Final years ML student @ KTH. Also serving as the Head of Research @ KTH AI Society. I like infra and shipping things.

Moritz Kindler is the co‑founder and chief technology officer of StudyPDF, a Stockholm‑based venture that leverages AI to streamline PDF study workflows. With five years of experience as an AI engineer focusing on application development, Moritz combines technical expertise with a business background earned at Stockholm University after completing his Abitur at Luisen‑Gymnasium in Hamburg‑Bergedorf. Based in Stockholm County, he drives product innovation and oversees the company's technical strategy while actively sharing insights on Twitter (@moritzkindler) and LinkedIn.

AI-driven study materials, gamified learning experiences, product design, UI/UX, web design, front-end development (HTML/CSS/JavaScript, React), full-stack development, MVP/rapid prototyping, design systems, CMS integration, AI/ML prototyping (AI grader, real-time fact‑checking), hackathon organization and community engagement

StudyPDF — building AI-driven study materials and gamified learning experiences for PDF workflows: automatic note extraction, quiz generation, spaced-repetition and analytics. Also developing MVP AI prototypes (AI grader and a 48‑hour real‑time fact‑checking tool). Tech stack: Python ML models, React frontend, Node backend, CMS integrations; rapid prototyping and iterative productization.

I am a Driven engineer and fourth-year student at KTH Royal Institute of Technology, currently completing the first year of the Machine Learning Master's program. I specialize in bridging advanced Deep Learning (Computer Vision and OCR) with high-performance systems engineering. Currently, I work part-time as a Junior Machine Learning Engineer, focusing on deploying robust, cost-efficient infrastructure. I also serve as the Research Lead at the KTH AI Society, directing student research. I am eager to contribute rapid prototyping skills and system-level thinking to any project.

I am open to explore any area of AI/ML to expand my knowledge and try new things, from Generative AI and Reinforcement Learning to time-series analysis.

Extracting height data from topographical maps using OCR and segmentation

Inventor and first-year dual-enrolled student in Applied Physics and Materials Science at KTH Royal Institute of Technology. Previously dual-enrolled in high school with Örebro University, where I studied machine learning and computer science. I am the Ground Control Station Lead at KTH ÆSIR, involved in exploratory work related to a potential missile manufacturing defense collaboration with the Swedish military, and a researcher at the KTH AI Society.