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Maksim Kukushkin
Research Assistant Dept. Neuromorphic information processing, Leipzig University

About Me

Salut! I'm Maksim Kukushkin, a graduated from Leipzig University. I am delighted to be working as a Research Assistant in the Machine Learning Group at the Neuromorphic Information Processing Department of Leipzig University. Currently, I am working on analysing hyperspectral data and developing algorithms for classification of various seed species. Here you can find my CV.

Research Interests

My research focuses on computer vision with a specialization in hyperspectral imaging. Specifically, I am interested in various aspects of classification, anomaly detection, and morphological networks for hyperspectral and multispectral imaging.

Education

Ph. D. Student in Computer Science
Leipzig University · Leipzig, Germany
08/2022 - present
M. Sc. Computer Science (Semester Abroad)
09/2021 - 03/2022
M. Sc. Business Information Systems
Leipzig University · Leipzig, Germany
10/2018 - 10/2021
B. Sc. Business Information Systems
Leipzig University · Leipzig, Germany
10/2014 - 09/2018

Work Experience

Research Assistant
Leipzig University · Leipzig, Germany
08/2021 - Present
  • Practicing CV & DL on hyperspectral images. Link to the project.
Working Student Data Science / Backend Developer
CHECK24 Reise GmbH · Leipzig, Germany
04/2017 - 10/2020

  • Hotel Matching System

    • Automatic hotel matching based on the descriptions of various hotel providers

  • Automatic hotel image classification system

    • Integration of external providers via provided API into the existing IT architecture

  • Integration & maintenance of new APIs

    • Classification of hotel images into different categories using transfer learning
Internship Web-Developer
Posterlounge GmbH · Leipzig, Germany
09/2017 - 03/2018
  • Portal for customer returns
    • Design and development of a customer returns portal where customers initiate and process their returns
Skills
  • Programming Languages
    • Python, PHP, R, SQL, HTML, CSS, Bash.
  • Frameworks & Libraries
    • TensorFlow, Keras, PyTorch, scikit-learn, pandas, numpy, matplotlib, seaborn, spectral, OpenCV, CatBoost, Flask, Zend Framework, Laminas, jQuery, Smarty
  • Tools & Platforms
    • Docker, Git, Jira, Confluence, Linux, Windows, macOS, Apache Web Server, mySQL, AWS.
Publications
  • Kukushkin, M. & Stavros, N. 2021. Automatic acoustic classification of feline sex. In Proceedings of the 16th International Audio Mostly Conference (AM '21). Association for Computing Machinery, New York, NY, USA, 156–160. https://doi.org/10.1145/3478384.3478385
  • Kukushkin, M., Enders, M., Kaschuba, R., Bogdan, M., & Schmid, T. (2023). Canola seed or not? Autoencoder-based Anomaly Detection in Agricultural Seed Production. INFORMATIK 2023 - Designing Futures: Zukünfte gestalten. Gesellschaft für Informatik e.V., Bonn, Germany, 1645-1652. https://doi.org/10.18420/inf2023_169.
  • Kukushkin, M., Enders, M., Kaschuba, R., Bogdan, M., & Schmid, T. (2023). On Optimization of Morphological Network for Hyperspectral Image Classification. In 16th International Conference on Machine Vision (ICMV 2023). SPIE.
  • Erichsmeier, F., Kukushkin M., Fiedler. J., Enders, M., Goertz S., Bogdan, M., Schmid T., & Kaschuba, R. (2024). Automating the purity analysis of oilseed rape through usage of hyperspectral imaging. SPIE Photonics West 2024 . SPIE, Bellingham, WA, USA. (Accepted)
  • Kukushkin, M., Bogdan, M., & Schmid, T. BiCAE – A Bimodal Convolutional Autoencoder for Seed Purity Testing (2024). 3st Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE). 2024. (Accepted)