations across two seminal papers. More recently, she has applied these computational techniques to precision surgery, including integrating tractography for pelvic surgery (10 citations) and developing 3D modeling and robotics for pediatric oncology (7 citations). Her research uniquely bridges theoretical advances in fuzzy set theory and evidence theory with practical, life-saving applications in image-guided surgery and autonomous robotics, making her a distinctive voice in computational intelligence and its clinical translation.