Ömer Köse

I obtained my B.S. in Computer Engineering from METU. In October 2023, I will begin my M.S. program in Informatics at TUM.

I am a Research Fellow at TUBITAK. I also work as a researcher in iVizLab at Simon Fraser University.

My research interests span computer graphics, geometry processing, and deep learning.

Outside of research, I also have experience working on both software and hardware for computer graphics. I love working on complex graphics software such as game engines, and I am a Graphics Engineer at Esri, where I work on developing and improving ArcGIS Pro's graphics engine.

I am strongly interested in bridging the gap between research and engineering by utilizing research findings to solve real-world problems.

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• Currently, I am working as a Researcher at iVizLab (Simon Fraser University), collaborating with Meehae Song and Nouf Abukhodair on the classification of artworks with neural networks.

• Currently, I am working as a Part-Time Core Graphics Engineer on ArcGIS Pro Software.

• Currently, I am working as a Research Assistant at TUBITAK, collaborating with Güneş Sucu under the supervision of Professor Sinan Kalkan and Yusuf Sahillioğlu on shape matching with neural networks.

• Research on mesh flattening under high number of constraints
• Developed a framework in MATLAB which provides a user interface and flattens the mesh
• Developed a visualizer in C++ with OpenGL to visualize textures on the meshes using the UV coordinates obtained in MATLAB

• Worked on mesh morphing. Explored the effect of different bases on mesh morphing problem. Different linear interpolation techniques like linear, bilinear and trilinear interpolation are used to obtain the morph based on the reduced basis projected vertices of the original two shapes
• Developed a framework in C++ to get the morphed mesh. Geometry Central and Eigen libraries are used to obtain needed data structures, operators, and solvers. Visualizing is done using the Polyscope library

• Worked on geodesics on triangle meshes. Focused on improving graph-based approach towards approximating geodesics. Constructed different graphs to straighten the geodesics locally on each triangle face. Worked on a post-processing step to straighten the geodesics
• Developed a framework in C++ to get the geodesics. Geometry Central library is used to obtain needed data structures and operators. Visualizing is done using the Polyscope library

• Implemented a renderer that uses Ray Marching with Signed Distance Functions with my teammate.
• Implementation is done in C++ with OpenGL.

• Implemented an Eulerian Fluid Simulation where grid is represented by a staggered MAC Grid
• Implementation is done in Python using Taichi

• Implemented SMG: A Shuffling Gradient-Based Method with Momentum paper published at ICML 2021 conference with my teammate
• Implemented the paper in Python using PyTorch. The networks were trained on Google Colab

• Implemented The Heat Method for Distance Computation published at ACM Transactions on Graphics 2013 for triangle meshes
• Implemented the paper in C++ using Geometry Central and Eigen libraries for their data structures, operators, and solvers, Polyscope for Visualization

• Currently developing a procedural terrain generation engine in C++ with OpenGL
• The engine procedurally generates a terrain of different biomes depending on different heights

• Developed a Ray Tracer in C++ following Peter Shirley's Ray Tracing in One Weekend series

• Developed a Software Rasterizer in C++ following Dimitry Sokolov's Tiny Renderer wiki.