Engineer with a bias to ship: indoor autonomy, explainable ML, and polished tools.
B.Eng. (IoT) student at Savonia UAS. Delivered a UWB-guided navigator, a SHAP-backed churn model, and a local AI recipe app.
Core strengths
Technical Skills
Programming
Python, C, JavaScript, SQL (MySQL)
Frameworks & Libraries
ROS, Flask, Flet, scikit-learn, XGBoost, SHAP, pandas, NumPy, Matplotlib
Tools & Tech
Power BI, Excel, Azure Cloud, Raspberry Pi, Arduino, UWB (Iiwari), Nokia 5G, REST APIs, TCP/Socket, Git, Docker, Linux, HTML5/Canvas
Experience
Project Worker, IoT & Robotics — DigiCenter North Savo (Savonia UAS)
May – Sep 2025 • Kuopio, FI- LiDAR-free indoor navigation using dual UWB tags (10 Hz) + odometry yaw; custom A* → spline → Pure-Pursuit pipeline.
- Integrated Iiwari Cloud API and aligned Y-down map to ROS yaw frames.
- Real-time Flask + Canvas visualizer (pose, path, goals, telemetry).
- Supervisory pause/resume via TCP; pre-built AI obstacle detection over Nokia 5G integrated for reliability.
- Collected and processed telemetry logs (UWB + odometry + IMU) for post-analysis and model training.
- Contributed to dataset preparation and AI experiments for navigation behavior analytics.
- Result: reliable goal convergence with practical indoor precision across the Savonia campus.
Selected Projects
ProcureFlow – Sievo-style Procurement Analytics
Python • SQL • Power BI • Data Modeling
Python/SQL/Power BI pipeline for procurement analytics, budget variance & spend trends.
UWB Indoor Autonomous Navigation
Python • ROS • Flask • UWB API
Floorplan A* + Pure-Pursuit with live web monitoring.
Predicting Telecom Customer Churn (XAI)
Python • scikit-learn • XGBoost • SHAP
Explainable churn model (AUC ≈ 0.93) + ROI simulation.
Let’s talk
Hiring for IoT, robotics, or ML roles? I’m available for internships and junior positions.