Felipe Cueto

Table of contents

## Summary Colombian and Spaniard, Bilingual (English/Spanish), Systems and Computing Engineer, from the Universidad de Los Andes (September 2018). With a Masters of Science in Systems and Computing Engineering (February 2021) focused on Artificial Intelligence. With experience in advertising, academic data analysis, and desktop application development. Interested in software development, artificial intelligence, and robotics. Knowledge in programming language theory, data analysis, machine learning, semantic networks, and full stack development. ## Academic Training ### Undergraduate degree in Systems and Computing Engineering Universidad de los Andes Bogota, Colombia (2018) ### Masters of Science in Systems and Computing Engineering Universidad de Los Andes Bogota, Colombia (2021) ## Academic work and achievements ### “Graph Comparison” For my graduate project (2018), I implemented several graph similarity algorithms. The algorithms were used in a semantic graph analysis project. The project culminated in an article titled “Comparing Graph Similarity Measures for Semantic Representations of Documents” (Manrique et al., 2018). (Project link, Paper link) ### “Steps Towards a Predictive Semantic Resource Recommendation System for University Students” For my master's thesis (August 2019 - November 2020), I created the underlying systems necessary for the development of a resource recommendation system for university students. The system used machine learning to predict students’ performance in future courses based on their academic history. In parallel, I developed a system to analyze and connect university courses using semantic information. The project detected a significant correlation between these two systems, which suggests that an important link between 2 branches of Artificial Intelligence (machine learning and semantic networks) exists in academic data. (Thesis link) My master's thesis resulted in 2 academic articles: "Predicting Students' Course Performance Using Classification and Regression Algorithms” (Cueto-ramirez, Marino, Manrique, & Romero, n.d.) (Manuscript) and "Analyzing Feature Importance in a Course Performance Prediction Model by Detecting Semantic Relationships” (Cueto-ramirez, Marino, Manrique, & Bejarano, n.d.) (Manuscript) ## Work Experience ### Digital57 (https://digital57.co/) June 2017-December 2017 Data Engineer Intern I was in charge of the internal data management of the company. Among my responsibilities were: sending SMS to appropriate audiences, handling reports, metrics, and data visualizations for internal (employee) and external communication (with customers), supporting the design team with the implementation of tools and solutions for landing pages and emails. Achievements: I designed and developed the Digital57 customer and employee platform. This project involved designing and deploying the server infrastructure on an AWS virtual machine, designing and deploying a web page using REACT, and designing and deploying the Java back-end with a MySQL database. ### University of Los Andes (https://uniandes.edu.co/) August 2018-August 2020 Graduate Assistant Assistant to the director of the Masters in Science in Systems and Computing Engineering program with various support responsibilities including: monitoring meetings of the administrative board of the program, data analysis, and data collection platform development. Achievements: I designed and developed a system for handling Cursera course file information. This system allowed course resources to be tagged with semantic tags connected to Dbpedia. ### WebGameFramework December 2020-May 2021 Full Stack Developer As a personal project, I developed a framework which allows developers to create web games using HTML, CSS, and JavaScript game development using web tools. The framework avoids using the HTML canvas tool to ensure that games can use HTML, CSS, and JavaScript libraries to enhance the users experience. Achievements: A game system compatible with a wide variety of tools and web libraries. A web tool that optimizes server costs by compressing transferred resources into zip files. An execution environment with high security to prevent possible attacks on the end user. ### Hummingbirds AI (https://hummingbirds.ai/) June 2021-Present Back End Developer Although my official title working for Hummingbirds is Back End developer, I’d argue that my duties have been expanded to Full Stack developer since being hired. At Hummingbirds I’ve worked on two windows applications which integrate AI systems to improve user security and user privacy. GuacamoleCX was an application meant to improve security at call-centers. The app used 2 cameras, birds eye view camera, and a front facing camera to monitor a users actions, and record any suspicious activity for later inspection. The app was developed using Python, and was connected to a python backend and a REACT frontend. GuacamoleID is an application designed to run continuous face matching on your desktop computer. As soon as you walk away, the system automatically blocks your computer screen to protect your privacy. And as soon as you come back to your PC, the system automatically recognizes you, and unblocks your PC. We developed a prototype with python, and a production app with C++/QT. Achievements: Integrated computer vision code to a GUI interface. Managed communication between a native application and a remote server to handle a user login, an app heartbeat, and secure video transfers. Managed complex dynamic inter-thread communication. ## Skills

Programming Language	Primary	Secondary
C++	X
Python	X
HTML, CSS, JS	X
Java		X
SQL		X
Python		X

Tools	Primary	Secondary
QT	X
Scikit-learn		X
Jupyter		X
Power-BI		X

Fields of Knowledge	Primary	Secondary
Multi-Threading	X
Desktop Application Development	X
Machine Learning		X
Front End Development		X
Back End Development		X
Data Mining		X

## Publications (Manuscript) Cueto-ramirez, F., Marino, O., Manrique, R., & Bejarano, S. (n.d.). Analyzing Feature Importance in a Course Prediction Model by Detecting Semantic Relationships. (Manuscript) Cueto-ramirez, F., Marino, O., Manrique, R., & Romero, L. (n.d.). Predicting Students ’ Course Performance Using Classification And Regression Algorithms. Manrique, R., Cueto-Ramirez, F., & Mariño, O. (2018). Comparing graph similarity measures for semantic representations of documents. In Communications in Computer and Information Science (Vol. 885). https://doi.org/10.1007/978-3-319-98998-3_13 ## Other English 90% TOEFL 102/120 Spanish 95%