Data Science Lab
The Data Science Lab main purpose is to contribute with proposals and solutions to the challenges posed by the new knowledge society through the analysis and modeling of complex data. The aim is to respond to society’s real demands, optimize processes, and find evidence-based solutions to high-impact issues.
Specific Objectives
Scientific field
Develop research projects in data science linked to the development of mathematical models and methods for the analysis and modeling of complex data in the fields of neuroscience, biology, ecology, and economics.
Public sphere
Model and describe prioritized problems, outline diagnoses regarding their origin, and develop probable scenarios that can be evaluated as potential interventions for public policy. The problems will be prioritized considering their social impact scale, the availability and quality of representative data, and other institutions previous approaches.
Private sector
Data Analysis and modeling for decision-making. The aim is to optimize processes and procedures within organizations and understand behavior patterns. We prioritize projects that entail a significant social impact.
Unprecedented opportunities
The growing and exponential availability of information assets, coupled with accelerating technologies regarding storage, processing, and data analysis has given rise to the creation of data-based knowledge. The data-driven approach, while providing the opportunity to analyze problems from a different perspective, enables the generation of proposals that were previously unattainable. Consequently, new opportunities arise for both applied and theoretical research and their corresponding transfer to the public and private sectors, creating unique conditions to inform and transform our society.
The Data Science Lab is an experimental, developmental, and pivotal study laboratory aimed at expanding the application of data science methods and facilitating interdisciplinary collaboration in research.
Research Techniques
We analyze data and model solutions using the most efficient techniques for each prioritized problem.
Addressing high-impact problems and creating knowledge through data-based evidence.
News
Seminario “New Trends in Mathematical Statistics II” en homenaje al Dr. Ricardo Fraiman
Del 16 al 18 de diciembre, el Instituto de Matemática y Estadística Rafael Laguardia, en Montevideo, Uruguay, fue sede del seminario “New Trends in Mathematical Statistics II”, organizado en homenaje a la trayectoria del Dr. Ricardo Fraiman. Fraiman se desempeñó como profesor plenario y luego como director del Departamento de Matemática y Ciencias entre 1998 y 2013, dejando una huella significativa en la disciplina.
¡Octavo Encuentro del Seminario de Estadística Matemática Multisede en Argentina!
El pasado jueves 28 de noviembre, se celebró el octavo y último encuentro del Seminario de Estadística Matemática Multisede en Argentina, un evento de gran relevancia para la comunidad de investigadores y profesionales de la estadística matemática del país. En esta ocasión, tuvimos el honor de contar con la participación especial del Dr. Alejandro Cholaquidis, investigador de la Universidad de la República, quien brindó una conferencia titulada "Dimensiones y sus estimaciones".
Se entregaron los premios del Concurso “Contar con Datos" 2024
Organizado por la Subsecretaría de Ciencia y Tecnología y el Data Science Lab de la Universidad de San Andrés, en su cuarta edición se galardonaron los proyectos más destacados que promovieron el uso de datos abiertos para visualizar información.
