I am a Data Scientist with a solid foundation in statistics and computer engineering. With over 18 years of experience, I excel in employing predictive modeling, data mining, machine learning algorithms, and business intelligence to tackle complex challenges and drive impactful solutions.

I earned my PhD in Computer Engineering, specializing in Artificial Intelligence, under the guidance of Professors Gerhard Klimeck and Okan Ersoy. My research focused on integrating advanced statistical modeling techniques to diagnose and mitigate degradation issues within supervised learning algorithms.

My Interests

  • Statistical detection of hidden relations between variables in large datasets
  • Degradation in supervised learning algorithms
  • Applications of machine learning algorithms to solve complex problems in digital agriculture, consumer insights, and the economics of food systems.


M.Sc. in Statistics
School of Statistics, University National of Colombia.


Graduate Certificate in Statistics
School of Statistics, University National of Colombia.


Graduate Certificate in Management for Engineers
School of Business, Pontifical Bolivarian University.


B.S. Electronic Engineering
School of Electrical and Computer Engineering, Pontifical Bolivarian University.


Purdue University
Lead Research Data Analyst
I drive efforts to bolster research within the Center of Food Demand and Analysis and Sustainability (CFDAS), College of Agriculture. My role involves enhancing researchers’ capabilities in data stewardship, integration, and analysis, fostering a culture of reproducibility and reliability in research outcomes. Through these efforts, we ensure that our research results are consistently robust and reproducible

Lead Data Scientist (2022-2023)
I was responsible for developing, implementing, and supporting cutting-edge data analysis techniques within the Regenstrief Center for Healthcare Engineering (RCHE). This includes the creation of robust data pipelines, advanced statistical modeling, machine learning methodologies, and innovative data visualization approaches.


Advanced Agrilytics
Director Data Scientist.
As the Director of the Data Science team, I spearheaded initiatives aimed at tackling quantitative challenges in digital agriculture, particularly focused on maximizing crop yields (corn, soybean, and wheat) and optimizing agricultural products. Leveraging extensive datasets, my role involved employing advanced techniques including statistical modeling, data mining, and machine learning to drive innovation and precision in agricultural practices.


Purdue University
Research Assistant in the Network for Computational Nanotechnology (NCN).

As a research assistant, I developed and applied data analytics models to identify behavior patterns based on user actions on ‘nanoHUB’, the world’s largest online nanotechnology user facility.


Group Bancolombia
IT Security Analyst – Fraud Prevention Analyst
I specialized in developing statistical and data mining models aimed at fortifying cybersecurity processes. My focus lay in creating robust frameworks for detecting insider threats, identifying targeted attacks, and implementing preventive measures against financial fraud.


Purdue University
Teaching Assistant at the School of Electrical and Computer Engineering

Course: ECE 30010 – Introduction to Machine Learning and Pattern Recognition.


Pontifical Bolivarian University
Assistant Professor at the School of Engineering
Courses: Data visualization
* Statistical Inferencedrive.


Eafit University
Adjunct Professor at the School of Engineering
Courses: Data visualization * Data Mining * Business Intelligence.