Here I list noteworthy projects that I have built (or added to) either alone or with a team.

Spotlight Projects

☁️ Berlin PM2.5 Spatiotemporal Modeling

  • In this project, I built a data pipeline that scrapes a website daily for sds011 sensor data, does ETL, does inference, and serves a simple front-end (internal to the university network). Each component was containerized with docker and deployed on the cluster with kubernetes.
  • I used Amazon’s Chronos2 time series foundation model and ordinary kriging to do spatiotemporal modeling.
  • GitHub

📊 tab-err - Tabular Data Error Generation Library

  • Working at the BHT’s Calgo Lab with Sebastian Jaeger I added to the tab-err, realistic errors in tabular data, package on PyPi.
  • Wrote basic tests, developed a high level api, and modified some other error types as well as worked on bug fixes in python.
  • PyPi
  • GitHub

🗄️ Tax Law RAG System

  • In this project, I worked on implementing a RAG system. This included fine tuning BERT on a kubernetes cluster, comparing vector databases such as Annoy and FAISS, and using LangChain to build the pipeline.
  • I worked with one other student and I worked on English data while they worked on German data.
  • Disclaimer: The GitHub is built like research code, other projects do a better job of indsutrial structure.
  • Presentation
  • Vector DB Notebook
  • RAG Notebook
  • GitHub

🪙 Dynamic Pricing Competition 2026

  • This was a long running project where I iterated on various designs for a revenue-maximizing algorithm under competition in a duopoly simulation.
  • I worked with one other person with whom I loosely collaborated in terms of ideas + data exchange.
  • Placement (TBD… competition simulations are in progress)
  • Competition Website
  • Presentation 1 Presentation 2 Presentation 3 Presentation 4
  • GitHub Repo is private

🦜 LangGraph Agentic Email Answering Demo

  • This project implements the demo from the article Thinking in LangGraph. It was done with a group of 5 students.
  • I worked on serving the LLM on the university compute cluster (Nvidia A100 80GB GPUs), implementing the agent for our purposes, and “plumbing together” the LLM + Agent.
  • Presentation
  • GitHub

⚾ ML Baseball Analytics

  • In this project, I worked with and led a group of 3 other students to create a report covering the prediction of next-season batting average given the current season’s player statistics.
  • We implemented several machine learning models including gradient boosted decision trees and utilized XAI techniques including SHAP.
  • We did the project in R Markdown.
  • Report
  • Github

🕵️ CIA World Factbook Data Visualization

  • In this project, I worked with a group of 4 other students to create an R Markdown report on the CIA World Fact Book to survey data visualization techniques.
  • We were guided through the analysis by 5 research questions, the last two were done by me.
  • Report
  • GitHub
  • CIA World Fact Book

☁️ Weather Time Series Forecasting

  • In this project, I worked with a team of 2 other students to implement various time series forecasting models.
  • We utilized kubernetes, docker, and VSCode Remote SSH to prototype models on the BHT Berlin’s Nvidia V100 & A100 GPUs.
  • I scraped the website of my friend’s weather station to acquire the data and implemented two models.
  • Presentation
  • GitHub

🌐 K-Means Clustering of Cities

  • Implementation of the K-Means algorithm to cluster high population cities based on geographic coordinates.
  • I wrote this in R Markdown for fun.
  • Report

4️⃣ Anscombe’s Quartet

  • Details the importance of data visualization by an exploratory analysis of Anscombe’s Quartet in R.
  • Written in R Markdown.
  • Report

🏦 Messenger Bot

  • In this project, I setup messaging with the Telegram API, GitHub actions, and yfinance to ping my phone each day before the US Stock Exchange opens with information about the S&P 500 and crypto.
  • A future direction I am interested in is having LLMs summarize news articles and send a daily report to my phone from a curated list of sources.
  • GitHub

☁️ Business Intelligence Presentation

  • This is a presentation for a team project to analyze data from a 2006 AOL USA search query dataset which we hosted as an Exasol database on a Virtual Machine.
  • We were required to augment the database with another dataset, so we chose weather events in the USA during 2006.
  • The skills developed were: SQL, Python, OLAP, ETL, Data Visualization, Tableau, and EDA.
  • Presentation

⚡ Berlin Electric Vehicle Charger Geo-Visualizer

  • In this project, I loaded data from various German government sources about the population and charging stations in various postal codes in Berlin.
  • A heatmap overlay of a map of Berlin, subdivided by postal code is presented with options for viewing population, number of charging stations, and estimated new station demand.
  • Finally, a suggestion box functionality allows users to input suggestions attached to a given postal code.
  • Streamlit Page

🪙 Income Tax Calculator

  • In this application I loaded 2020 IRS data and used linear interpolation of tax brackets to compute the estimated median income of various zip codes in the United States.
  • Streamlit Page
  • Data

🤖 NumPy Feed Forward Neural Network

  • In this project, I implemented (alone, in NumPy, without the use of LLMs) a customizable feed forward neural network that can have an arbitrary number of layers and hidden units.
  • This was done from the absolute basics, just matrix & vector operations to implement forwardpropagation, backpropagation, and minibatched stochastic gradient descent.
  • GitHub

🏠 Housing Price Prediction Report

  • In this project, I worked with a team of 3 other students to apply and compare several different statistical learning methodolgies in R on a real estate dataset from Kaggle.
  • Report
  • GitHub

🎓 Computer Science BS Senior Project Writeup

  • This project was the culminating work of my senior research project in my bachelor’s of computer science.
  • I worked with a team of 3 people to build an applied deep learning model in Python using PyTorch, NumPy, Pandas, and Astropy to predict parameters of binary star systems.
  • Report
  • GitHub

📈 Data Mining Analysis of Energy Economics Time Series

  • In this project, I worked with one other student to analyze a set of time series concerning energy economics data.
  • During this project, we worked with faculty in the department of business and economics as well as the department of computer science.
  • The main techniques employed were clustering of time series and sequence mining. Traditional techniques for forecasting were not explored.
  • Report
  • GitHub

⚙️ Toy Operating System

  • In this project, as we worked through the textbook: Operating Systems Concepts 10th Edition, we had to individually implement (in KPL & Assembly) a toy operating system, the Blitz OS.
  • Due to academic integrity constraints I cannot publish my solution for this but I found the course instrumental in developing a deepened understanding of how operating systems work.
  • Book
  • Blitz OS Description
  • Blitz OS GitHub

⚙️ lsdir Implementation in C

  • This was a midterm live coding question which I did before the advent of ChatGPT.
  • We were given only 50 minutes to complete the program but I managed to get full points including extra credit.
  • GitHub

📡 TCP Client Server

  • In this class project, I implemented a client server architecture that allowed for the communication of messages using TCP/IP and UNIX sockets in C.
  • Assignment Description
  • GitHub

📡 UDP Load Balancing Server

  • In this class project, I implemented a UDP load balancing server using UNIX sockets in C.
  • The assignment description is on the GitHub but in MS Word…
  • GitHub

📝 Text Editor

  • In this assignment, I followed a lab to implement a text editor in Java. While not the most involved project, it is still a fun one.
  • GitHub