Jeongkyu Lee
(he/him/his)
Teaching Professor
Research interests
- Big data
- Machine learning
- Robotics
- Computer vision
- Database systems
- Data visualization
- Deep learning
Education
- PhD in Computer Science and Engineering, University of Texas at Arlington
- MS in Computer Science, Sogang University
- BS in Mathematics, Sungkyunkwan University
Biography
Jeongkyu Lee is a teaching professor at the Khoury College of Computer Sciences at Northeastern University’s Silicon Valley campus. He earned his bachelor’s in mathematics from Sungkyunkwan University, master’s in computer science from Sogang University, and PhD in computer science and engineering from the University of Texas at Arlington. His areas of teaching include big data, NoSQL database, Python, and statistics.
Prior to joining Northeastern, Lee worked as a database administrator with companies including Hana Bank and IBM. His research has been published in journals such as IEEE, ACM and MDPI.
Outside of work, he enjoys traveling via train.
Projects
Recent publications
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SQLearn: Automated SQL Statement Assessment using Structure-based Analysis
Citation: Sumukhi Ganesan, Tianchou Gong, Jeongkyu Lee. (2024). SQLearn: Automated SQL Statement Assessment using Structure-based Analysis SIGCSE (2), 1644-1645. https://doi.org/10.1145/3626253.3635607 -
MRI Segmentation of Musculoskeletal Components Using U-Net: Preliminary Results
Citation: Divit Vasu, Seungmoon Song, Hans Kainz, Jeongkyu Lee. (2024). MRI Segmentation of Musculoskeletal Components Using U-Net: Preliminary Results ICBBB, 30-35. https://doi.org/10.1145/3640900.3640902 -
Detection of Northern Corn Leaf Blight Disease in Real Environment Using Optimized YOLOv3
Citation: Brian Song, Jeongkyu Lee. (2022). Detection of Northern Corn Leaf Blight Disease in Real Environment Using Optimized YOLOv3 CCWC, 475-480. https://doi.org/10.1109/CCWC54503.2022.9720782 -
An Event Detection Platform to Detect Gender Using Deep Learning
Citation: Abdulrahman Aldhaheri, Khaled Almgren and Jeongkyu Lee, “An Event Detection Platform to Detect Gender Using Deep Learning,” Proc. of the 11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON), pp. 360-364, October 28–31, 2020 -
Topological Data Analysis for Classification of Heart Disease Data
Citation: Fatima Ali Aljanobi, and Jeongkyu Lee, “Topological Data Analysis for Classification of Heart Disease Data,” Proc. of 2021 IEEE International Conference on Big Data and Smart Computing (BigComp 2021), January 17–20, 2021. -
Miniature Humanoid Upgrade for Material Handling Tasks in Humanoid Challenge
Citation: Kiwon Sohn, Jeongkyu Lee, and Kevin Huang. “Miniature Humanoid Upgrade for Material Handling Tasks in Humanoid Challenge,” Proceedings of the ASME 2019 International Mechanical Engineering Congress and Exposition. Volume 4: Dynamics, Vibration, and Control. Salt Lake City, Utah, USA. November 11–14, 2019 -
Mapping Areas using Computer Vision Algorithms and Drones
Citation: Bashar Alhafni, Saulo Fernando Guedes, Lays Cavalcante Ribeiro, Juhyun Park, Jeongkyu Lee. (2019). Mapping Areas using Computer Vision Algorithms and Drones CoRR, abs/1901.00211. http://arxiv.org/abs/1901.00211 -
AD or Non-AD: A Deep Learning Approach to Detect Advertisements from Magazines
Citation: Almgren, K., Krishna, M., Aljanobi, F., and Jeongkyu Lee, “AD or Non-AD: A Deep Learning Approach to Detect Advertisements from Magazines,” Entropy, 20(12), 982, 2019. -
H2Hadoop: Improving Hadoop Performance Using the Metadata of Related Jobs
Citation: Hamoud Alshammari, Jeongkyu Lee, and Hassan Bajwa, “H2Hadoop: Improving Hadoop Performance Using the Metadata of Related Jobs,” IEEE Trans. Cloud Computing 6(4): 1031-1040, 2018.