---
date: "2021-01-23T12:21:38-08:00"
keywords: intern, python, golang, go, lua, moonscript, shell, bash, zsh, posix, java,
    haskell, C, influxdb, influxdata, chronograf, grafana, kapacitor, numpy, scipy,
    pandas, jupyter, docker, podman, buildah, skopeo, kubernetes, openshift, cloud
    native, physics, jenkins, git, gitlab, github, linux, bsd, red hat, fedora, debian,
    ubuntu, opensuse, suse
title: Rohan Kumar
---
<https://seirdy.one/> | <seirdy@seirdy.one>

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.

Education: Lewis and Clark College
----------------------------------

Bachelor of Arts, Major in Math and Computer Science

Fall 2018 - Spring 2022 (expected)

### Selected Coursework

- Computer Architecture/Assembly Lang
- Programming Language Structures
- Cybersecurity Fundamentals
- Networking Basics (CCNA)

Work Experience
---------------

### June-August 2019: Software Engineering Intern, SAP Ariba, Palo Alto

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.

Selected Projects
-----------------

Git repositories on [Sourcehut](https://sr.ht/~seirdy), [GitHub](https://github.com/Seirdy), and [GitLab](https://gitlab.com/Seirdy)

### [Clogstats](https://sr.ht/~seirdy/clogstats)

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.

### [MOAC](https://sr.ht/~seirdy/MOAC/)

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.

Technical Skills
----------------

### Cloud-Native Technologies

Familiar with Docker Podman, Buildah, Skopeo, Kubernetes, OpenShift 4.

### Operating Systems

Linux, BSD, Windows, macOS. Able to adapt to any UNIX-like environment.

### Linux

Familiar with various distributions, inc. Fedora, RHEL, Debian, Ubuntu, and OpenSUSE.

### Monitoring Systems

Grafana and the InfluxData stack (InfluxDB, Telegraf, Kapacitor, Chronograf).

### Programming Languages

Proficient in Go, Python, Lua/MoonScript, and shell languages (Bash, Zsh, POSIX sh).

Familiar with Java, C, SageMath, and Haskell.

### Python

Familiar with math and data science libraries such as the SciPy stack, Jupyter notebooks, and Pandas.

### Other Tools

Git, Continuous Integration/Delivery (Jenkins, GitLab CI, Travis CI), Nginx.