Aerospace Medicine specialist, researcher, and AI developer working at the intersection of aviation physiology, extreme‑environment medicine, and applied machine intelligence — building systems that help humans operate safely where the atmosphere stops cooperating.
Associate Professor of Aerospace Medicine and lead researcher at the Direction of Aerospace Medicine. My day‑to‑day blends clinical aviation medicine, advanced human‑factors training, and the design of computational tools that turn physiology into actionable signal.
A working portfolio across human performance modeling, aerospace medicine tooling, and applied AI. Several projects are private — descriptions intentionally stay high‑level.
Implementation of a sleep–wake bio‑mathematical model that forecasts effectiveness, alertness, and cognitive risk for variable duty schedules — designed to support flight operations and crew planning.
A multi‑agent LLM workflow for aeromedical certification and research support — orchestrates retrieval, reasoning and verification across regulatory, clinical and scientific knowledge sources.
An end‑to‑end pipeline for screening, extracting and synthesizing the literature on large language models applied to aerospace and clinical aviation contexts.
Toolkit for processing wearable bio‑signal recordings (ECG, HRV, respiration, accelerometry) from astronaut‑grade and athletic devices — built around reproducible HRV metrics and time‑series QC.
Application for managing hypobaric‑chamber profiles, capturing physiological data and supporting instructor decisions during hypoxia awareness training.
Serial‑port acquisition layer and GUI for capturing customized data from a normobaric hypoxia training device, enabling research‑grade logging beyond the stock interface.
Iterative DCS modeling — both classical physiological formulations and machine‑learning variants — to better characterize altitude‑exposure risk in operational profiles.
Computational model of pressure‑driven middle‑ear injury, grounded in chamber experience and the published literature, intended for instructor briefings and risk discussion.
Systematic review and meta‑analytic work on the neuropsychological profile of high‑performance fighter aircrews, with emphasis on attention, executive function and workload tolerance.
Research project examining attention and neurocognitive domains in commercial pilots operating highly automated flight decks — manuscript and analysis pipeline in progress.
Customized derivative of an open multi‑attribute task battery, tailored toward military aviation workload research, with extensions for experiment replicability and data export.
Living review and analysis pipeline on metabolic syndrome and cardiometabolic risk among aircrews, connecting clinical markers to operational fitness implications.
Resource‑flow simulation of symptom induction and recovery from sustained Gz acceleration in aeronauts — supports training narratives and tolerance discussions.
Working library for simulating and analyzing human circadian rhythms under arbitrary light schedules — useful for shift, mission and long‑haul operational planning.
Model‑Context‑Protocol server for AI‑assisted deep research — built around citation discipline, scientific rigor and tight integration with reasoning models.
Vector‑store and retrieval system that backs my aerospace‑medicine literature workflow, including a private MCP layer over a personal reference library.
Collection of small Python utilities that estimate physiological outcomes used routinely in aerospace medicine training and consultation.
Custom interface to acquire SpO₂ and pulse signals directly from Bluetooth pulse oximeters, rebuilt after the original mobile pipeline became unavailable.
Medical Officer and researcher with the Colombian Antarctic Program. Studied physiological responses, cold‑exposure adaptation and risk management in extreme polar environments.
Medical Officer in a confined‑habitat space analog campaign, focused on isolation, confinement and cognitive‑physiological responses relevant to long‑duration spaceflight.