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2022
PhD SWE Internship / Student Researcher
Google - CA, US
- Research on improving self-supervised dense contrastive learning using different dense comparison methods and reconstruction decoders. Work accepted to NeurIPS 2022 Self-Supervised Learning - Theory & Practice Workshop.
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2021
PhD SWE (Machine Learning) Internship
Google - CA, US
- Implemented & compared various visual-semantic image embedding techniques, deployed a novel Supervised Contrastive Learning based method to replace an attribute-based embedding one to assist graph-hierarchical clustering.
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2020
Research Internship
Michigan State University (MSU) – MI, US
- Advisor: Prof. Saiprasad Ravishankar
- Worked on dynamic estimation methods and developing block-matching algorithms with learned transforms.
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2019
Graduate Research Internship
Los Alamos National Laboratory (LANL) – NM, US
- Worked on Machine/Deep Learning based tomographic reconstruction methods for ill-posed single view reconstruction.
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2017
Internship
ASELSAN Advanced Sensing Research Program Department – Ankara, Turkey
- Performed time and frequency domain passive acoustic mapping, sparsity-based microbubble detection using constrained optimization methods for ultrasound imaging.
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2016
Internship
KAREL Electronics Research & Development Center – Ankara, Turkey
- Performed image processing tasks for vehicles on ARM based NXP iMX6 board by cross compilation of OpenCV libraries.