Bio Summary

I am a proactive Computer Vision/Machine Learning Engineer driven by a deep passion for leveraging innovative ideas to positively impact society. My expertise lies in the dynamic intersection of Computer Vision and Machine Learning, particularly in the realm of 3D reconstruction and visual pose estimation algorithms from images and videos. My hands-on experience includes successfully implementing and refining these algorithms for tasks such as reconstructing digital entities and estimating poses of articulated and rigid objects.

Throughout my career, I have had the privilege of taking on leadership roles, guiding MSc./PhD students, and spearheading collaborative projects with industry partners. This experience has not only strengthened my technical skills but also honed my ability to translate cutting-edge research into practical solutions. I am excited about the prospect of bringing my skills in machine learning, problem-solving, and collaborative leadership to contribute to impactful projects in a dynamic engineering role. 

I previously worked as a research associate at Huawei Noah's Ark Lab. I finished my post-doctoral studies at Imperial Computer Vision & Learning Lab, Imperial College London under the supervision of Prof. Tae-Kyun Kim. I obtained a PhD degree in Sep, 2018 from the Institute for Computer Graphics and Vision, TU Graz under the supervision of Prof. Vincent Lepetit. My research interests are Computer Vision and Machine Learning algorithms, more specifically 3D hand pose estimation and camera localization for urban environments. I received my M.Sc. and B.Sc. Degrees in 2014 and 2012 respectively, at Dep. of Computer Engineering, Bilkent University. During my M.Sc. I worked on Multimedia Event Detection in videos under supervision of Prof. Pinar Duygulu.  

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