Google tag (gtag.js) Andres Hernandez-Matamoros — Researcher NAV HERO / ABOUT
Andres Hernandez-Matamoros

Staff Scientist · OIST, Okinawa

Andres
Hernandez-Matamoros

Electronics Engineer turned AI researcher with a Ph.D. (with distinction) in Communications & Electronics from IPN Mexico. International career spanning Mexico, Italy, and Japan — now at the Okinawa Institute of Science and Technology working at the intersection of machine/deep learning and biomedical signals.

CSEC Award Former SNI Level 1 — CONACyT Mexico Ph.D. — IPN Mexico U. of Tokyo Meiji Univ. OIST
GOOGLE SCHOLAR

Google Scholar Profile

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AREAS OF INTEREST

Areas of Interest

Machine/Deep Learning

Machine &
Deep Learning

Transfer Learning

Transfer Learning

Processing Digital Signals

Digital Signal
Processing

Data Privacy

Data Privacy &
LDP

ACADEMIC EXPERIENCE

Academic Experience

April 2025 — Present

Staff Scientist

Okinawa Institute of Science and Technology (OIST), Japan ↗

March 2022 — March 2025

Postdoctoral Researcher

Meiji University, Japan ↗

November 2020 — February 2022

Project Researcher

The University of Tokyo, Japan ↗

January 2019 — October 2020

Postdoctoral Fellow

Iwate Prefectural University, Japan ↗

PROJECTS

Projects

01 / Transfer Learning

Sleep Staging from Clinical PSG to Wearables

A transfer learning framework leveraging labeled PSG data to train models for awake/asleep classification and sleep staging on EEG from novel wearables. Addresses signal domain mismatch via latent space representations using deep learning, enabling accurate inference without manual annotations.

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Transfer Learning

02 / Multimodal Biomarker

EEG + ECG Fusion for Health Monitoring

Integration of EEG and ECG signals from wearables to identify robust multimodal biomarkers for early disease detection. The framework fuses neurological and cardiovascular data, emphasizing real-time processing and artifact removal for continuous, non-invasive healthcare.

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Wearable signals

03 / Data Privacy

Local Differential Privacy for Healthcare Data

Bayesian Ridge Regression to tackle high-dimensional, correlated healthcare and smartwatch data under LDP. The "Castell" approach refines perturbation and aggregation, enabling accurate joint probability estimation with enhanced privacy safeguards.

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Data Privacy

04 / Anomaly Detection

Real-Time Stuck-Prediction via Autoencoders

Autoencoder-based models for real-time anomaly detection, tracking failures through elevated reconstruction errors. Identifies warning signs earlier and more accurately than supervised approaches, improving overall system reliability.

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Anomaly Detection

05 / Synthetic Data

BiRNN Synthetic Biomedical Signal Generation

A Bidirectional RNN with statistical stage to generate five types of synthetic biomedical signals (ECG, EEG, BCG, PPG, respiratory). Outperforms GAN-based techniques, addressing data scarcity crucial for medical diagnoses.

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06 / Forecasting

Region-Based COVID-19 ARIMA Forecasting

Region-based ARIMA model for COVID-19 spread prediction across six global regions with population data integration. Achieves an average RMSE of 144.81, with potential for improvement via climate and cultural variables.

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COVID Forecasting

07 / Computer Vision

Facial Expression Recognition (99% Accuracy)

Automatic face detection, segmentation, Gabor feature extraction, and PCA-reduced fuzzy clustering classification. Achieves ~97% accuracy with one region and up to 99% combining both, robust even under partial occlusion.

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PUBLICATIONS

Selected Publications & Talks

IT = Invited Talk  ·  J = Journal  ·  B = Book  ·  C = Conference. Full list: Full CV ↗

2026
C16

Transfer Learning from Clinical PSG to Real-World Wearables for Sleep Staging

Hernandez-Matamoros A., Doya K., Tomonaga S., Mizutani H.

19th BIOSTEC — HEALTHINF, pp. 548–555, ISBN 978-989-758-802-0

C15

Opportunistic Teacher Forcing: Training RNNs on Wearable Signals with Inherent Missing Data

Tomonaga S., A. Hernandez-Matamoros, Mizutani H., Doya K.

19th BIOSTEC — BIOSIGNALS, pp. 446–453, ISBN 978-989-758-802-0

2025
J9

Machine Learning-Driven Prediction of Heat Transfer Coefficients for Pure Refrigerants in Diverse Heat Exchanger Types

Santiago Galicia E., A. Hernandez-Matamoros, Miyara A.

Journal of Experimental and Theoretical Analyses, 3(4), 32

B3

Proceedings of the 24th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques (SoMeT_25)

Fujita H., Hernandez-Matamoros A., Watanobe Y. (Eds.)

IOS Press 2025, Frontiers in AI and Applications 411

C14

Differential Private Risk Factors Analysis of Polypharmacy

Kikuchi H., A. Hernandez-Matamoros

MDAI 2025, LNCS vol. 15957. Springer, Cham

2024
C13

Secure Aggregation of Smartwatch Health Data with LDP

A. Hernandez-Matamoros, Kikuchi H.

SocialSec 2024, LNCS vol. 15565. Springer, Singapore

J8

Comparative Analysis of Local Differential Privacy Schemes in Healthcare Datasets

Andres Hernandez-Matamoros, Hiroaki Kikuchi

Applied Sciences 2024, 14, 2864

B2

Advances and Trends in Artificial Intelligence. Theory and Applications

Fujita H., Cimler R., Hernandez-Matamoros A., Ali M. (Eds.)

Springer Singapore, 2024

B1

New Trends in Intelligent Software Methodologies, Tools and Techniques

Fujita H., Pérez Meana H.M., Hernandez-Matamoros A. (Eds.)

IOS Press, 2024

C12

Prediction of Heat Transfer Coefficient and Pressure Drop of Flow Boiling and Condensation Using Machine Learning

Galicia E.S., A. Hernandez-Matamoros, Miyara A.

Journal of Physics: Conference Series, 2024

C11

Meaningful Performance Analysis on Healthcare Data under Local Differential Privacy

A. Hernandez-Matamoros, Hiroaki Kikuchi

SoMeT 2024: 398–411, ISBN 978-1-64368-538-0

C10

Machine Learning-Based Approach to Correct Saturated Flow Boiling Heat Transfer Correlations

Galicia E.S., A. Hernandez-Matamoros, Miyara A.

SoMeT 2024: 235–248, ISBN 978-1-64368-538-0

2023
J7

Ozone Responses to Reduced Precursor Emissions

Vazquez Santiago J., Jaimes Palomera M., Resendiz Martinez C., A. Hernandez-Matamoros, et al.

Science of The Total Environment, 2023, 169180

C9

New LDP Approach Using VAE

A. Hernandez-Matamoros, Kikuchi H.

NSS 2023, LNCS 13983. Springer

C8

An Efficient Local Differential Privacy Scheme Using Bayesian Ridge Regression

A. Hernandez-Matamoros, Kikuchi H.

20th Annual Int. Conference on Privacy, Security & Trust (PST), Copenhagen, 2023

IT2

Webinar: Medical Big Data — Machine Learning

Invited Talk · March 31, 2023

2022
IT1

International Congress of Geoeconomic Engineering — Synthetic Biomedical Signals with ANNs

Invited Talk · October 25, 2022

C7

A Vulnerability in Video Anonymization — Privacy Disclosure from Face-Obfuscated Video

Kikuchi H., Miyoshi S., Mori T., A. Hernandez-Matamoros

19th Annual Int. Conference on Privacy, Security & Trust (PST), Fredericton, 2022

2021
J6

Less Complexity One-Class Classification Approach Using Construction Error

Hayashi T., Fujita H., A. Hernandez-Matamoros

Information Sciences, Vol. 560, pp. 217–234, 2021

2020
J5

A Novel Approach to Create Synthetic Biomedical Signals Using BiRNN

A. Hernandez-Matamoros, Fujita H., Perez-Meana H.

Information Sciences, Vol. 541, pp. 218–241, 2020

J4

Recognition of ECG Signals Using Wavelet Based on Atomic Functions

A. Hernandez-Matamoros, Fujita H., Nakano-Miyatake M. et al.

Biocybernetics and Biomedical Engineering, Vol. 40, Issue 2, 2020

J3

Forecasting of COVID-19 per Regions Using ARIMA Models and Polynomial Functions

A. Hernandez-Matamoros, Toshitaka H., Fujita H., Perez-Meana H.

Applied Soft Computing, Vol. 96, 2020

C6

Heart Beat Recognition Using a Novel Preprocessing Scheme and Neural Networks

A. Hernandez-Matamoros, Fujita H., Perez-Meana H.

SoMeT 2020, Frontiers in AI and Applications, Vol. 327

2019
J2

Scheme Fuzzy Approach to Classify Skin Tonalities Through Geographic Distribution

Hernandez-Matamoros A., Fujita H., Nakano-Miyatake M. et al.

J. Ambient Intelligence and Humanized Computing, 11, pp. 2859–2870, 2019

C5

A Scheme to Classify Skin Through Geographic Distribution of Tonalities Using Fuzzy Based Classification Approach

A. Hernandez-Matamoros, Fujita H., Nakano M., Perez-Meana H., Hernandez-Escamilla E.

SoMeT 2019, Frontiers in AI and Applications, Vol. 318

2017
C4

Facial Expression Recognition in Unconstrained Environment

A. Hernandez-Matamoros, Nagai T., Attamimi M., Perez-Meana H.

SoMeT 2017, Frontiers in AI and Applications, Vol. 297, pp. 525–538

2016
J1

Facial Expression Recognition with Automatic Segmentation of Face Regions Using a Fuzzy Based Classification Approach

Andres Hernandez-Matamoros, Andrea Bonarini, E. Escamilla-Hernandez, M. Nakano-Miyatake, H. Perez-Meana

Knowledge-Based Systems, 2016, ISSN 0950-7051

2015
C3

A Facial Expression Recognition with Automatic Segmentation of Face Regions

A. Hernandez-Matamoros, Bonarini A., Escamilla-Hernandez E., Nakano-Miyatake M., Perez-Meana H.

SoMet 2015, Naples, Italy, LNCS pp. 529–540

2014
C2

A Supervised Classifier Scheme Based on Clustering Algorithms

A. Hernandez-Matamoros, Escamilla-Hernandez E., Perez-Daniel K., Nakano-Miyatake M., Perez-Meana H.

CONCAPAN XXXIV, IEEE, Panama City, 2014

2013
C1

Learning an Object Through Images Obtained from the Internet Using Unsupervised Learning

A. Hernandez Gerardo, Perez Meana H.M., Escamilla Hernandez E.

9th Int. Congress Technological Trends in Computation, Research in Computer Science, Vol. 69

CONTACT