Joseph A. Gallego-Mejia

joseph-a-gallego-mejia

Joseph Alejandro Gallego Mejia

PHD(C) SYSTEMS AND COMPUTER ENGINEERING · CTO MUNKYS GROUP INC

USA Phone: (+1) 302 513 6784 | Email: joaggi@gmail.com | Website: munkys.co

LinkedIn: Joseph A. Gallego-Mejia | Twitter: @JoagLogik

“We are able to respect and accept differences.”

Profile

I am technology manager and founder of SAMMU. It is an international company with presence in Colombia, Chile, Peru among others. Currently, I develop applications where there is a broad component of systems engineering, statistics and industrial engineering, using principles of Lean Manufacturing and statistics to software development. I am passionate about programming and the use of free technologies for rapid development of web and mobile applications. Leader, with aptitudes and skills to work in a team, take responsibility, create commitment, and of course, always be willing to change. Interested in generating new knowledge. I teach both programming and artificial intelligence, one of the activities that I enjoy the most.

PhD candidate in computer and systems engineering. Master in Systems Engineering from the National University of Colombia. Researcher in the area of computer science. Participant in secondary education in systems olympiads at the Universidad Antonio Nariño at national level. Student associated with the MindLab research group at the National University of Colombia, Bogotá, conducting research in Machine Learning.

Work Experience

Trillium ‑ Frontier development lab - ESA ‑ NASA US | MACHiNE LEARNiNG RESEARCHER | 4/2023 ‑ 09/2023

Create machine learning pipeline using self supervised learning on satellite images and improve the state of the art methods on 5% of accuracy.
Collaborate with 7 machine learning researches to create new self Clip supervised machine learning methods to improve by 10 percent state of the art methods in vegetation and biomass estimation.
Create a mask autoencoder algorithm to improve land cover classification using self supervised learning methodology and improve by 7% the state-of-the-art-methods.
Present the results to a large audience of expert in 10 minutes showing the principal results obtained by the team.
Create a pytorch lightning dataloader and dataset to ingress a variety of satellite images with different modalitius using Goepandas, XArray and Dask and improve the reading time by 50% using blosc compression.
Create a full-pipeline using model versioning with Hydra, commiting and accepting pull request using git and model logging with Weights & Biases.
Using Google Cloud Platform for training using GPUs and Nvidia’s DGX for multi‑gpu and distributed multi‑gpu training. I trained 4 state-of-the-art foundational models in 20 TB of satellite images.

Munkys Group Inc - Bogotá, Colombia

Chief Technology Officer (Jan. 2012 - Actual)
Create a Spring Boot application for manufacturing enterprises supporting 10k mobile devices users with 10M transactions each hour, using PostgreSQL, RabbitMQ and redis.
Create 10 android applications using Java and Kotlin that supports 10k users. The applications has several usecases such as maintenance, quality, production, messages, payroll, biometric.
Create a triplet network to improve the human recognition of the employees, improving the accuracy by 20% and reducing the inference time by 15%
Create a React Application that supports 10 different applications and 10K users, using realtime communication with RabbitMQ
Create a hybrid infrastructure using docker, docker compose, and kubernetes to support 10k users using a hybrid infrastructure. This achived a cost reduction of 60% compared to the traditional virtual machine cloud setting.
Lead a team of 8 developers and designers to create 10 applications using Scrum, with dealy meetings. Supporting, encourage, and solving their problems.

Universidad Nacional de Colombia - Bogotá, Colombia

Computer Programming (Aug. 2022 - Dic. 2022)
Teaching Support for ”Machine Learning and Big Data” Diploma Course (Aug. 2019 - Actual)
Data Structures Teacher (Aug. 2020 - Jun. 2022)
Creation of Material for Agile Methodologies and Machine Learning Course (Aug. 2021 - Dec. 2021)
Computer Programming and Software Development Teacher (Aug. 2021 - Dec. 2021)
Natural Language Processing Teacher (Aug. 2021 - Dec. 2021)
Development of a Machine Learning System for Supersolidaria (Aug. 2021 - Dec. 2021)
Teach to 2k students in topics such as machine learning, natural language processing, deep learning, machine learning operations, data structure, and programming.

Comware - Bogotá, Colombia

Knowledge Transfer Lecturer in the Project Development of the Predictive Model of Crime for the Criminal Analysis Center of the Criminal Investigation Department and Interpol (Dec, 2021 - Jan, 2022)

Etraining - Bogotá, Colombia

Machine Learning Module Leader and Expert in Charge of the Sessions (Sep, 2021 - Oct, 2021, May, 2022 - Oct, 2022)

Universidad Nacional de Colombia - Medellín, Colombia

Programming Fundamentals Teacher (Jul. 2015 - May. 2016)

Minciencias - Universidad Nacional De Colombia - Bogotá, Colombia

Young Researcher (Jan. 2014 - Dec. 2015)

Munkys SAS - Bogotá, Colombia

Administrative and Financial General Manager (Jan. 2007 - Dec. 2011)
Office Assistant (Ene. 2010 - Jun. 2010)

Education

PhD in Systems Engineering, Universidad Nacional de Colombia, Bogotá, Colombia, Jan. 2019 ‑ Jun. 2023
- Grade point average 3.9 out of 4.0.
- Teaching assistant scholarship.
Specialization in Deep Learning, Deep.AI, Bogotá, Colombia, Jan. 2020 ‑ Dec. 2020
- 6 Courses approved in deep learning.
- Coursera platform.
Master’s Degree in Systems Engineering and Computer Science, Universidad Nacional de Colombia, Medellín, Colombia, Jan. 2014 ‑ Jun. 2017
- Grade point average 3.88 out of 4.0.
- Teaching assistant scholarship.
- Young Researcher.
Systems and Computer Engineering, Universidad Nacional de Colombia, Bogotá, Colombia, Jan. 2008 ‑ Dec. 2013
- Grade point average 3.74 out of 4.0.
- Winner of "mejores saber pro".
- Third place in graduation in systems and computer engineering.
Industrial Engineering, Universidad Nacional de Colombia, Bogotá, Colombia, Jan. 2008 ‑ Dec. 2013
- Grade point average 3.66 out of 4.0.
- Winner of "mejores saber pro".
- First place in industrial engineering graduation.
Intermediate Education ‑ Systems Technician, Instituto técnico central de la Salle, Bogotá, Colombia, Jan. 2003 ‑ Dec. 2007
- Best student in school.
- Participant and winner of systems and computer olympiads

Papers

Computing expectation values of density matrices for quantum anomaly detection

Authors: Diego H. Useche, Oscar A. Bustos-Brinez, Joseph A. Gallego, Fabio A. Gonzalez
Year: 2022
Link: Arxiv, Research Gate

This paper explores how density matrices can be used as a building block to build machine learning models exploiting their ability to straightforwardly combine linear algebra and probability.

Robust Estimation in Reproducing Kernel Hilbert Space

Authors: Joseph A Gallego, Fabio A Gonzalez, Olfa Nasraoui
Year: 2019
Conference: Neurips 2023 LatinX Workshop
Link: Research Gate

Our work shows that estimating the mean in a feature space induced by certain kinds of kernels is the same as doing a robust mean estimation using an M-estimator in the original problem space.

Robust kernels for robust location estimation

Authors: Joseph A Gallego, Fabio A Gonzalez, Olfa Nasraoui
Year: 2021
Journal: Neurocomputings 429, 174-186
Link: Research Gate

This paper shows that least-square estimation (mean calculation) in a reproducing kernel Hilbert space (RKHS) F corresponds to different M-estimators in the original space depending on the kernel function associated with F.

Learning with Density Matrices and Random Features

Authors: Fabio A Gonzalez, Joseph A Gallego, Santiago Toledo-Cortes, Vladimir Vargas-Calderón
Year: 2022
Journal: Quantum Machine Intelligence
Link: Research Gate

This paper explores how density matrices can be used as a building block to build machine learning models exploiting their ability to straightforwardly combine linear algebra and probability.

Fast Kernel Density Estimation with Density Matrices and Random Fourier Features

Authors: Joseph A Gallego, Juan F Osorio, Fabio A Gonzalez
Year: 2022
Conference: Ibero-American Conference on Artificial Intelligence
Link: Research Gate

In this paper, we systematically evaluate the novel DMKDE algorithm and compare it with other state-of-the-art fast procedures for approximating the kernel density estimation method on different synthetic data sets.

Quantum Adaptive Fourier Features for Neural Density Estimation

Authors: Joseph A Gallego, Fabio A Gonzalez
Year: 2022
Link: Arxiv, Research Gate

This paper presents a method for neural density estimation that can be seen as a type of kernel density estimation, but without the high prediction computational complexity.

Anomaly Detection through Density Matrices and Kernel Density Estimation (AD-DMKDE) LatinX Workshop in Neurips 2022

Authors: OSCAR A BUSTOS, JOSEPH A GALLEGO, FABiO A GONZÁLEZ

This paper presents a novel density estimation method for anomaly detection using density matrices (a powerful mathematical formalism from quantum mechanics) and Fourier features.
Presented at Neurips 2022 LatinX Workshop.
Link to Research Gate.

InQMeasurement: Incremental Quantum Measurement Anomaly Detection ICDM

Authors: JOSEPH A GALLEGO, OSCAR A BUSTOS, FABiO A GONZÁLEZ

The paper proposes a new incremental quantum measurement anomaly detection method based on Fourier features and density matrices.
Presented at The IEEE International Conference on Data Mining (ICDM).
Link to Research Gate.

LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection AAAI

Authors: JOSEPH A GALLEGO, OSCAR A BUSTOS, FABiO A GONZÁLEZ

The method combines an autoencoder with a density-estimation model based on random Fourier features and density matrices in an end-to-end architecture that can be trained using gradient-based optimization techniques.
Presented at AAAI.
Link to Arxiv and Research Gate.

Risk Automatic Prediction for Social Economy Companies using Camels WEA

Authors: JOSEPH A GALLEGO, DANiELA MARTiN V, FABiO A GONZÁLEZ

The paper proposed a prediction model based on a machine learning approach, which was trained with the random forest algorithm using historical data provided by each Social Economy Enterprise (SEE).
Presented at WEA.
Link to Research Gate.

MLOps (Machine Learning Dev Ops) ACIS

Authors: JOSEPH A GALLEGO, FABiO A GONZÁLEZ

The paper discusses how data analytics and machine learning are changing every aspect of our lives and how activities that were once performed entirely by humans are now being automated using machine learning algorithms.
Link to ACIS.

Encuesta Nacional "Machine Learning Operations y sus desafíos de implementación en Colombia" ACIS

Authors: JOSEPH A GALLEGO, FABiO A GONZÁLEZ

The paper discusses how data analytics and machine learning are changing every aspect of our lives and how activities that were once performed entirely by humans are now being automated using machine learning algorithms.
Link to ACIS.

Software

Undergraduate Thesis Bogota, Col

Prototype of a Distributed Language for Agents, 2013

Github: https://github.com/Joaggi/Prototype-of-a-distributed-language-for-agents

February 12, 2023 Joseph Gallego · Curriculum Vitae 2

Robust Estimation in Reproducing Kernel Hilbert Space Bogota, Col

Robust Kernels, 2019

Github: https://github.com/Joaggi/Robust-kernels-for-robust-location-estimation

Quantum Measurement Classification Bogota, Col

Learning with Density Matrices and Random Fourier Features, 2021-Now

Github: https://github.com/fagonzalezo/qmc

Fast Kernel Density Estimation Bogota, Col

Learning with Density Matrices and Random Fourier Features, 2021

Github: https://github.com/Joaggi/Fast-Kernel-Density-Estimation-with-Density-Matrices-and-Random-Fourier-Features

Anomaly Detection with Density Matrix Kernel Density Estimation Bogota, Col

Learning with Density Matrices and Random Fourier Features, 2022

Github: https://github.com/Joaggi/anomaly-detection-density-matrix-kernel-density-estimation

LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection Bogota, Col

Learning with Density Matrices and Random Fourier Features, 2022

Github: https://github.com/Joaggi/qaddemadac

Incremental Anomaly Detection using Quantum Measurements Bogota, Col

Learning with Density Matrices and Random Fourier Features, 2022

Github: https://github.com/Joaggi/Incremental-Anomaly-Detection-using-Quantum-Measurements

Posters

Association for the Advancement of Artificial Intelligence AAAI 2023

Washington DC, USA

LEAND: QUANTUM LATENT DENSiTY ESTiMATiON FOR ANOMALY DETECTiON (STUDENT ABSTRACT)
- Presentation of research in anomaly detection
- Winner of travel award to present work
DOCTORAL CONSORTiUM Feb. 2023
- Presentation of doctoral research

LatinX in AI Research Workshop co-located with the Thirty-Third Neural Information Processing Systems (NeurIPS)

New Orleans, USA

ANOMALY DETECTiON THROUGH DENSiTY MATRiCES AND KERNEL DENSiTY ESTiMATiON (AD-DMKDE) Nov. 2022
- Presentation of research in anomaly detection
- Winner of travel award to present work

LatinX in AI Research Workshop co-located with the Thirty-Third Neural Information Processing Systems (NeurIPS)

Vancouver, Canada

ROBUST ESTiMATiON iN REPRODUCiNG KERNEL HiLBERT Dic. 2019
- Presentation of research in robust estimation
- Winner of travel award to present work

Fundación COPEC-UC - International Seminar on Artificial Intelligence

Sant. de Chile, Chile

ROBUST ESTiMATiON iN HiLBERT AND KREiN SPACES WiTH REPRODUCiNG KERNEL Nov. 2018
- Presentation of master's thesis in research seminar on artificial intelligence

Honors and Medals

International

2023

2023 Selected as one of the researcher for developing generalizable SAR image method, Frontier Development Lab sponsorship by NASA and ESA Europe

2020

Selected as one of the 17 best entrepreneurs of Colombia, Young Leaders of the Americas Initiative fellowship

U.S.A

2018

Generation 20 extension winner, Start-Up Chile Chile
Generation 20 winner, Start-Up Chile Chile

National

2014

Third place graduation in computer and systems engineering, Universidad Nacional de Colombia Bogotá, Colombia
First place industrial engineering graduation, Universidad Nacional de Colombia Bogotá, Colombia

2013

Best Saber Pro in Computer and Systems Engineering, Colombian Higher Education Examination Bogotá, Colombia
Best Saber Pro Industrial Engineering, Colombian Higher Education Examination Bogotá, Colombia

2006

2do Puesto, National Programming Olympics Bogotá, Colombia

2005

4to Puesto, National Programming Olympics Bogotá, Colombia

2007

Best student of the whole school, Instituto tecnico central de la Salle Bogotá, Colombia

Skills:

MlOps: MlFlow, DVC, PyTorch, Tensorflow, Jax, Keras, Sklearn, Pandas, Numpy, Matplotlib, Seaborn, PyPlot
DevOps: Google Cloud, AWS, Docker, Kubernetes, Terraform, Jenkins, Git
Back-end: SpringBoot, Spring Framework, FastAPI, Flask, Django, REST API, R, Matlab
Databases: PostreSQL, MySQL, MongoDB, Cassandra, HBase, SQlite, SqlAlchemy, Datastore, Hadoop, PySpark
Front-end: React, Redux, HTML5, LESS, SASS, Javascript, Angular, AngularJs
Programming: Python, JAVA, Javascript, Kotlin, C, C++, Matlab, LaTeX, Visual Basic
Languages: Spanish (Nativo), English (C1), French (B2), Italian(A1)

Program Committee

2022 Technical Committee, International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS 2022), Bristol, UK
2021 Jury, Digital Entrepreneurship Incubator - Colombo Americano Bogotá, Colombia
2020 Mentor, Entrepreneurship Program - Innovation Center Faculty of Engineering, University of Santiago de Chile, Sant. de Chile, Chile
2018 Mentor and Jury, Entrepreneurship Program - GearBox Sant. de Chile

Extracurricular Academic Activities

2020 Machine Learning, How to win a Kaggle competition Coursera
2020 Machine Learning, Improving Deep Neural Networks Coursera
2020 Software Development, Front‑End Web Ui Frameworks and Tools: Boostrap 4 Coursera
2020 Machine Learning, Bayesian Statistics: From Concepts to Data Analysis Coursera
2020 Machine Learning, Sequence Model Coursera
2020 Machine Learning, Convolutional Neural Networks Coursera
2020 Machine Learning, Structuring Machine Learning Projects Coursera
2020 Machine Learning, Neural Networks and Deep Learning Coursera
2019 Software Development, Kotlin for Java Developers Udemy
2019 Machine Learning, Curso de reinforcement learning dictado por Microsoft Edx
2016 Machine Learning, The analitic edge Coursera
2016 Software Security, Software Security Coursera
2016 Software Security, Usable Security Coursera
2015 Software Development, Software process and agile practices Coursera
2015 Machine Learning, The Data Scientist’s Toolbox Coursera
2015 Machine Learning, Pattern Discovery in Data Mining Coursera
2014 Machine Learning, Massive Data Mining Coursera
2013 Machine Learning, Machine Learning Coursera
2013 Machine Learning, Learning from data Edx
2013 Machine Learning, Introduction to statistics Edx
2013 Machine Learning, Introduction to Statistics Coursera
2013 Computer Science, Introduction to Theoric computation Udacity
2012 Machine Learning, Model thinking Coursera
2011 Universidad Nacional De Colombia, Italian language elective course Bogotá, Colombia
2011 Language, English iTEP international test test of english proficiency Certificate level B2 Bogotá, Colombia
2011 Language, English level B2 T&T teaching and tutoring college of colombia Bogotá, Colombia
2005 Instituto Técnico Central de la Salle, III mathematics meeting Liceo Brother Miguel de la Salle Bogotá, Colombia