Pablo Lara

E3WS: Science to Public Safety

Science

E3WS is a transferable AI algorithm for earthquake early warning, currently powering Peru's SASPe system. It estimates earthquake parameters from the first 3 seconds of single-station records using machine learning, enabling rapid decisions before damaging waves arrive.

View E3WS GitHub

Operational Backing

Peru currently uses E3WS through SASPe, benefiting more than 18 million people. Beyond Peru, E3WS has also been applied in scientific articles and dissertations involving Colombia and Haiti, showing that the algorithm can support earthquake early warning research and deployment in seismic regions worldwide.

Social Impact

The work is designed for high-consequence environments where seconds matter, with an emphasis on reliable deployment, open-source reproducibility, and disaster risk reduction.

About Me

I am a Research Scientist and Postdoctoral Researcher at Los Alamos National Laboratory (LANL) in Los Alamos, New Mexico. I hold a PhD in Earth and Universe Sciences and build machine learning systems for earthquake detection, rapid source characterization, and early warning. My work connects peer-reviewed science, operational deployment, and public impact: algorithms developed during my PhD are part of Peru's earthquake early warning effort, serving a population of more than 18 million people.

International Recognition

International Recognition for Seismic Innovation (France)

Recognized for the distinctive capability of E3WS, an AI-based earthquake early warning algorithm designed to operate with both high-cost and low-cost seismic sensors.

E3WS can be applied in seismic regions around the world and is designed for exceptional speed and effectiveness: it uses the first seconds of seismic records to support some of the fastest warning decisions currently possible.

Innovation Pitch

France Innovation Trophies pitch

Pitch segment from 15:19 to 18:42 presenting E3WS as an AI-based earthquake early warning method designed to convert the first seconds of seismic data into rapid public-safety decisions. The embedded player requests YouTube's automatic English captions.

English translation: E3WS uses artificial intelligence to analyze the first 3 seconds of seismic records, detect earthquakes rapidly, and estimate their magnitude and location so warning systems can make faster public-safety decisions before strong shaking arrives.

Watch pitch on YouTube Visit website

Publications

P. Lara, H. Tavera, Q. Bletery, J. P. Ampuero, A. Inza, D. Portugal, B. Orihuela, F. Meza; "Implementation of the Peruvian Earthquake Early Warning System," Bulletin of the Seismological Society of America, 2025.
P. Lara, Q. Bletery, J. P. Ampuero, A. Inza, H. Tavera; "Earthquake Early Warning starting from 3 s of records on a single station with machine learning," Journal of Geophysical Research: Solid Earth, 2023.
A. A. T. Peixoto, C. A. R. Fernandes, P. Lara, A. Inza; "Low-correlation multilinear dimensionality reduction applied to volcano-seismic classification," Pattern Recognition, 2024.
E. Calais, S. Symithe, T. Monfret, B. Delouis, A. Lomax, F. Courboulex, J. P. Ampuero, P. Lara, Q. Bletery, J. Cheze, et al.; "Citizen seismology helps decipher the 2021 Haiti earthquake," Science, 2022.
A. A. T. Peixoto, C. A. R. Fernandes, P. Lara, A. Inza, J. I. Mars, J. P. Metaxian, M. Dalla Mura, M. Malfante; "Tensor-based learning framework for automatic multichannel volcano-seismic classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021.
P. Lara, C. A. R. Fernandes, A. Inza, J. I. Mars, J. P. Metaxian, M. Dalla Mura, M. Malfante; "Automatic multichannel volcano-seismic classification using machine learning and EMD," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020.

Experience

Los Alamos National Laboratory (LANL)

Research Scientist / Postdoctoral Researcher

Scientific machine learning for earthquake seismology, rapid source characterization, and scalable research software in Los Alamos, New Mexico.

Instituto Geofisico del Peru (IGP)

Research Scientist

Developed AI-based earthquake early warning algorithms for SASPe and E3WS, including real-time detection, P-wave picking, magnitude estimation, and hypocentral parameter estimation.

Instituto Geofisico del Peru (IGP)

Software Engineer

Built real-time monitoring systems for the Peruvian national seismic and accelerometric network, including server watchdogs, ShakeMap workflows, and operational seismic infrastructure.

Education

Universite Cote d'Azur, France

2020 - 2024

Ph.D. in Earth and Universe Sciences

Public Thesis: Detection of seismological signals based on artificial intelligence.
Advisors: Quentin Bletery and Jean-Paul Ampuero.
Check out: Ph.D. Thesis.

Universidade Federal do Ceara, Brazil

2018 - 2020

Master of Science in Electrical Engineering and Computer Science

Public Dissertation: "Automatic multichannel volcano-seismic classification using Machine Learning and EMD"
Check out: Master Dissertation.

Universidad Nacional de Ingenieria, Peru

2017

Degree in Electronic Engineering

Public Thesis: "Design of a monitoring system for the satellite seismic network of Peru in real-time"
Check out: Electronic Engineering Thesis.

Universidad Nacional de Ingenieria, Peru

2007 - 2014

Bachelor of Science degree in Electronic Engineering. BAC+5

Projects

Earthquake Early Warning System of Peru: SASPe

SASPe is Peru's national Earthquake Early Warning System: a service for monitoring, warning, dissemination, and communication, designed to alert seconds before urban areas are shaken by seismic waves. Its core algorithmic component is E3WS.

View Project

E3WS: Global AI for Early Warning

Open-source scientific software for machine-learning-based earthquake early warning from the first seconds of seismic records. E3WS currently powers Peru's SASPe system and is designed for reproducible research, real-time deployment, and adaptation to seismic regions worldwide.

View GitHub

Skills

Machine Learning
Earthquake Early Warning
Real-time Seismic Systems
HPC
TensorFlow
PyTorch
Keras
Scikit-learn
C
C++
Python
Bash
HTML
PHP
Matlab
Clusters
MySQL
MariaDB
MongoDB
Linux
Generic Mapping Tools
Earthworm
Seedlink
Nanometrics
Reftek
Guralp
SeisComP
Proxmox VM

Research Scientist in AI for Seismology

E3WS: Science to Public Safety

Science

Operational Backing

Social Impact

About Me

Media & Impact

Ica earthquake alert report

International Recognition

International Recognition for Seismic Innovation (France)

France Innovation Trophies pitch

Publications

Experience

Los Alamos National Laboratory (LANL)

Research Scientist / Postdoctoral Researcher

Instituto Geofisico del Peru (IGP)

Research Scientist

Instituto Geofisico del Peru (IGP)

Software Engineer

Education

Universite Cote d'Azur, France

Ph.D. in Earth and Universe Sciences

Universidade Federal do Ceara, Brazil

Master of Science in Electrical Engineering and Computer Science

Universidad Nacional de Ingenieria, Peru

Degree in Electronic Engineering

Universidad Nacional de Ingenieria, Peru

Bachelor of Science degree in Electronic Engineering. BAC+5

Projects

Earthquake Early Warning System of Peru: SASPe

E3WS: Global AI for Early Warning

Skills

Get in Touch

Contact me at pablo.elara@ieee.org