Крістіна

KRISTINA PANCHENKO
Hauts-de-Seine, France • [open contact info](look above in the "contact info" section) • [open contact info](look above in the "contact info" section)
[open contact info](look above in the "contact info" section)

SUMMARY
Software Engineer with experience in developing and evaluating ML systems for IoT and
cybersecurity applications. Skilled in Python, Linux, Docker, Git, data preprocessing, model training,
and performance optimization. Experienced in distributed ML architectures, network traffic
analysis, and deploying research prototypes in distributed environments. Interested in ML
engineering, MLOps, and reliable production-oriented machine learning systems.
WORK EXPERIENCE
Research Intern, Conservatoire National des Arts et Métiers (Paris) Jun 2025 – Sep 2025
Conducted research on network anomaly detection for IoT using split learning architectures.
Performed traffic analysis, data preprocessing, model training, and performance evaluation.
Developed and evaluated machine learning pipelines on the base of federated learning
cybersecurity application with achieved scalability up to 16 end clients.
Assistant System Administrator, Linaset (Czech Republic) Mar 2022 – Aug 2022
Supported administration and troubleshooting of industrial digital infrastructure in a
manufacturing environment.
Diagnosed and resolved issues related to production systems, machine monitoring, alarm
systems, surveillance cameras, and employee tracking platforms.
PROJECTS
Split Learning Model with Activation Compression in IoT Systems:
Implemented a distributed Split Learning architecture for resource-constrained IoT devices.
Reduced communication overhead through activation compression techniques.
Developed ML training pipelines with client-side and server-side distributed model components
using Python and PyTorch in Linux and Docker environments.
Technologies: Python, Docker, Linux, Apache Kafka, Git.
Malware Detection Using Supervised Machine Learning:
Developed a ML pipeline for malware traffic detection using the CTU-13 network traffic dataset.
Preprocessed network traffic data and transformed extracted traffic characteristics into
numerical feature vectors for ML models.
Applied feature engineering and model evaluation using Scikit-learn and Keras.
Trained and compared multiple classification models using accuracy and performance metrics.

EDUCATION
Master of Science in Computer Networks & IoT Systems Sep 2023 – Oct 2025
Conservatoire National des Arts et Métiers (CNAM)
Bachelor of Science in Software Technologies of the Internet of Things Sep 2019 – Jul 2023
Taras Shevchenko National University of Kyiv

ADDITIONAL INFORMATION
Machine Learning & MLOps: Python, PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, Pandas,
Flower framework, Model evaluation, Distributed ML, Performance optimization, ML pipelines.
Systems & DevOps: Linux, Bash, Git, Docker, Apache Kafka, Microsoft Azure.
Networking & Cybersecurity: TCP/IP, Network Traffic Analysis, Wireshark, Cisco IOS.
Programming: C, C++, Java, SQL, SQLite, R, Django, HTML, CSS.
Technical Skills: IoT Architectures, Arduino, Embedded Systems, Web/loT Testing.
Languages: Ukrainian - Native, English - B2, French - B1, Russian - C2.
Certifications: Cisco CCNA Certification, Oracle Certified Professional (OCP).
Activities: The hackathon organization team’s member of Global Game Jam in Kyiv, Feb 2020.