Can Koz
I am a MSc in Advanced Computer Science student at University of Oxford. I am currently being mentored by Dr. Tomas Jakab and Luke Melas-Kyriazi at Visual Geometry Group. My thesis focuses on developing animatable and deformable 3D objects using generative modeling techniques.
Previously I worked as a Large Language Model Engineer, where I worked on projects at the intersection of machine learning, air charter services. I have also worked as a Computer Vision Engineer focusing on event-based vision.
I was an undergraduate researcher at Visual Design and Engineering Lab (VDEL) in the Mechanical Engineering Department at CMU for three years. I was advised by Prof. Levent Burak Kara, Wentai Zhang and Kevin Ferguson. As an undergraduate research assistant, I solved problems in mechanical engineering using deep learning / computer vision such as flaw detection in metal additive manufacturing and generating / understanding engineering design. During my studies in the US, I worked with undergraduate CS students from UC Berkeley, Stanford and MIT on projects at the intersection of machine learning, healthcare, and finance. Click here to see my projects!
Over the past couple of years, I have also taken non-degree machine learning courses on Coursera. I have completed Deep Learning Specialization, AI for Medicine Specialization and Self-Driving Cars Specialization. I am currently learning financial machine learning and building high frequency trading bots, with a particular interest in applying reinforcement learning techniques to optimize trading strategies. When I’m not in front of a screen, I enjoy rowing, playing drums, and reading science fiction novels.
I am a proud mentor at AI for Medicine Specialization , Deep Learning Specialization and a member of the Learning on Graphs and Geometry Reading Group (LoGG).
news
Oct 30, 2023 | Our paper “Multi-task Learning for Optical Coherence Tomography Angiography (OCTA) Vessel Segmentation” was accepted to Medical Imaging Meets NeurIPS 2023 |
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Oct 15, 2023 | I was a reviewer at the Temporal Graph Learning Workshop at NeurIPS 2023 |
Oct 1, 2023 | Excited to start my MSc in Advanced Computer Science at University of Oxford. |
Aug 1, 2022 | Our paper “Data Augmentation of Engineering Drawings For Data-Driven Component Segmentation” was accepted to IDETC-CIE 2022. |
Jul 1, 2022 | Graduated from Koc University, Computer Engineering Department with Deans Student Award |
selected research (more)
I am interested in 3D generative models, self-supervised learning, score-based models, graph neural networks, multi-task learning, and leveraging sparse priors for 3D reconstruction. I draw inspiration from intelligence in humans and nature while I attempt to solve multidisciplinary problems using machine learning. My goal is to develop advanced design tools, allowing intelligent agents to understand and improve existing 2D and 3D designs made by humans.
publications
- Data Augmentation of Engineering Drawings for Data-Driven Component SegmentationIDETC-CIE, 2022
- Flaw Detection in Metal Additive Manufacturing Using Deep Learned Acoustic FeaturesML4Eng @ NeurIPS, 2020