I've always known that technology would be my path. From my early years, I was curious about how things work, and this curiosity naturally grew into programming and building systems.
Now I'm a Computer Science student (Data Science concentration) at Gonzaga University, graduating in 2026. My main focus is software engineering, data science, and machine learning.
I don't just think about code — I care about architecture, business value, and creating products that people actually use. Clients, teammates, and professors often highlight my ability to combine technical depth with practical results.
Almost every project I've been part of has brought new recommendations and new opportunities — and that's what I'm most proud of.
Working Now
Advanced log analysis system designed to evaluate company log data and identify anomalies using state-of-the-art machine learning techniques. The project combines multiple approaches including deep learning, natural language processing, and statistical modeling to detect unusual patterns, security threats, and system irregularities in large-scale log datasets.
Stack: LSTM, BERT, Tokenization, Drain3, Gated Recurrent Unit, Markov Models, Python, Deep Learning
In Development
Built control and simulation software for Unitree B2 and H2 robots, including MuJoCo-based testing and RNN-driven motion behaviors. Focused on reliable locomotion pipelines and real-time tuning workflows.
Stack: C++, Python, MuJoCo, RNN
Coming Soon
Recent Projects
A high-performance soft real-time trading system in C demonstrating advanced OS concepts: lock-free ring buffers, POSIX threads with CPU affinity and RT scheduling, explicit state machines, deadline-based scheduling (no sleep()), structured logging, latency histograms (p50/p95/p99), and fault injection for robustness testing.
Stack: C11, POSIX Threads, Lock-free Data Structures, CPU Affinity, Real-time Scheduling, Monotonic Clocks
A web-based enrollment system that helps students choose courses and avoid scheduling conflicts. It provides advanced filtering, real-time conflict detection, and personalized pathways to graduation. Built with Flask using Blueprints, it also supports advisor feedback and integration with degree requirements.
Stack: Flask, Python, Supabase, React, Scikit-learn, TensorFlow
A specialized ML system for 15-minute S&P 500 prediction optimized for Iron Condor options strategies. The system identifies low-volatility periods where markets trade sideways, enabling profitable options spreads. Uses proprietary algorithms (details restricted by NDA).
Stack: Python, Machine Learning, Deep Learning, Data Science
A groundbreaking NLP research project focused on creating an intelligent dictionary system that understands word meanings based on syntactic context. The core challenge was building a comprehensive dictionary from Wikipedia's entire corpus and training models to assign correct word meanings based on grammatical position within sentence structures.
Other Projects
Chess Engine (Python): Complete chess game implementation featuring move validation, check/checkmate detection, and AI opponent using minimax algorithm with alpha-beta pruning. Includes clean OOP design with separate classes for pieces, board state, and game logic.
Monopoly Terminal Game (C++): Full console-based Monopoly implementation with property management, banking system, chance/community cards, and turn-based gameplay. Demonstrates advanced C++ concepts including inheritance, polymorphism, and memory management.
Stack: Python, C++, Object-Oriented Programming, Game Logic Algorithms
Personal wardrobe management system designed to optimize clothing usage and outfit planning. Features usage pattern analysis, wear frequency tracking, and intelligent outfit recommendations based on weather, occasion, and personal style preferences. Includes data visualization for clothing utilization insights and wardrobe optimization suggestions.
Stack: JavaScript, Python, Data Visualization, Personal Analytics
Sup Olymp Bot: Educational assistant helping students find optimal programming olympiads for university admission without entrance exams (БВИ). Features competition database, eligibility checking, and personalized recommendations based on student profile and academic goals.
Visa Slot Alert Bot: Real-time monitoring system for visa appointment availability across multiple consulates. Implements web scraping, notification system, and user subscription management with instant alerts when slots become available.
Stack: Python, Telegram Bot API, Web Scraping, Automation, Notifications