Nahuel Gómez Raguileo
Nahuel Gómez Raguileo

Ph.D. Student · Computer Engineer (M.Sc. Computer Science)

Universidad de Chile

I’m a Ph.D. student and Computer Engineer (M.Sc.) at Universidad de Chile, specializing in applied Artificial Intelligence and multimodal models for healthcare, psychology, and IoT systems.

I build end-to-end machine learning pipelines, natural language processing models, and AI solutions in enterprise and clinical settings — from raw audio and biomedical signals to real-time predictions.

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Experience

Research Engineer

Universidad de Chile · Santiago

Designed and built the real-time machine learning engine for a clinical diagnostic system, analyzing live EEG signals and tabular data. Developed the ML backend for a pose-estimation mobile app tracking rehabilitation exercises, supporting the reduction of public healthcare waiting lists.

Data / AI Engineer

Customer Trigger · Santiago

Trained machine learning and deep learning models for personalized messaging across retail, insurance, automotive and healthcare, increasing monthly sales by 5%. Analyzed large-scale datasets for record completeness and produced automated reports to support strategic decision-making.

Data Engineer — Treasury

Banchile Inversiones · Santiago

Automated key operational processes and eliminated workflow bottlenecks within the Treasury team by building and deploying bots in a Microsoft ecosystem.

Education

Ph.D. in Computer Science — Applied Artificial Intelligence

Universidad de Chile

Doctoral research in applied Artificial Intelligence. In progress — expected completion December 2029.

M.Sc. in Computer Science

Universidad de Chile

Master’s Thesis — Highest Honors, Best Computer Science Thesis 2025: “Natural Language Processing for the Diagnosis of Postoperative Delirium.” Built an end-to-end diagnostic pipeline combining Transformer-based semantic analysis of raw audio with tabular models for clinical data.

B.S. in Computer Science and Engineering (Computer Engineer)

Universidad de Chile

Projects

Award-winning thesis

Postoperative Delirium Diagnosis with NLP

End-to-end diagnostic pipeline, from raw patient audio to final clinical prediction. Two analytical pathways: transformers for semantic analysis and tabular models for clinical variables. Best Computer Science Thesis 2025.

PyTorch Transformers Hugging Face Clinical NLP
INRIA · IoT

LoRaWAN Network Analysis

During my internship with the Agora team (INRIA, Lyon), I analyzed LoRaWAN networks through unstructured metadata, creating dynamic visualizations to detect hidden patterns and traffic anomalies.

Data Analysis IoT Anomaly Detection
Research

Real-time ML Diagnostic Engine (EEG)

Machine learning engine that analyzes live EEG signals together with tabular data to generate immediate diagnostic predictions, within an interdisciplinary team.

Python Deep Learning EEG Signals Real-time
Public health

Pose Estimation ML Backend

ML backend in a mobile app for pose estimation, tracking patient activity during specific exercises to help reduce waiting lists in public healthcare.

Pose Estimation Computer Vision Mobile ML
Fullstack · GMDS

Clinical Decision Support (Code Blue)

Full-stack clinical decision support system to predict mortality in patients undergoing Code Blue procedures, presented at the GMDS conference (Germany). Low-latency real-time data ingestion backend using the international FHIR standard.

FastAPI FHIR Real-time
Publications
S. Callejas, Nahuel Gómez Raguileo, C. Pelachaud, B. Ravenet, V. Barriere (2026). MultiLinguahah: A New Unsupervised Multilingual Acoustic Laughter Segmentation Method. arXiv.
Source Document
V. Barriere, Nahuel Gómez Raguileo, L. Hemamou, S. Callejas, B. Ravenet (2025). StandUp4AI: A New Multilingual Dataset for Humor Detection in Stand-up Comedy Videos. EMNLP Findings.
Source Document
Talks & Events
Healthcare

Clinical Decision Support for Critical Care (Code Blue)

Presenter & Lead Developer — presented a full-stack clinical decision support system to predict mortality in Code Blue procedures, with low-latency real-time data ingestion via the …

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Nahuel Gómez Raguileo
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Contact

Open to collaborations in ML, NLP and applied research.

Connect

I'm always open to discussing new projects, opportunities, or just having a chat.

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