Data Analysis and Engineering Tools

Overview

This section covers my work in time-series analysis, signal detection, and batch-processing tools for research and development. The focus is on turning algorithms, data workflows, and user interfaces into configurable and verifiable engineering tools.

Time-Series Analysis Workbench

The workbench provides a complete workflow for time-series data, from import, preview, and field mapping to analysis configuration, task execution, and result review. It supports continuous and binary variables as well as relationships between data series.

My main responsibilities included:

• Designing data import and column-mapping workflows for different time formats, sampling methods, and series types.
• Organizing analysis capabilities for data quality, descriptive statistics, trends, change points, state transitions, and anomalous events.
• Supporting single-series checks and pairwise relationship analysis, with explicit results for insufficient data or inapplicable configurations.
• Building asynchronous analysis tasks and result views that present summaries, checks, events, and charts consistently.

Low-Frequency Oscillation Detection

This tool targets low-frequency oscillations in power and process signals. It turns frequency-domain analysis into a repeatable detection workflow with offline data replay and result validation.

My main responsibilities included:

• Implementing signal preprocessing, windowed analysis, target-band detection, and alert decisions.
• Handling sampling information, data continuity, input validity, and insufficient-data conditions consistently.
• Building offline data replay, result export, and visualization workflows for parameter adjustment and algorithm validation.

Modular Batch-Processing Tool

This desktop tool brings recurring data and file-processing tasks into a unified workflow for task selection, parameter configuration, batch execution, and runtime feedback.

My main responsibilities included:

• Designing an extensible task registration and configuration mechanism that keeps tasks independent while sharing a consistent interface.
• Supporting workspace selection, batch execution, persistent settings, and runtime logs.
• Turning scripts for medical data, signals, images, and media processing into reusable desktop tools.

Project Scope

These tools support data inspection, analysis, and research workflows. They do not modify source data automatically or replace professional judgment. Because algorithm results depend on data quality, sampling conditions, and parameter settings, the design emphasizes input validation, explicit status reporting, and repeatable verification.