Seokki Lee, Assistant Professor (PI)
My research area focuses on database systems, specifically data provenance over big data. I have two main research pillars: (i) Efficient provenance management for providing concise and meaningful explanations for complex queries and workflows over large amounts of data; (ii) Developing provenance models to enhance explainability across diverse domains, with a particular focus on applications in machine learning (ML), privacy-enhancing technologies (PETs), and data visualization.
Short Bio
I received my Ph.D. in Computer Science at Illinois Institute of Technology under supervision of Dr. Glavic and Master’s degree in Computer Science and Engineering at Hanyang University.
Contact Information
- Office: Rhodes 885
- Email: seokki.lee@uc.edu
- Phone: 513-556-5795
- UC Homepage
Members
Current Ph.D. Students
- N. Akwari (CSE) Explainable Machine Learning using Provenance 2022–present
- S. Rawat (CSE) Exploring Provenance for Explainable Information Gain 2021–present
Current Master Student Theses
- A. Margi (MSCS) Efficiently Measuring Information Gain using Provenance 2023–present
- S. Chouhan (MSCS) Efficiently Sampling Big Provenance 2023–present
Current Undergraduate Student Projects
Supervised Master Theses
- S. Moshtaghi Largani (CSE) Provenance Summaries for Big Data 2021–2023
- B. Su (CMPE) Hybrid Explanations 2021–2022
Supervised Student Projects
- J. Turnau (CS) Explainable Machine Learning using Provenance 2022–2024
- B. Ju (CS) Hybrid Explanations and Repairs 2023
- B. Tyagi (MEng) Efficiently Measuring Information Gain using Provenance 2023
- P. Amezcua (MEng/CCHMC) Effect of Hemostatic Proteins on Eczematic Microbiota in Mice 2021–2022
- C. Lu (EE) Provenance Support for Aggregation 2021–2022
- D. Ma (EE) Provenance Support for Aggregation 2021–2022
- A. Liu (EE) Provenance Support for Aggregation 2021–2022
- B. He (EE) Provenance Support for Aggregation 2021–2022
- R. Strohm (CS) Developing A Simplified ERP System using Postgres 2021–2022
- D. Hosford (CS) Developing A Simplified ERP System using Postgres 2021–2022
- D. Rajput (BANA) Efficient Evaluation of Machine Learning Model using Provenance 2021
- N. Quynh (BS.Chem.Eng) Data Analysis using big data systems 2021
- S. Jayaraj (MEng) Integration and Analysis of User’s interests 2021
- P. Kathan Hitesh (MEng) Analysis of Data for User trend 2021