Overview

Melanie Segado

PhD. Neuroscience, McGill University

> About Me

I am an applied AI researcher in Konrad Kording’s lab at the University of Pennsylvania. Currently I am working on data-driven, explainable machine learning for clinical risk prediction, multimodal AI (LLM/ViT/VLM) post-tuning for scalable integration of tacit knowledge, and self-supervised representation learning for movement foundation models.

> Research Interests

Embodied AI, movement & behavior
Safe, trustworthy AI
Machine learning for healthcare
Neuroscience & neurotechnology

> Highlighted Papers

A Pre-Registered, Open Pipeline for Early Cerebral Palsy Risk Assessment from Infant Videos
M Segado, LA Prosser, AF Duncan, MJ Johnson, KP Kording

GigaScience (provisional) 2026 [paper] [code] [dataset]

Grounding Intelligence in Movement
M Segado, F Parodi, JK Matelsky, M Platt, EL Dyer, KP Kording

arXiv 2025 [paper]

PrimateFace: A Machine Learning Resource for Automated Face Analysis in Human and Non-human Primates
F Parodi, JK Matelsky, A Lamacchia, M Segado ... M Platt, KP Kording

bioRxiv 2025 [paper] [code] [dataset]

Effector-Independent Brain Network for Auditory-Motor Integration: fMRI Evidence from Singing and Cello Playing
M Segado, VB Penhune, RJ Zatorre

NeuroImage 2021 [paper][dataset][youtube]

An Integrated Platform Combining Immersive Virtual Reality and Physiological Sensors for Systematic and Individualized Assessment of Stress Response (bWell)
B Khundrakpam, M Segado, J Pazdera, V Gagnon Shaigetz, JA Granek, N Choudhury

JMIR Formative Research 2025 [paper]

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