Hello! I’m Suleyman Serhan Narli, a dedicated computer scientist currently pursuing my doctoral studies in Machine Learning at Charité – Universitätsmedizin Berlin. With a rich background in engineering and a deep passion for data science and artificial intelligence, I am committed to leveraging technology to solve complex problems and drive innovation.

Professional Background

My journey in the field of computer science began with a Bachelor’s degree from İskenderun Technical University, where I worked on real-time emotion detection analysis using the Neurosky device. This project, supported by the Scientific and Technical Research Council of Turkey (TUBITAK), laid the foundation for my expertise in signal processing and machine learning.

I furthered my education with a Master’s degree in Computer Science, focusing on Medical Image Processing. My thesis, „COVID-19 Detection using Deep Learning on Chest X-rays Enhanced by Adaptive Methods,“ involved extensive research in deep learning and image processing, utilizing tools such as Python, Keras, and transfer learning models.

Professional Experience

  • AI/ML Engineer at MCG Motion Capture GmbH, Heidelberg, Germany (February 2022 – Present)
    • Developed and implemented machine learning algorithms for biomechanics analysis, focusing on kinematics of humans and animals.
    • Collaborated with cross-functional teams to integrate AI solutions into research projects and commercial products.
    • Utilized Python and TensorFlow to develop predictive models and automate data processing tasks.
  • Signal Processing Engineer Intern at StepUp Air Solutions, Copenhagen, Denmark (September 2020 – April 2021)
    • Solved design problems and developed products for medical hardware and software.
    • Researched and recorded biomedical and environmental data, and filtered and classified ECG signals using Python.
  • Signal Processing Engineer Intern at Wroclaw Technical University, Poland (January 2020 – March 2020)
    • Collected and processed participant data, applied noise removal to brain signals, and used Matlab and Weka for signal processing and classification.

Skills and Expertise

  • Programming Languages: Python, R, MATLAB, C
  • Machine Learning Frameworks: TensorFlow, Keras, Scikit-learn
  • Tools and Libraries: Pandas, Numpy, Scipy, OpenCV, Google Colab
  • Specializations: Deep Learning, Image Processing, EEG Signal Processing, Computer Vision, Biomechanics Analysis

Publications and Conferences

  • Publication: „Impact of Local Histogram Equalization on Deep Learning Architectures for Diagnosis of COVID-19 on Chest X-rays“ (2021)
  • Conferences:
    • International Congress on Engineering and Life Science (2018) – „The Effect of the Features of Time, Frequency and Time-Frequency Domain on the Performance of Classification.“
    • International Conference on Artificial Intelligence towards Industry 4.0 (ICAII4.0) (2018) – „The Effect of Different Stimulations on Emotion Estimation with Deep Learning.“
    • International Conference on Artificial Intelligence towards Industry 4.0 (ICAII4.0) (2019) – „Denoising Medical X-ray Images using Blockmatching and 3D filtering.“

Languages

  • English: Proficient (C1)
  • German: Independent (B1)
  • Turkish: Native

Contact Information

  • Email: serhan.narli@gmail.com
  • Phone: (+49) 15257848836
  • Address: Am Sportplatz 2, Hoppegarten, 15366 Brandenburg, Germany

Feel free to explore my website to learn more about my projects and research. If you share my interests or have any questions, don’t hesitate to reach out!