Facundo Gilles Email and Phone Number

Computational Methods is an introduction to the world of linear algebra and its applications in computing. Throughout the course, fundamental concepts of matrix algebra, vector space geometry, and optimization methods such as linear programming are explored. The course strikes a balance between theory and practice, providing a solid understanding of key concepts in linear algebra and the necessary tools for programming these techniques in numerical computing frameworks using Python. By the end of the course, students will be prepared to use computational methods in applied problems ranging from engineering and economics to computer graphics and data science.

Sports analytics:The primary objective was to implement state-of-the-art models for assessing the performance of soccer players, leveraging thorough research on specialized publications. Furthermore, a significant emphasis was placed on developing customized data visualizations for effectively communicating game insights derived from these advanced models.

In my role, I held primary responsibility for visitor segmentation and optimizing marketing strategies, with a specific focus on training xgboost models. Additionally, I took the initiative to deliver corporate talks, aimed at introducing the marketing team to the significant potential of applying Machine Learning techniques in the field of marketing. Furthermore, I conducted dedicated sessions aimed at enhancing the team's understanding of Python dataclasses and the fundamental principles of code design.

As a Data Scientist, I had the opportunity to work on various aspects of the end-to-end development and deployment of both supervised and unsupervised ML models. I gained proficiency in utilizing Python and PySpark to create proof-of-concept models, which helped streamline our processes. I also automated ML models using popular Python libraries such as pandas, numpy, sklearn, xgboost, mllib, papermill, and multiprocessing, among others.In my recent projects, I had the privilege of contributing to the following key initiatives: Audience Segmentation: Objective: To identify, describe, and scale subgroups within a given audience across the full database. Challenge: Developing an unsupervised model (clustering) and determining a suitable metric for selecting the optimal number of segments. Approach: I had the opportunity to build this project from scratch using pyspark, utilizing the k-means approach. To evaluate the stability of the results, we employed normalized mutual information as a metric. Consumer Product Goods: Objective: Scaling knowledge from transactional data to the entire database. Challenge: Effectively preprocessing the data and optimizing the model. Approach: I developed this project from scratch, using an xgboost model. We addressed preprocessing challenges and focused on optimizing the model to ensure accurate predictions.

Ayudante Diplomado Ordinario con dedicación simple, en las cátedras de Física Experimental I y Física (CIBEX), Taller de enseñanza de la Física.

Title: Investigation of Physicochemical Properties of Solid-State Nanopores Modified with Polymer MonolayersAbstract: In this thesis, differential equations were derived to describe the thermodynamic state of a complex system confined within solid-state nanopores. Numerical calculation techniques were applied to discretize these equations, and subsequently, high-performance computing (HPC) methods were implemented to solve them. The primary code for solving these equations was developed using Fortran90, while additional scripts in Bash and Python were created to facilitate the management of computational experiments and the analysis of resulting data. The findings of this research were published in reputable journals within the field, contributing to the existing body of knowledge.

Ayudante Alumno de la Facultad de Ciencias Exactas, cargo ordinario con dedicación simple, rentado.Participe como ayudante en materias de la carrera Lic. en Ciencias Físicas.

Scholarship Title: Training for the Pharmaceutical IndustryDuring this scholarship, under the guidance of Dr. Daniel Vega and Dr. Griselda Polla, I acquired hands-on experience in utilizing calorimetric techniques and preparing comprehensive reports specifically tailored to the pharmaceutical industry. The techniques employed encompassed Thermogravimetry (TGA) and Differential Scanning Calorimetry (DSC), enabling me, along with my dedicated research team, to determine critical parameters such as the eutectic point, purity level, and characterization of phase transitions. Together, we conducted parallel research projects, leveraging our collective expertise, which culminated in the publication of a scientific paper in a reputable journal within the field.