I am an experienced mathematician with a passion for data science, cybersecurity, and artifical intelligence.
With a strong foundation in applied mathematics and analytical problem-solving, I am detail-oriented, responsible, and continually expanding my knowledge. I am eager to contribute in the fields of data science, artificial intelligence, cybersecurity, database management, and cryptography.
I am fascinated by the intersection of mathematics, data science, artificial intelligence, and cryptography. Mathematics gives me the tools to think rigorously and abstractly, while data science provides the means to uncover patterns and insights from complex information. Artificial intelligence excites me for its ability to push the boundaries of what machines can learn and do, and cryptography inspires me with its role in securing information and enabling trust in our digital world. What motivates me most is how these fields come together: the mathematical foundations that drive both AI and cryptography, the use of data to strengthen intelligent systems, and the need for privacy and security in an increasingly data-driven society. I am eager to explore these connections further and contribute to advancing knowledge and applications where these disciplines converge.
- Data cleaning, exploration, analysis, and visualization (Python, R, Rust)
- Big data (PySpark, MongoDB, )
- Database management (MySQL, PostgreSQL)
- ML Engineering (MLFlow, FastAPI, Docker)
- MLOPs (Docker, CI/CD, Deploy, monitoring)
- SIEM platforms (Splunk, Elastic Stack)
- Network Monitoring and Analysis (Wireshark, Nmap, Tcpdump, Snort)
- Vulnerability Assessment and Penetration Testing (Nessus, Metaploit, Burp Suite, OpenVAS, Kali Linux, John the Ripper)
- Cryptography (VeraCrypt, Kruptos 2, Boxcryptor, Docker)
Mathematics is my original area of training. My areas of study and interests include:
- Mathematical Logic (Proof Theory; Computability Theory)
- Abstract Algebra (Group Theory; Lie Groups & Lie Algebras; Representation Theory; Category Theory; Universal Algebra; Computational Algebra)
- Number Theory
- Statistics and Probability
Post-Quantum Cryptography Visualization Dashboard
Major League Baseball RBI Regression
Data-Cleaning Pipeline & Dashboard
Video Games Data Analysis and Machine Learning Recommender
Google Search Analysis and Visualization
Text Recognition/Detection with OpenCV and OCR (Optical Character Recognition)
Anomaly Detection in Time Series
Synthetic Images with DCGANs (Deep Convolutional Generative Adversarial Networks)
Data-Cleaning Pipeline & Dashboard
Encrypted Network Traffic Classification using Machine Learning
Post-Quantum Cryptography Visualization Dashboard
Encrypted Network Traffic Classification using Machine Learning
Lockbox — A Modern File & Secret Encryptor
Lie Groups and Representation Learning: Learning Symmetry-Informed Neural Networks