
Kihun Jung developed data analytics and research tooling across the Hyubbbb/Daily_SQL and team-epoch/EPOCH_4th_TASK repositories, focusing on SQL-driven data extraction, reporting, and time series forecasting. He built reusable SQL scripts for domains such as sales analytics, animal shelter operations, and anomaly detection, enabling maintainable business intelligence workflows. In Python, he implemented an LSTM-based forecasting pipeline using TensorFlow and Pandas, supporting both univariate and multivariate time series analysis. Kihun also standardized research documentation and onboarding templates, improving reproducibility and team efficiency. His work demonstrated depth in SQL, Python, and technical writing, with clean, well-documented, and production-ready deliverables.

September 2025 monthly performance summary for team-epoch/EPOCH_4th_TASK. Focused on delivering two major features that enhance task management, research documentation, and data science capabilities, with an emphasis on business value, maintainability, and deployable artifacts.
September 2025 monthly performance summary for team-epoch/EPOCH_4th_TASK. Focused on delivering two major features that enhance task management, research documentation, and data science capabilities, with an emphasis on business value, maintainability, and deployable artifacts.
August 2025 performance: Delivered consolidated Research Team Task Documentation and Templates for EPOCH_4th_TASK, standardizing onboarding and task execution. Key contributions include creating and refining README guidelines for weeks 1–2, defining deadlines and penalties, updating citation style, adding reading/task templates, and including resource PDFs. All changes were tracked via a set of commits to team-epoch/EPOCH_4th_TASK, improving documentation quality, consistency, and reproducibility.
August 2025 performance: Delivered consolidated Research Team Task Documentation and Templates for EPOCH_4th_TASK, standardizing onboarding and task execution. Key contributions include creating and refining README guidelines for weeks 1–2, defining deadlines and penalties, updating citation style, adding reading/task templates, and including resource PDFs. All changes were tracked via a set of commits to team-epoch/EPOCH_4th_TASK, improving documentation quality, consistency, and reproducibility.
May 2025 monthly summary for Hyubbbb/Daily_SQL: Delivered analytics enhancements by adding two SQL scripts to enable targeted data retrieval and anomaly detection. The updates include a script to retrieve fish information by maximum length per fish type and a script to calculate colony size deviation from the yearly maximum in the E. coli dataset. These changes enhance data-driven decision making, enable researchers to quickly identify outliers, and lay groundwork for downstream dashboards.
May 2025 monthly summary for Hyubbbb/Daily_SQL: Delivered analytics enhancements by adding two SQL scripts to enable targeted data retrieval and anomaly detection. The updates include a script to retrieve fish information by maximum length per fish type and a script to calculate colony size deviation from the yearly maximum in the E. coli dataset. These changes enhance data-driven decision making, enable researchers to quickly identify outliers, and lay groundwork for downstream dashboards.
Month: 2025-04 — Delivered the Data Insights SQL Scripts Suite within Hyubbbb/Daily_SQL to enable cross-domain data extraction and reporting. Key domains include book catalog, animal shelter operations, sales analytics, product popularity, and developer information, forming a foundation for BI dashboards and ad-hoc queries. No major bugs reported this period. Overall impact shows accelerated data-driven decision making by providing ready-to-run SQL scripts and a unified data view. Skills demonstrated include SQL scripting, data extraction, cross-domain data modeling, and repository collaboration for scalable analytics.
Month: 2025-04 — Delivered the Data Insights SQL Scripts Suite within Hyubbbb/Daily_SQL to enable cross-domain data extraction and reporting. Key domains include book catalog, animal shelter operations, sales analytics, product popularity, and developer information, forming a foundation for BI dashboards and ad-hoc queries. No major bugs reported this period. Overall impact shows accelerated data-driven decision making by providing ready-to-run SQL scripts and a unified data view. Skills demonstrated include SQL scripting, data extraction, cross-domain data modeling, and repository collaboration for scalable analytics.
March 2025 monthly summary: Delivered foundational data retrieval and reporting capabilities in Hyubbbb/Daily_SQL, enabling actionable analytics across member profiles, doctor information, and practice data. Expanded coverage with car seat-based queries and monthly sales by book category, supporting data-informed decision making. Completed SQL challenge solutions repository with artifacts for flavor selection, Seoul-rated restaurants, max-priced product, and animal registry count. No major defects reported; changes are clean, well-documented, and ready for production data workflows. Overall impact demonstrates increased data accessibility, maintainability, and cross-repo SQL proficiency.
March 2025 monthly summary: Delivered foundational data retrieval and reporting capabilities in Hyubbbb/Daily_SQL, enabling actionable analytics across member profiles, doctor information, and practice data. Expanded coverage with car seat-based queries and monthly sales by book category, supporting data-informed decision making. Completed SQL challenge solutions repository with artifacts for flavor selection, Seoul-rated restaurants, max-priced product, and animal registry count. No major defects reported; changes are clean, well-documented, and ready for production data workflows. Overall impact demonstrates increased data accessibility, maintainability, and cross-repo SQL proficiency.
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