Andres Hernandez-Matamoros CV

Andres Hernandez-Matamoros

I earned a degree in Electronics Engineering from the Metropolitan Autonomous University (Mexico) in 2011. Later, in 2013 and 2018, I earned a Master's degree in Microelectronics and a Ph.D. in Communications and Electronics, respectively. I graduated with Distinction from the Polytechnic National Institute (Mexico). From 2012 to 2013, I completed a research stay at the Politecnico di Milano. As part of the JUSST program, I completed a research stay at the University of Electro-Communications in Tokyo, Japan, from 2015 to 2016. In 2019-2020, I completed a postdoctoral stay at Iwate Prefectural University in Intelligent Software Systems. Afterwards, I worked as a project researcher at The University of Tokyo developing anomaly detection using deep learning approaches from 2020 to 2022. Currently, I am a postdoctoral researcher at Meiji University.

You can find me on

Google Scholar, LinkedIn, ORCID, Research Gate, Scopus, Research Map, SciProfiles
Email:matamoros@meiji.ac.jp, phd.matamoros@gmail.com

Areas of interest

Data Privacy, Machine Learning, Deep Learning, Image Processing, Anomaly Detection, Processing Digital Signals

Projects

Facial Expression Recognition Video
Skin detection
Recognition of ECG Signals
Creating synthetic biomedical signals
Forecasting of Covid-19
Anomaly Detection
Data Privacy using VAE

Distinctions

National System of Researchers, Level 1 (Mexico-CONACyT) Document in Spanish

Membership

The Information Processing Society of Japan (IPSJ) Document in Japanese

Education

2006 - 2011. Autonomous Metropolitan University, Mexico City. Electronic Engineer.

2011 - 2013. National Polytechnic Institute, Mexico City. Title of the Thesis: "Optimization and Application of Unsupervised Learning Algorithms", Master in Microelectronics Engineering.

2014 - 2018. National Polytechnic Institute, Mexico City. Title of the Thesis: "Facial Expression Recognition", Ph.D. on Communications and Electronics (With Distinction).

Research stays

Polytechnic of Milan, Milano Italy (October 2012 - March 2013). Research was conducted on facial expressions using OpenCV to detect the face, followed by the proposal of a machine learning technique to recognize the facial regions. Advisor Ph.D. Andrea Bonarini.

University of Electro-communications, Tokyo, Japan (April 2015 - March 2016). Recognition of facial expressions in the wild. Advisor Ph.D. Takayuki Nagai.

Other courses

Japanese University Studies in Science & Technology (JUSST) (April 2015 - March 2016).

Industry experience

Senior Consultant in Artificial Intelligent at Praxis(Mexico) (April 2018 - December 2018). I kept in touch with all areas at Praxis to apply AI in areas such as big data, healthcare, finance, etc. I was responsible for creating white papers and advising customers on how to apply AI.

Academic experience

Postdoctoral Stay

Iwate Prefectural University (January 2019 - October 2020). Fujita Laboratory. Research in Arrhythmia detection using Deep Learning.

The University of Tokyo (November 2020 - February 2022). Ocean Industrial Science, Technology & Environmental Relations Lab. Research in Anomaly Detection applying Deep learnig.

Meiji University (March 2022- ). Kikuchi Lab. Research in data privacy which is part of the project "Anonymous healthcare cohort with the guarantee of data privacy and utility".

UNITEC (May 2016 - August 2016)

Autonomous Metropolitan University (September 2017 - March 2018)

National Autonomous University of Mexico (July 2017 - December 2018)

Inner Mongolia University of Technology (IMUT) (December 2023)

Invited speaker

International Congress of Geoeconomic Engineering, How to create synthetic biomedical signals using artificial neural networks. 2022/October/25. Certificate [Spanish]

Webinar Medical Bid Data-Machine Learning 2023/March/31. Certificate

Journal Publications

J1. Andres Hernandez-Matamoros, Andrea Bonarini, Enrique Escamilla-Hernandez, Mariko NakanoMiyatake, Hector Perez-Meana, Facial expression recognition with automatic segmentation of face regions using a fuzzy based classification approach, Knowledge-Based Systems, (2016), ISSN 0950-7051.

J2. Hernandez-Matamoros, A., Fujita, H., Nakano-Miyatake, M. et al., Scheme fuzzy approach to classify skin tonalities through geographic distribution, J. Ambient Intell Human Comput, 11, 2859-2870 (07-2019).

J3. Hernandez-Matamoros, A., Fujita, H., Nakano-Miyatake, M. et al., Recognition of ECG Signals Using Wavelet Based on Atomic Functions,Journal Biocybernetics and Biomedical Engineering, Volume 40, Issue 2, Pages 803-814, (04-2020).

J4. Hernandez-Matamoros, A., Fujita, H., & Perez-Meana, H. (2020)., A novel approach to create synthetic biomedical signals using BiRNN, Information Sciences, Volume 541, Pages 218-241, ISSN 0020-0255, (12-2020).

J5. Hernandez-Matamoros, A., Toshitaka H., Fujita, H., Hector Perez-Meana, Forecasting of COVID19 per regions using ARIMA models and Polynomial Functions, Applied Soft Computing, Volume 96, 11-2020, 106610, ISSN 1568-4946.

J6. Toshitaka Hayashi, Hamido Fujita, Andres Hernandez-Matamoros, Less complexity oneclass classification approach using construction error of convolutional image transformation network,Information Sciences,Volume 560,Pages 217-234, 06-2021, ISSN 0020-0255.

J7. Andres Hernandez-Matamoros, Ryota Wada, et al., Semi Supervised Early Stuck Detection, Under revision at SPE journal

J8. Jairo Vazquez Santiago, Monica Jaimes Palomera, Cintia Resendiz Martinez, Andres Hernandez-Matamoros, Hiroo Hata, Kazuya Inoue, Kenichi Tonokura, Ozone responses to reduced precursor emissions: A modeling analysis on how attainable goals can improve air quality in the Mexico City Metropolitan Area, Science of The Total Environment, 2023, 169180, ISSN 0048-9697

J9. Andres Hernandez-Matamoros, Hiroaki Kikuchi, Comparative Analysis of Local Differential Privacy Schemes in Healthcare Datasets, submitted at Applied Sciences Special Issue Data Privacy and Security for Information Engineering

Conference Publications

C1. Andres Gerardo Hernandez Matamoros, Hector Manuel Perez Meana, Enrique Escamilla Hernandez, Object Learning using images from the Internet through Unsupervised Learning, SIMCI 2013.

C2. Andres Gerardo Hernandez Matamoros, Hector Manuel Perez Meana, Enrique Escamilla Hernandez, Learning an object through images obtained from the Internet using Unsupervised Learning, 9 International Congress Technological Trends in Computation indexed to the journal, Research in Computer Science, 2013.

C3. A. Hernandez-Matamoros, E. Escamilla-Hernandez, K. Perez-Daniel, M. Nakano-Miyatake and H. Perez-Meana, A supervised classifier scheme based on clustering algorithms, Central America and Panama Convention (CONCAPAN XXXIV), 2014 IEEE, Panama City, 2014, pp. 1-5.

C4. A. Hernandez-Matamoros, Andrea Bonarini, E. Escamilla-Hernandez, M. Nakano-Miyatake and H. Perez-Meana, A Facial Expression Recognition with Automatic Segmentation of Face Regions. Intelligent Software Methodologies, Tools and Techniques: 14th International Conference, SoMet 2015, Naples, Italy, September 15-17, 2015, Proceedings, Springer Pages 529-540, ISBN 978-3-319-22689-7.

C5. Andres Hernandez-Matamoros, Takayuki Nagai, Muhammad Attamimi, Hector Perez-Meana, Facial Expression Recognition in the wild Mini-Conference for Exchange Students on Informatics & Engineering and Information Systems No. 34, Poster presentation, 2015.

C6. Andres Hernandez-Matamoros, Takayuki Nagai, Muhammad Attamimi, Hector Perez-Meana, Facial Expression Recognition in the wild Mini-Conference for Exchange Students on Informatics & Engineering and Information Systems No. 35, Oral presentation, 2016.

C7. Andres Hernandez-Matamoros, Takayuki Nagai, Muhammad Attamimi, Hector Perez-Meana, Facial expression recognition in unconstrained environment (2017) (Frontiers in Artificial Intelligence and Applications; Vol. 297, pages 525-538), ISSN (Print)0922-6389.

C8. Hernandez-Matamoros, A., Fujita, H., Nakano, M., Perez-Meana, H.,& Hernandez-Escamilla E.(2019), A Scheme to Classify Skin Through Geographic Distribution of Tonalities Using Fuzzy Based Classification Approach (pp. 3-10), Frontiers in Artificial Intelligence and Applications; Vol. 318, DOI 10.3233/FAIA190034.

C9. Hernandez-Matamoros, A., Fujita, & Perez-Meana, H., Heart Beat Recognition using a novel preprocessing scheme and Neural Networks, pp. 162-172, Frontiers in Artificial Intelligence and Applications; Volume 327: Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques, DOI 10.3233/FAIA200562.

C10. H. Kikuchi, S. Miyoshi, T. Mori and A. Hernandez-Matamoros, A Vulnerability in Video Anonymization - Privacy Disclosure from Face-obfuscated video, in 2022 19th Annual International Conference on Privacy, Security & Trust (PST), Fredericton, NB, Canada, 2022 pp. 1-10. doi: 10.1109/PST55820.2022.9851976

C11. Andres Hernandez-Matamoros, Hiroaki Kikuchi, Risk Evaluation of LDP scheme LoPub against Variational Autoencoder,Computer Security Symposium 2022, pp. 289-296, 2022.

C12. Jairo Vazquez Santiago, Monica Jaimes Palomera, Cintia Resendiz Martinez, Andres Hernandez-Matamoros, Hiroo Hatab, Kazuya Inoueb, Kenichi Tonokura, Evaluation of Ozone Responses to Feasible Reduction Goals in Precursor Emissions in the Mexico City Metropolitan Area Using Air Quality Models to be presented at CMAS-Asia-Pacific, Japan, July 19-21, 2023.

C13. Hernandez-Matamoros, A., , Kikuchi, H. (2023), New LDP Approach Using VAE. In: Li, S., Manulis, M., Miyaji, A. (eds) Network and System Security. NSS 2023. Lecture Notes in Computer Science, vol 13983. Springer, Cham. https://doi.org/10.1007/978-3-031-39828-5_10

C14. A. Hernandez-Matamoros and H. Kikuchi, An Efficient Local Differential Privacy Scheme Using Bayesian Ridge Regression, in 2023 20th Annual International Conference on Privacy, Security and Trust (PST), Copenhagen, Denmark, 2023 pp. 1-7.

C15. Santiago Galicia Edgar, Miyara Akio, Andres Hernandez-Matamoros, "機械学習による冷媒の熱伝達率予測", 第２３回西日本地区技術交流会公益社団法人日本冷凍空調学会　西日本地区事業推進委員会

C16. Andres Hernandez-Matamoros, Hiroaki Kikuchi, A Randomized Response Layer for Ensuring User Privacy in Synthetic Data Generation, Computer Security Symposium 2023

Languages

English: spoken 90 % written 90%
Italian: spoken 25 % written 25%
Japanese: spoken 10 % written 10%

Skills

Statistics, Programming knowledge, Data Manipulation and Analysis, Machine Learning, Deep Learning, Model Deployment, Communication Skills, Structured Thinking, Curiosity.

Software

Windows, Linux, MAC OS, Office, Matlab, Simulink, System Generator, ISE 6.1 Xilinx, Nallatech FUSE, AVR Studio, Pony Prog, Code::Blocks , Dev-C++, Visual Studio, OpenCV, Anaconda, Python, Pandas, Matplotlib, Scikit-learn, Keras, TensorFlow, Pytorch.

Hardware

FPGA Virtex II and Spartan-3, Microcontrollers, Spectrum analyzers, Oscilloscope, Function generator.

Personal & Professional References

Upon Request