Detail oriented, committed and self-motivated, open-source enthusiast proficient in technologies related to Python, Go, Linux and UNIX systems, and cloud-native computing looking for an internship.
Bachelor of Arts, Major in Math and Computer Science
Fall 2018 - Spring 2022 (expected)
Developed an anomaly detection and seasonal forecasting tool in Golang using Triple Exponential Smoothing (Holt-Winters) techniques to smooth time series data. It was capable of scaling to over one million historical points from InfluxDB, real-time, in an extensively configurable manner. Use cases include detecting a server's anomalous spikes in resource usage and analyzing trends in environmental data.
Gathers IRC channel activity statistics from WeeChat logs and performs time-series analysis and forecasting on them. It can quantify, rank, and chart chatting activity over time and display forecasts. It can also detect anomalous increases in activity. Written in Python with NumPy and Pandas.
Analyze password strength given physical limits to computing. Computes theoretical limits to a brute-force attack limited by given physical quantities (mass, energy, power, temperature, etc.) and generates passwords to withstand them. This provides a future-proof understanding of password strength. Written in Go.
Familiar with Docker Podman, Buildah, Skopeo, Kubernetes, OpenShift 4.
Linux, BSD, Windows, macOS. Able to adapt to any UNIX-like environment.
Familiar with various distributions, inc. Fedora, RHEL, Debian, Ubuntu, and OpenSUSE.
Grafana and the InfluxData stack (InfluxDB, Telegraf, Kapacitor, Chronograf).
Proficient in Go, Python, Lua/MoonScript, and shell languages (Bash, Zsh, POSIX sh).
Familiar with Java, C, SageMath, and Haskell.
Familiar with math and data science libraries such as the SciPy stack, Jupyter notebooks, and Pandas.
Git, Continuous Integration/Delivery (Jenkins, GitLab CI, Travis CI), Nginx.