mirror of
https://git.sr.ht/~seirdy/seirdy.one
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Fix resume
Fix some resume details and put its file in a subdir.
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date: "2021-01-23T12:21:38-08:00"
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keywords: intern, python, golang, go, lua, moonscript, shell, bash, zsh, posix, java,
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haskell, C, influxdb, influxdata, chronograf, grafana, kapacitor, numpy, scipy,
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pandas, jupyter, docker, podman, buildah, skopeo, kubernetes, openshift, cloud
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native, physics, jenkins, git, gitlab, github, linux, bsd, red hat, fedora, debian,
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ubuntu, opensuse, suse
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title: Rohan Kumar
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---
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<https://seirdy.one/> | <seirdy@seirdy.one>
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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.
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Education: Lewis and Clark College
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----------------------------------
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Bachelor of Arts, Major in Math and Computer Science
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Fall 2018 - Spring 2022 (expected)
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### Selected Coursework
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- Computer Architecture/Assembly Lang
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- Programming Language Structures
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- Cybersecurity Fundamentals
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- Networking Basics (CCNA)
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Work Experience
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---------------
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### June-August 2019: Software Engineering Intern, SAP Ariba, Palo Alto
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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.
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Selected Projects
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-----------------
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Git repositories on [Sourcehut](https://sr.ht/~seirdy), [GitHub](https://github.com/Seirdy), and [GitLab](https://gitlab.com/Seirdy)
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### [Clogstats](https://sr.ht/~seirdy/clogstats)
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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.
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### [MOAC](https://sr.ht/~seirdy/MOAC/)
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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.
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Technical Skills
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----------------
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### Cloud-Native Technologies
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Familiar with Docker Podman, Buildah, Skopeo, Kubernetes, OpenShift 4.
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### Operating Systems
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Linux, BSD, Windows, macOS. Able to adapt to any UNIX-like environment.
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### Linux
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Familiar with various distributions, inc. Fedora, RHEL, Debian, Ubuntu, and OpenSUSE.
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### Monitoring Systems
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Grafana and the InfluxData stack (InfluxDB, Telegraf, Kapacitor, Chronograf).
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### Programming Languages
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Proficient in Go, Python, Lua/MoonScript, and shell languages (Bash, Zsh, POSIX sh).
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Familiar with Java, C, SageMath, and Haskell.
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### Python
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Familiar with math and data science libraries such as the SciPy stack, Jupyter notebooks, and Pandas.
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### Other Tools
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Git, Continuous Integration/Delivery (Jenkins, GitLab CI, Travis CI), Nginx.
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54
content/resume/index.md
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54
content/resume/index.md
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---
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date: "2021-01-23T12:21:38-08:00"
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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
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title: Rohan Kumar
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---
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<https://seirdy.one/> | <seirdy@seirdy.one>
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Detail oriented, committed, self-motivated, open-source enthusiast proficient in Python, Go, Linux/UNIX systems, and cloud-native computing looking for an internship.
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Education: Lewis and Clark College
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----------------------------------
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Bachelor of Arts, Major in Math and Computer Science. Fall 2018 - Spring 2023 (expected)
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Certifications
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--------------
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CompTIA Security+ (SY0-601), Dec. 2021. Verification available upon request.
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Work Experience
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---------------
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### June-August 2019: Software Engineering Intern, SAP Ariba, Palo Alto
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Developed an anomaly detection and seasonal forecasting tool in Go (Golang) to smooth over one million historical points from InfluxDB, real-time, in an extensively configurable manner. The approach moved processing in-memory to achieve a speedup of several orders of magnitude with a minimal footprint. Use cases included detecting a server's anomalous spikes in resource usage and analyzing trends in environmental data. Used Go, shell, and Grafana.
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### June-August 2021: Software Engineering Intern, Cisco, Remote
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Worked with a remote team on YAML-based data serialization and validation of data streamed in from Redfish and Selenium test suites to ensure compliance with a schema. Developed Redshift and Selenium tests for Cisco Intersight's APIs and user interface. Used Python.
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Portfolio
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---------
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Git repositories mirrored across [Sourcehut](https://sr.ht/~seirdy), [GitHub](https://github.com/Seirdy), and [GitLab](https://gitlab.com/Seirdy). Selected projects:
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### Clogstats: [sr.ht/~seirdy/clogstats](https://sr.ht/~seirdy/clogstats)
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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.
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### MOAC: [sr.ht/~seirdy/MOAC](https://sr.ht/~seirdy/MOAC/)
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Analyze password strength given physical limits to computing, and generate secure passwords. 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. Extensively tested. Written in Go.
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Technical Skills
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----------------
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- Cloud-native technologies: Docker Podman, Buildah, Skopeo, Kubernetes, OpenShift 4.
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- Operating systems: Linux, BSD, Windows, macOS. Able to adapt to any UNIX-like environment.
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- Linux: various distributions, inc. Fedora, RHEL, Debian, Ubuntu, and OpenSUSE; familiar with components like Systemd, SELinux.
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- Monitoring systems: Grafana and the InfluxData stack (InfluxDB, Telegraf, Kapacitor, Chronograf).
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- Programming languages: Proficient in Go, Python, Lua/MoonScript, and shell languages (Bash, Zsh, POSIX sh). Familiar with Java, C, SageMath.
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- Python: Familiar with math and data science libraries such as the SciPy stack, Jupyter notebooks, and Pandas.
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- Other tools: Git, Continuous Integration/Delivery (Jenkins, GitLab CI, Travis CI), Nginx.
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