Hi, I'm Behsad.

I'm an American-German Computer Science student at TUM currently collaborating on machine learning research with MIT. I was a former software engineering teamlead at TUM.ai and engineering intern at Knowunity, BMW, and Check24.

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| about me

I'm a German-American computer science student at TUM. I have built tools across companies in various stages, going all the way up to 20M+ users, and am generally excited by the challenges that data introduces. My current interests are ML engineering, infrastructure, and reliability engineering. My appreciation for the technology landscape ultimately led me to join TUM.ai in 2023, where I have immersed myself in AI applications while leading the TUM.ai software engineering team and fostering collaborations with partners such as Google and Anthropic.


Here's a non-exhaustive list of technologies I currently use:

Go

Python

PyTorch

NumPy

TypeScript

Next

I also absolutely love speed-house and groove music.

| experience

20252025

Massachusetts Institute of Technology

Co-Author, Research Collaboration

  • Implemented ETL pipeline processing 150,000+ material systems.

  • Refactored graph lookups, improving latency by 60x (from ~30s to <0.5s).

  • Used graph convolutional networks (GCN) to represent material systems as graphs.

  • Implemented a factory pattern to construct graphs using SOTA embeddings models as node features.

Python

PyTorch

Geometric

NumPy

Pandas

20252025

Knowunity GmbH

AI Engineer Intern

  • Owned implementation and observability of an AI-summary feature with highest retention, garnering 25,000+ uses within 7 days of launch.

  • Integrated image extraction and re-insertion into AI-driven summaries with embedded LaTeX rendering for 4+ file formats.

  • Evaluated reliability of in-house AI request-gateway handling 10,000+ daily requests with retry and fallback logic.

Go

PostgreSQL

Python

BigQuery

AWS

20242024

BMW Group

Software Engineer Intern

  • Used React, Node.js, MongoDB and GraphQL to enable data aggregation in Earth's largest car simulation center.

  • Built a full-stack feature to persist 70+ data points on car simulation studies for 100+ researchers.

  • Automated 100% of issue creation and formatting for car simulation studies using the Jira API.

TypeScript

MongoDB

GraphQL

Node.js

React

20232024

TUM.ai

Software Engineer Team Lead

  • Led the development of a modular Next.js platform to track and review 1000+ applicants across multiple phases for events and recruitment.

  • Designed API using Next.js endpoints to persist 2000+ reviewer notes on potential candidates.

  • Dockerized PostgreSQL database with Prisma, integrated OAuth, and outlined RBAC features.

TypeScript

PostgreSQL

Next.js

Prisma

React

20222024

Check24 GmbH

Software Engineer Intern

  • Used Docker-in-Docker to periodically update dependencies in over 50 repositories using Renovate.

  • Decreased PHPStan errors by 50% and 70%, respectively in two internal repositories.

  • Refactored 15% of the codebase to support PHP 8.2 and increased unit test coverage by 40% in two repositories, leading to a talent pool nomination.

PHP

Symfony

Laminas

PHPUnit

Docker

| projects

Invenus - Night Club Ticket Sales Platform

Before scalable ticket ecommerce, I developed a full-stack application for selling night club tickets with 4 friends. I was in charge of client-side API calls in JavaScript and creating component-based web-pages for viewing feeds, events and e-mails.

Java

Spring Boot

React

Research Paper on Pathfinding algorithms

In high school, I authored a paper with reflection process, analyzing time efficiency of various graph algorithms such as A* Search. The paper earned an 'A' (Scale: A, B, C, D, E) and was selected by the computer science department as an exemplar of outstanding research.

Literature Review: Automated Bug Replay using LLMs

Wrote an exhaustive evaluation and summary of the ICSE paper, “Prompting Is All You Need: Bug Replay with LLMs” by Feng and Chen (2023). Proposed latency and accuracy improvements for programmatic bug replay using LLMs, earning the highest grade (1.0).

UnternehmerTUM Innovation Sprint Winner 2024

The innovation sprint is a week-long design-thinking challenge with 250+ participants, offered by UnternehmerTUM and industry partners. My team and I won the "Mobility" track by TUM Venture Labs, solving the issue of limited parking spaces. Pitched to an audience of 300+ people and got offered 4 digit funding.

Women in Tech: Coding Workshop

Led a three-day coding workshop during Covid-19, promoting STEM engagement among young women between the ages of 12 and 14. We created a gamified workshop format to incentivize collaboration between girls and boys.

Coding Society

The Coding Society is a high-school initiative I started to explore data structures and algorithms beyond standard curricula, hosting coding workshops for young learners, and organizing mini hackathons. We also proposed a pin-code locking system for the school campus to the board.

Designed and built by Behsad Riemer.

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