Carlos Simón Amador Izaguirre

Simón Amador

AI Engineer building reliable AI systems in healthcare and for knowledge-intensive teams.

I work across production GenAI, RAG, evaluation and biomedical AI research. Currently building AI systems at Laboratorios Bagó del Perú.

Selected work Research & CV Consulting
Carlos Simón Amador Izaguirre, AI Engineer and biomedical AI researcher
Background
Research at Harvard Medical School. Production AI systems in pharmaceutical workflows.
01

About

I'm Carlos Simón Amador Izaguirre, most people call me Simón. I'm a Peruvian biomedical engineer building reliable AI systems in healthcare and for knowledge-intensive work, with a focus on production GenAI, medical computer vision, and biomedical research.

I studied at Tecnológico de Monterrey and spent six months at the Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC) from Boston Children's Hospital and Harvard Medical School, where I co-authored research on deep generative models for fetal brain anomaly detection.

Currently, I build and scale internal GenAI systems at Laboratorios Bagó del Perú for pharmaceutical commercial and medical workflows. I work across RAG, evaluation, analytics, deployment, and cross-functional delivery.

My work connects production AI engineering with biomedical research. I welcome focused conversations about graduate study, research collaboration, and technical roles aligned with that intersection.

Simón Amador at Boston Children's Hospital / Harvard Medical School
Rigorous AI should be useful before it is impressive.
4+
Years in AI
3
Companies
3
Research labs
5
Publications & talks

Research output

More research output
2
Presentation

Conditional deep generative normative modeling for structural and developmental anomaly detection in the fetal brain

You S, Amador Izaguirre CS, Tafoya-Milo G, et al.
BibTeXScholar
ISMRM
2025
3
Poster

Deep generative anomaly detection for structural anomalies in fetal brain with ventriculomegaly

You S, Amador Izaguirre CS, Jeong S, et al.
BibTeXScholar
OHBM
2024
4
Symposium

GA-informed VAE-GAN anomaly detection for fetal MRI

You S, Tafoya-Milo G, Amador Izaguirre CS, et al.
BibTeXScholar
FNNDSC
2024
5
Conference Poster

Covariate-conditioned fetal MRI anomaly detection

You S, Tafoya-Milo G, Amador Izaguirre CS, et al.
BibTeXScholar
MIT-MGB
AI Cures 2024
Model architecture for conditional VAE-GAN fetal brain MRI anomaly detection
Model Architecture - Conditional VAE-GAN
Anomaly detection results on fetal brain MRI from NeuroImage 2025
Anomaly Detection Results - NeuroImage 2025
02

Work & Research

AI Engineer

Laboratorios Bagó del Perú · ICT Management
Jul 2024 - Present
Lima, Peru · UTC-5
  • Built and scaled internal GenAI systems for pharmaceutical commercial and medical workflows, including a clinical RAG platform handling 7,000+ queries per week.
  • Designed RAG, evaluation, and analytics systems for document-heavy healthcare use cases.
  • Established practical evaluation and prompt-improvement workflows for reliable production AI.
  • Coordinated technical delivery across internal teams and external specialists.

Organizing Committee Member

Hackathon Desafío IA · Bagó Perú 2026
Jun 12–13, 2026
Lima, Peru
  • Helped organize a two-day AI hackathon with 70+ student participants and 17 evaluated projects.
  • The challenge explored scalable B2C AI concepts for physician workflows and people living with chronic conditions.

Research Intern

Conceivable Life Sciences · Dr. Adolfo Flores-Saiffe
Mar - Jun 2024
Guadalajara, Mexico
  • Led a 4-person team developing AI-assisted pipelines for gamete detection and segmentation in high-resolution microscopy images for IVF clinical workflows.
  • Trained and benchmarked 9 transfer-learning architectures for embryo-quality assessment.
  • Built a Python inference platform for rapid prototyping of embryologist decision-support tools.

Research Intern

Boston Children's Hospital · FNNDSC · Dr. Kiho Im
Jul 2023 - Jan 2024
Boston, MA
  • Curated and preprocessed ~50 fetal brain MRI volumes from four multicenter datasets for anomaly-detection experiments.
  • Developed two PyTorch deep-learning architectures for fetal MRI anomaly detection, contributing to the NeuroImage publication baseline.
  • Optimized preprocessing pipelines (bias-field correction, normalization, orientation harmonization) for a 4-month neuroimaging study.
FNNDSC team at Boston Children's Hospital with Simón Amador

Undergraduate Research Assistant

ITESM · Dr. Rita Q. Fuentes-Aguilar · Advanced Cyberphysical Systems Lab
Aug 2022 - Jun 2023
Guadalajara, Mexico
  • Processed 1,526 biosignal recordings and designed 6 ML models for a brain-computer interface study.
  • Led a 3-member research team coordinating experiments, documentation, and reproducible analysis.
03

Capabilities

Production AI systems

Reliable GenAI, agent and evaluation workflows.

Knowledge and document workflows

Search, RAG, extraction and reporting.

Biomedical AI

Medical imaging and research-oriented model evaluation.

Technical delivery

Solution design, prototyping, deployment and analytics.

Core toolkit: Python, PyTorch, LLM APIs, RAG, evaluation, SQL, FastAPI, Docker, AWS and Azure AI.

Selected projects

MICCAI 2026 · Challenge participant

MRIxFields 2026

Developing and evaluating a challenge submission for cross-field MRI translation and harmonization across multiple magnetic field strengths.

PyTorchGenerative ModelsMRIEvaluation
Challenge
Biomedical AI research

Fetal MRI anomaly detection

Deep generative normative modeling for structural and developmental anomaly detection in fetal brain MRI, contributing to research published in NeuroImage.

PyTorchVAE-GANMedical ImagingEvaluation
PaperGitHub
Production GenAI

Pharmaceutical workflow copilot

Built and scaled a conversational AI system for pharmaceutical commercial workflows, combining structured and unstructured knowledge with retrieval, evaluation and analytics.

GenAIRAGEvaluationAnalytics
More projects
Knowledge workflows

Document-heavy healthcare RAG

Designed retrieval, evaluation and analytics patterns for reliable healthcare knowledge workflows.

RAGSearchEvaluationLLM
Synthetic Identity Infrastructure

personalab

Production-grade synthetic identity infrastructure that enforces facial consistency using embeddings, geometric landmarks, and longitudinal drift tracking.

PythonEmbeddingsComputer VisionSynthetic Data
GitHub
Startup-style AI Assistant · 2024

Baan

Independent AI assistant project focused on practical healthcare workflows, product discovery, and user experience for conversational support tools.

LLMAssistant UXHealthcare AI
IVF Visual Assistance

gasparin

Django application for an in vitro fertilization visual assistance medical device, supporting clinical workflows around embryo and gamete analysis.

PythonDjangoComputer VisionIVF
GitHub
Signal Processing Research

BinauralBeatsResearch

MATLAB research project analyzing binaural beats and auditory stimulation patterns in neuroscience experiments.

MATLABNeuroscienceSignal Processing
GitHub
CT Image Processing

Visible-light CT Image Processing

Image-processing experiments for visible-light CT data, focused on reconstruction and analysis workflows for biomedical imaging.

MATLABImage ProcessingCTBiomedical Imaging
GitHub
Brain-Computer Interface

EEG Channel Selection Algorithm

Jupyter Notebook project for EEG channel selection, supporting feature extraction and model development for brain-computer interface research.

Jupyter NotebookEEGBCIFeature Selection
GitHub
04

Education

Focused AI consulting

I take on a limited number of scoped engagements involving internal knowledge systems, document workflows and AI automation.

Explore consulting

Let's build something
meaningful together.

For research, graduate study, technical opportunities or a clearly scoped consulting question, email is the best way to reach me.

[email protected] Academic CV Tech Resume LinkedIn GitHub Scholar ORCID