[Probabilidad-Estadistica-Seminario] Seminario de Probabilidad y Estadística - Sam Perochon (Ecole Normale Supérieure Paris-Saclay)

[seminarios en cmat.edu.uy]

Seminario de Probabilidad y Estadística
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Título: "Recent advances of AI in health: computational approaches for the screening and monitoring of autism spectrum disorder, dysexecutive syndromes, and cardiovascular health."

Expositor: Sam Perochon (Ecole Normale Supérieure Paris-Saclay)

Resumen:
 
This presentation will focus on computational behavioral phenotyping,
illustrating how machine learning (ML) methods can be leveraged to transform raw
complex multimodal health data into objective and interpretable biomarkers. I
first present computer vision and ML algorithms that (i) extract digital
behavioral biomarkers from video and gamified visuomotor assessments and (ii)
combine them for early autism screening. I then describe computational
approaches for analyzing egocentric video to characterize the execution of a
chocolate cake cooking task, by producing compact symbolic representations of
behavioral trajectories that enable alignment and comparison across patients
with sensorimotor and executive disorders. Finally, I present a methodology for
learning compact and generalizable representations of wearable biosignals to
improve the sensitivity to subtle cardiovascular health changes.

[1] Perochon S., Di Martino J.M. et al. A scalable computational approach to
assessing response to name in toddlers with autism. J Child Psychol Psychiatr
(2021).

[2] Perochon S., Di Martino J.M.   et al.   A tablet-based game for the
assessment of visual motor skills in autistic children.   npj Digit. Med.
(2023).

[3] Perochon, S., Di Martino, J.M.   et al.   Early detection of autism using
digital behavioral phenotyping.   Nat Med.   (2023).

[4] Perochon S., Oudre L. Recursive prototyping for computational behavior
analysis from egocentric videos. In review at ICPR 2026

[5] Perochon, S.   et al.   Time-varying representations of longitudinal
biosignals using self-supervised learning. NeurIPS 2024 Workshop: Self-
Supervised Learning-Theory and Practice .
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Viernes 17/4 a las 10:30, FCEA: Salón 1 del EIP (entrada por Lauro Müller)

Contacto: Laura Aspirot - laspirot en gmail.com
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https://salavirtual-
udelar.zoom.us/j/87033011104?pwd=qnKGw4syp4Izilf5QekV7Ama7oyjXZ.1
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