Umuralp Kaytaz

R&D Engineer and Researcher at DAI-Labor der TU Berlin
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Contact Information
us****@****om
(386) 825-5501
Location
Berlin, Berlin, Germany, DE
Languages
  • Turkish Native or bilingual proficiency
  • English Full professional proficiency
  • German Limited working proficiency
Skills

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Bio

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Credentials

  • CKA Certification Course - Certified Kubernetes Administrator
    KodeKloud
    Oct, 2023
    - Nov, 2024
  • Certified Kubernetes Application Developer (CKAD)
    KodeKloud
    Oct, 2023
    - Nov, 2024
  • Docker Training Course for the Absolute Beginner
    KodeKloud
    Sep, 2023
    - Nov, 2024
  • Kubernetes for the Absolute Beginners - Hands-on Tutorial
    KodeKloud
    Sep, 2023
    - Nov, 2024
  • Security of Emerging Satellite Mega-Constellations
    IEEE Communications Society
    Jun, 2023
    - Nov, 2024
  • OTFS and Delay Doppler Communications
    IEEE Communications Society
    Nov, 2022
    - Nov, 2024
  • O-RAN: Disrupting the Radio Access Network through Openness and Innovation
    IEEE Communications Society
    Oct, 2022
    - Nov, 2024
  • Cloud - Native 5G: Architecture, Enablers and Roadmap
    IEEE Communications Society
    Sep, 2022
    - Nov, 2024
  • Introduction to MIMO
    IEEE Communications Society
    Sep, 2022
    - Nov, 2024
  • Machine Type Communications in LTE and 5G/NR
    IEEE Communications Society
    Aug, 2022
    - Nov, 2024
  • Natural Language Processing with Classification and Vector Spaces
    DeepLearning.AI
    Nov, 2021
    - Nov, 2024
  • Introduction to Machine Learning in Production
    DeepLearning.AI
    Jun, 2021
    - Nov, 2024
  • Scalable Machine Learning on Big Data using Apache Spark
    Coursera
    Mar, 2020
    - Nov, 2024
  • AI For Everyone
    Coursera
    Mar, 2019
    - Nov, 2024
  • Convolutional Neural Networks
    Coursera
    Mar, 2019
    - Nov, 2024
  • Deep Learning Specialization
    Coursera
    Mar, 2019
    - Nov, 2024
  • How Google does Machine Learning
    Coursera
    Mar, 2019
    - Nov, 2024
  • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
    Coursera
    Mar, 2019
    - Nov, 2024
  • Launching into Machine Learning
    Coursera
    Mar, 2019
    - Nov, 2024
  • Sequence Models
    Coursera
    Mar, 2019
    - Nov, 2024
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
    Coursera
    Feb, 2019
    - Nov, 2024
  • Neural Networks and Deep Learning
    Coursera
    Feb, 2019
    - Nov, 2024
  • Structuring Machine Learning Projects
    Coursera
    Feb, 2019
    - Nov, 2024

Experience

  • DAI-Labor der TU Berlin
    • Germany
    • Research Services
    • 1 - 100 Employee
    • R&D Engineer and Researcher
      • Jan 2021 - Present

      Research associate at GT-ARC gGmbH, an affiliated research institute of DAI-Labor, TU Berlin. R&D for reliable end-to-end 5G networking using containerized Open RAN in the Cobra5G project sponsored by the German Federal Ministry of Transport and Digital Infrastructure. Intelligent Transportation System (ITS) (e.g. infrastructure optimization, HD maps, V2X communications, data reliability) development for autonomous driving application in BeIntelli project sponsored by the German Federal Ministry of Transport and Digital Infrastructure. Work package (WP3: Development, Integration & Roll-Out) coordinator and deliverable editor in Horizon 2020 project 5G MOBIX funded by the European Commission. Revised and updated modules for Raspberry Pi based IoT education in CC + IoT project co-funded by the Erasmus+ programme of the European Union. Supervised B.Sc. theses and seminar research topics on cutting-edge ITS and AI applications. Project coordinator and teaching assistant for the Smart Communication Systems (SCS) course at TU Berlin. Research on data-driven wireless communication systems and ITS optimization. Publications: “Online Monte Carlo Planning with QoS Subgoals for Data Caching in ITS MEC Networks”, IEEE Conference on Omni-layer Intelligent Systems (COINS), 2023. (Best Paper Award) - “Graph Neural Network for Digital Twin-enabled Intelligent Transportation System Reliability”, IEEE Conference on Omni-layer Intelligent Systems (COINS), 2023. “Competitive Learning for Unsupervised Anomaly Detection in Intelligent Transportation Systems”, IEEE International Conference on Communications (ICC), 2022. “Hierarchical Deep Reinforcement Learning based Dynamic RAN Slicing for 5G V2X”, IEEE Global Communications Conference (Globecom), 2021. Show less

  • Huawei
    • China
    • Telecommunications
    • 700 & Above Employee
    • 5G Machine Learning Engineer
      • Jun 2020 - Sep 2020

      Research and development work on face detection, object detection, head pose estimation, gaze detection, hand gesture recognition, Voice Activity Detection (VAD) and speech frequency clustering for AI-assisted online exam proctoring. Implementations were completed in python using deep/machine learning models with scikit-learn, OpenCV, ffmpeg, dlib and python_speech_features libraries. Research and development work on face detection, object detection, head pose estimation, gaze detection, hand gesture recognition, Voice Activity Detection (VAD) and speech frequency clustering for AI-assisted online exam proctoring. Implementations were completed in python using deep/machine learning models with scikit-learn, OpenCV, ffmpeg, dlib and python_speech_features libraries.

  • Koç University
    • Türkiye
    • Higher Education
    • 700 & Above Employee
    • Research Assistant
      • Feb 2017 - Jan 2020

      For my MSc thesis I have conducted research on the reliability and performance of spectrum decisions in wireless networks. I have proposed a distributed Deep Reinforcement Leaning (DRL) based Dynamic Spectrum Access (DSA) scheme for Cognitive Radio (CR) networks. I have modeled dynamic multi-channel access problem in Wi-Fi networks as a Restless Multi-Armed Bandit (RMAB) Process and proposed a novel Whittle index based MAC scheme, namely Index Based Channel Hopping (IBCH). I have also worked on synthetic data generation using Generative Adversarial Networks (GANs) for vehicular Visible Light Communications (VLC) channel modeling. Show less

    • Teaching Assistant
      • Feb 2017 - Jan 2019

      -Entrepreneurship and Innovation (ENGR 401/ MGMT 412)-Embedded Systems (ELEC 317)-Probability and Random Variables for Engineers (ENGR 200)-Introduction to Programming (Java) (COMP 130)

Education

  • Koç Üniversitesi
    Master of Science - MS, Electrical and Electronics Engineering
    2017 - 2020
  • University of Warwick
    Master of Science - MS, Computer Science
    2015 - 2016
  • Koç Üniversitesi
    BSc, Electrical and Electronics Engineering
    2011 - 2015
  • St. George's Austrian High School
    2006 - 2011

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