Sergii K.

I am a Top-Rated Data Scientist and Researcher with a PhD in Remote Sensing and over 15 years of experience delivering high-performance R&D solutions for industrial, academic, and enterprise sectors. I specialize in bridging the gap between raw, noisy data and actionable business objectives, transforming complex signals into deployable machine learning pipelines. Whether it's developing novel diagnostic algorithms, predicting physical parameters from multi-channel data, or building advanced event-detection models, I design end-to-end architectures that solve complex, non-standard problems. My Recent R&D Successes Include: - Time-Series & High-Frequency Data: Engineered robust detection models for electric and water appliances using high-frequency data, providing highly accurate recognition pipelines. - Computer Vision & Remote Sensing: Developed predictive models for physical and nutritional parameters using hyperspectral imaging. - SOTA AI Implementation: Investigated and deployed ready-to-production State-of-the-Art (SOTA) AI/ML solutions based on advanced Kaggle competition methodologies. - Biomedical Data: Deep sleep data visualization and advanced processing for physiological monitoring. How I Help Businesses: - End-to-End Problem Solving: I handle the entire pipeline—from raw data evaluation, advanced feature engineering (using communication theory), to hyperparameter optimization and rigorous out-of-fold validation. - Advanced Digital Signal Processing (DSP): Extracting critical insights from 1D/2D signals, including noise assessment, filtering, and compression. - Deployable ML Architectures: Building predictive models with PyTorch, XGBoost, and OpenCV, optimized for real-world integration. Recognized Expertise: - Upwork Skill Certified in Data Science & Data Analytics - AWS Certified Machine Learning & Cloud Foundations - Author of 100+ Scopus-indexed publications (h-index: 14) - Tech Stack: Python (PyTorch, SciPy, Scikit-Learn, OpenCV), MATLAB, Signal Filtering, Multivariate Statistics, SQL, Cloud Computing (AWS).