Bridging mathematics with practical solutions. Currently pursuing a Masters in Data Analysis and Engineering, specializing in Machine Learning algorithms and their mathematical foundations.
With a strong foundation in mathematics and currently pursuing a Masters in Big Data, I specialize in developing machine learning solutions that are both theoretically sound and practically effective.
My approach combines rigorous mathematical analysis with innovative algorithmic design, focusing on interpretable models and scalable solutions for real-world problems.
I'm passionate about bridging the gap between abstract mathematical concepts and their practical applications in artificial intelligence and big data.
Linear and Abstract Algebra, Probability, Statistics
Deep Learning, Neural Networks, Ensemble Methods, NLP
Python, R, SQL, TensorFlow, PyTorch, Scikit-learn
Statistical Analysis, Visualization, Big Data Processing
The application consists of a platform for managing processes associated with charcoal production.
The automatic update of charcoal stock, company revenue, and profit whenever a sale occurs is just one example of the app functionalities.
Developed a web-based application for digitizing university sports processes, applying systems modeling with Visual Paradigm and Agile methodologies via JIRA/SCRUM.
Created comprehensive documentation including use cases, prototypes in Figma, and architectural analysis before implementing a functional system with HTML/CSS/JavaScript and LocalStorage persistence.
The project followed an iterative development approach with three sprints.
A clinical trial evaluated a novel cholesterol treatment through comprehensive statistical analysis using R and Python.
The study employed ANOVA, logistic regression, and power analysis with G*Power software to assess treatment effectiveness and predict outcomes.
A study was conducted to examine certain parameters related to mental and physical health and their impact on productivity.
A questionnaire was developed to gather data and we used Excel and SPSS to do Exploratory Data Analysis and Statistical Tests.
Analyzed impartial combinatorial games (Nim, Hackenbush), deriving winning strategies and safe positions through mathematical modeling, implementing winning algorithms
Modeled economic competition (Cournot/Bertrand) by developing a Python simulation with matplotlib visualization.