Andriy Fedorenko

• Building AI sensing systems that integrate hardware, edge processing, and machine learning for real-time detection, tracking, and classification across ocean and aerial environments. • Deploying vessel-based sensor systems to accumulate large-scale datasets across maritime environments, using distributed architecture across coordinated vessel networks. • Extending multi-sensor systems from aerial to ocean-based platforms, tested in Antarctica and the Baltic Sea, capturing marine, surface, and airborne objects.

• The Galileo Project is a Harvard-led initiative advancing instrumented, data-driven observation of aerial phenomena through multi-sensor systems for UAP research. • Multi-modal, multi-spectral observatory integrating infrared and complementary sensing modalities for continuous detection, tracking and classification of objects in environments lacking calibrated, reproducible data. • Combines YOLO, transformer-based models, and SORT trained on visual and synthetic trajectory datasets. Calibration methods for long-wave infrared arrays using ADS-B data. • Event-driven architecture with edge-based processing for real-time detection, tracking, and multi-sensor data fusion. • 500K reconstructed trajectories across field conditions formed a structured dataset for statistical analysis and anomaly detection. • Peer-reviewed publications on multi-sensor observatories, infrared calibration, and aerial object detection (Sensors; arXiv).

• SaaS platform for real estate workflow, translation fragmented user behavior into structured product systems. • End-to-end product architecture from initial concept through deployment, including iterative user-driven design and data-informed refinement of registration and retention dynamics.

• Energy Optimization systems for distributed electric vehicle charging, modeling load behavior across aggregated assets under dynamic pricing and marginal CO₂ signals. • Forecasting and control models (ARIMA, LSTM, state-space) for load prediction and grid interaction. Linear programming for real-time scheduling and energy market participation • Integration with OEM platforms (Honda, BMW, Renault) and development of APIs for distributed energy systems and data exchange.

• Accomplished a set of projects on data analysis, data engineering and modeling (R, SQL, Alteryx, Python). • Making variables and model for a demand prediction based on the historical data (machine learning algorithms). • Predicting customer behavior based on the accounts profile for one of a web services.

• Developed a software for data analysis (Excel, Visual Basic). • Discovered a new mechanism of thermogenesis and metabolic efficiency (Two "Cell" papers published). • Acquired a broad experience across a number of biological sciences and medicine.

Research project: Redox modulation of ligand-gated channels in neurons of PNS

• Teamwork on designing protocols to study memory mechanisms • Managed graduate students to program imaging system and design (Visual Basic, Delphi)

• Developed software for external devices used for temperature control in manufacturing processes.