Welcome!

I'm Arjuna, a Gonzaga Alum and Software Developer from Roseville, Minnesota.

I’m interested in how technology and people intersect—whether that’s developing reliable software, improving processes, or helping teams and clients achieve their goals.

I take pride in learning quickly, solving problems with care, and bringing a thoughtful approach to everything I work on.

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About Me

My full name is Arjuna Herbst and I'm a big Manchester City & Gonzaga Basketball fan. I love getting outside and taking pictures of nature.

Currently, I'm a backend dev at Hatchproof, a behavioral-science backed, AI-powered platform built to help companies hire and retain people who thrive in their roles.

My Skills in Programming Include: Python, SQL, Node.js, React, Vue.js, HTML/CSS, AWS, and more.

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Projects

Space

3D Web Page

Built a web page with 3D animations and models using Vite.js with Three.js. May not load properly on smaller devices.

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KNN Clustering

NBA Data Analysis

Using Jupyter Notebook, I implemented KNN clustering to analyze NBA 2022-23 player data and find trends and patterns within the data.

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Micro SaaS

ultraLite

Using Node.js, Express, React.js and PostgreSQL, I created a gear store web application for backpackers. Users can build custom gear bags, and track pack weight.

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React Native + Supabase

Weather App

Using React Native and Supabase, I developed a weather app that provides real-time weather updates and forecasts. Map view is available and you can tap anywhere to get the conditions.

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Previous Coursework

CPSC260 Computer Organization

This course covered the basics of computer organization and architecture. This course was taught in C and assembly language. Topics covered included: CPU articheture, ALU's, logic gates, registers, calling functions in assembly, and more. Course Github repo below.

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CPSC323 AI/ML

This course served as an introduction to the implementation of machine learning algorithms in Python using Google Colab. Topics covered incduded: linear regression, logistic regression, A* search, model fitting, LLM's, and more. Course Github repo below.

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CPSC321 Database Management

CPSC321 was a course that covered the basics of relational dat abase management. Languages used included SQL, Javascript (Node.js), and Python. Topics covered included: ER diagrams, advanced and basic SQL queries, querying a database from a frontend web application (see project link), and more. See YouTube video on this course's final project below

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CPSC450 Algorithm Design & Analysis

This course covered principles and techniques of computational complexity. Topics could include dynamic programming, B-trees, minimum spanning trees, Floyd and Warshall algorithms, various string matching algorithms, computational geometry, exponential growth of round-off errors, NP-completeness and reducibility.

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CPSC326 Organization of Programming Languages

In this course, I learned the main components of programming languages and the architecutre of intepreters and compilers. We used Java as a base language to implement our own language called "MyPL". This involved building a lexer, parser, type checker, VM, and code generator to compile MyPL code to bytecode. Also covered was OCaml and functional programming.

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CPSC322 Data Science Algorithms

This course provided a detailed overview of the processes and techniques used in creating data science applications. Topics included data preparation and cleaning, summary statistics, basic data visualization techniques, feature selection, discretization, k nearest neighbors, naive bayes, decision trees, ensemble methods, apriori rule mining, and k-means clustering.

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