You can find a list of my latest publications below!
Ufuk Çakır
Ufuk Çakır
Hey! I am Ufuk, a Physics Masters student at Heidelberg University, specializing in Computational Physics and Machine Learning. You will find my latest projects, research interests, and notes on this website.
During my studies in Heidelberg I participated in a variety of engaging projects, including Science Communication and Research.
I collaborated with international students from Sorbonne University in Paris, University in Milan, and Heidelberg University to produce an animated video on Quantum Simulation for Science Communication. I was responsible for coordinating, animating, and editing the video in Adobe After Effects and Premiere Pro.
I developed Python animations for public outreach during my undergraduate at the Quantum Dynamics Lab, visualizing research results on relaxation dynamics in disordered quantum spin systems.
I helped organizing the CZS Summer School For Scientific Machine Learning at IWR in Heidelberg, build the associated website and was the Local Organizing Comitee at the Summer School in Heidelberg.
Developed a project in collaboration with international scientists from the Lindau Alumni Network that combines molecular simulations and machine learning to improve the efficiency of plastic-degrading enzymes. I animated and edited the video in Adobe After Effects. This project was selected as one of the finalists and presented at the Lindau Nobel Laureate Meeting 2024.
I was selected as a Young Scientist to participate at the 73rd Lindau Nobel Laureate Meeting in 2024, where I had the opportunity to engage with Nobel Laureates and other Young Scientists from around the world.
I love to create animations to visualize science concepts! The following are some examples I created using Adobe After Effects:
During my academic journey my main focus has been on exploring how machine learning can be used for astrophysical purposes, specifically with data drawn from cosmological simulations.
Investigate the use of machine learning to create galaxy morphology models and encode the information contained in modern state-of-the-art galaxy simulations. Simulation data from the IllustrisTNG project is used to calculate the Eigengalaxies as the basis vectors of the transformed image space using Principal Component Analysis.
The GAMMA dataset is a comprehensive collection of galaxy data tailored for Machine Learning applications. This dataset offers detailed 2D maps and 3D cubes of 11 727 galaxies, capturing essential attributes: stellar age, metallicity, and mass. I created an interactive online dashboard to visualize the lower dimensional image space. This work was accepted at the Machine Learning and the Physical Sciences Workshop at NeurIPS 2023.
Together with the Machine Learning For Ecology Group at the African Institute for Mathematical Sciences (AIMS), I implemented a fully tested and well-documented Genetic Algorithm for optimizing bioacoustic data spectrograms. This work aims to enable real-time wildlife monitoring of critically endangered species, and will soon be published and available open source! This project was funded by the competitive Baden-Württemberg-Stipendium, that enabled a two-month visiting research stay in Cape Town, South Africa. Accepted as a Poster at the 2nd ML4RS Workshop, ICLR in Vienna 2024.
For my Master thesis in Heidelberg, starting in November 2023, I aim to develop a powerful, well-documented and modular tool for the science community that will enable the creation of galaxy images from a set of physical input parameters in a differentiable manner, specifically implementing astrophysical processes in JAX and leveraging automatic differentiation to incorporate the pipeline inside a bigger Machine Learning Framework. Since I am committed to open science, this project will be open source to enable wide-range use in the astrophysics community.
You can find a list of my latest publications below!
During my teaching lessons I created Notes for my students on various topics to support them in their physics and math studies. I have collected the notes covering different topics, together with some of my own research notes, and notes on lectures.