Tolgay Atınç Uzun
Machine learning scientist working on LLM-driven AutoML and neural architecture search.
About
I am a machine learning scientist at the Computer Vision Lab, CAIDAS & IFI, University of Würzburg. My research focuses on LLM-driven AutoML: using large language models to design, generate, and optimize neural network architectures in a closed loop.
I graduated as the 2nd ranked student of TED University's Faculty of Engineering (GPA 3.94/4.00) with a background in simulation software (C++, Unreal Engine), computer vision, and image processing.
Germany
Skills
- Python
- PyTorch
- Large Language Models
- Neural Architecture Search
- AutoML
- Computer Vision
- OpenCV
- Image Processing
- CNN
- C++
- Unreal Engine
- Java
- C
- SQL
- Git
Experience
Machine Learning Researcher
- First author of two papers on closed-loop LLM-driven channel configuration search for vision models (arXiv 2601.08517, 2607.20516).
- Contributor to NNGPT, an LLM-powered AutoML framework that generates, evaluates, and learns from neural network architectures.
- Contributor to LEMUR 2, a dataset of 14,000+ architectures and 750,000+ training records for LLM-driven AutoML.
Software Engineer
- Developed simulation software using C++ and Unreal Engine.
- Worked part-time while completing my bachelor's degree.
Computer Engineering Lab Tutor
- Taught Java in computer engineering lab sessions.
- Supported students in programming assignments and coursework.
Research and Development Intern
- Worked on image processing and computer vision with OpenCV and CNNs.
- Developed prototypes with Unity.
Software Developer (Intern)
- Built web applications with Java and Vaadin.
Software Developer (Intern)
- Developed desktop applications using C# and Windows Presentation Foundation (WPF).
Projects
NNGPT: Rethinking AutoML with LLMs
Open-source framework turning an LLM into a self-improving AutoML engine for computer vision: architecture synthesis, HPO, accuracy prediction, and NN-RAG.
Closed-Loop LLM Channel Configuration
First-author research: using LLMs to search channel configurations of vision models via conditional code generation with accuracy feedback (CIFAR-100).
Education
BSc in Computer Engineering
Secondary Field in Data Science
Honors & Awards
2nd Ranked Student in Faculty of Engineering
GBYF Second Place Prize in Defense, Cyber Security, Technology and Industry Category
High Honour Student
Academic Service
Languages
Let's work together
Have a project in mind or want to get in touch?
t.atincuzun@hotmail.com