Master's Student in Computer Science at CINVESTAV. Passionate about AI, Machine Learning, and Computer Vision.
Pipeline completo de visión por computadora: captura manual de imágenes, extracción de características geométricas, entrenamiento de un clasificador Naive Bayes Gaussiano y predicción en tiempo real con cámara.
Reemplazo del multiplicador secuencial del RISC0 por uno combinacional en Verilog, medición del nuevo throughput y comparativa con Tarea 6.
Implementación de instrucciones TICS en RISC0, evidencia de ciclos y comparativa de Throughput frente al diseño de hardware del oscilador caótico.
Passionate about AI, algorithms, and technology. Currently focused on Machine Learning and Deep Learning at Cinvestav IPN.
Read full bio →Advanced study of deep neural networks, covering modern architectures and applications in complex data.
In-depth analysis of computational problems, complexity classes (P, NP, NP-Complete), and limits of algorithmic efficiency.
Exploration of modern generative models and architectures for synthesizing text, images, and complex systems.
Principles and architectures for Computer-Supported Cooperative Work (CSCW) and distributed collaborative applications.
Supervised learning, neural networks, ensemble methods, and fundamental ML pipelines.
Processor architecture, primarily focusing on RISC-V and RISC0, assembly programming, and performance optimization.
Fundamental concepts including automata theory, formal languages, computability, and complexity theory.
Strategic decision-making analysis. Competitive scenarios, Nash equilibrium, and applications in CS.
Efficiency, data structures, and computational complexity.
Intro to AI principles, search, logic, and intelligent agents.
Software engineering, object-oriented design, and design patterns.
Logic, combinatorics, graph theory, and mathematical proofs.