Resume

📜 PDF


Computer science professional holding a B.Sc. and a M.Sc. degree and currently pursuing a Ph.D. degree, with an expected graduation date of April 2023. Active researcher in the ATHENA project, focusing on deep learning, computer vision, and video encoding. Strong problem-solving, collaboration and fast learning skills, able to lead innovative research projects and work with cross-disciplinary teams.


🎓 Education

Ph.D. in Computer Science

Universität Klagenfurt - Klagenfurt, Austria (2019 - Present)
Dissertation: Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning
Advisor: Christian Timmerer

M.Sc. in Computer Science

Ozyegin University - Istanbul, Türkiye (2018 - 2019)
GPA: 3.92 / 4.00
Thesis: Image Denoising Using Deep Convolutional Autoencoders [PDF]

B.Sc. in Computer Science

Ozyegin University - Istanbul, Türkiye (2013 - 2018)
GPA: 3.28 / 4.00


📌 Experience

Ph.D. Researcher (2019 - Present)
ATHENA Christian Doppler Laboratory - 📍 Klagenfurt, Austria

  • Proposed and developed innovative solutions for enhancing video coding in HTTP adaptive streaming using machine learning techniques, resulting in 4 patent filings and 15 scientific publications in prestigious conferences and journals.
  • Possess extensive knowledge and expertise in various machine learning models (e.g. CNN, LSTM, 3D-CNN, Vision Transformer) and frameworks (e.g. PyTorch, Tensorflow) to achieve project objectives.
  • Demonstrated strong leadership abilities through effective project management and collaboration with colleagues from diverse backgrounds and nationalities.
  • Selected to serve as an academic reviewer and proceeding chair for conferences, demonstrating recognition of expertise within the field.

Teaching Assistant (2018 - 2019)
Ozyegin University -📍 Istanbul, Türkiye —

🎒 Related Skills

Fundamental

Programming Languages

Tools

Extra


🏆 Awards

Best New Streaming Innovation Award @ The 2021 Streaming Media Readers’ Choice Awards (Nov 2021)
For the paper: Fast Multi-Resolution and Multi-Rate Encoding for HTTP Adaptive Streaming Using Machine Learning

Best Doctoral Symposium Paper Award @ ACM MMSys 2021 (Oct 2021)
For the paper: Machine Learning Based Video Coding Enhancements for HTTP Adaptive Streaming


📠 Patents

Fast Multi-Rate Encoding for Adaptive HTTP Streaming - 2021
Fast Multi-Rate Encoding for Adaptive Streaming Using Machine Learning - 2022


💬 Languages

🇹🇷 Turkish: Native
🇺🇸 English: C2
🇩🇪 German: B1
🇸🇦 Arabic: A2


📜 Selected Publications

Image Denoising Using Deep Convolutional Autoencoder with Feature Pyramids
Turkish Journal of Electrical Engineering & Computer Sciences - 2020

Synthesised noisy images in Blender
Designed an image denoising autoencoder with feature pyramids

Fast Multi-Resolution and Multi-Rate Encoding for HTTP Adaptive Streaming Using Machine Learning
IEEE Open Journal of Signal Processing - 2021

Constructed dataset from encoded videos in PyTorch
Predicted encoding decisions for videos using a custom CNN

ECAS-ML: Edge Computing Assisted Adaptation Scheme with Machine Learning for HTTP Adaptive Streaming
International Conference on Multimedia Modeling - 2022

Constructed training dataset from 4G radio traces in PyTorch
Categorised radio traces using LSTM

Super-Resolution Based Bitrate Adaptation for HTTP Adaptive Streaming for Mobile Devices
ACM Mile-High Video Conference - 2022

Constructed training dataset from encoded videos in Tensorflow
Designed an image super-resolution model for mobile devices

LiDeR: Lightweight Dense Residual Network for Video Super-Resolution on Mobile Devices
IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop - 2022

Designed a video super-resolution model for mobile devices
Implemented in Android using Tensorflow Lite

MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural Networks
International Conference on Multimedia Modeling - 2022

Designed an Android application to evaluate deep learning models on mobile
Used TensorflowLite as framework