Scholar
In Kee Kim
Google Scholar ID: O0-eXcoAAAAJ
The University of Georgia
Citations & Impact
Citations
546
H-index
12
i10-index
17
Publications
20
Co-authors
21
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers, including:
- - 'Convergo: Multi-SLO-Aware Scheduling for Heterogeneous AI Accelerators on Edge Devices', IEEE International Conference on Edge Computing and Communications (EDGE), 2025
- - 'Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing', IEEE Access, 2025
- - 'Characterizing Deep Learning Model Compression with Post-Training Quantization on Accelerated Edge Devices', IEEE International Conference on Edge Computing and Communications (EDGE), 2024, Best Paper Award
- - 'Using a Random Forest to Predict Quantized Reuse Distance in an SSD Write Buffer', Springer Computing, 2024
- - 'Near-Edge Computing Aware Object Detection: A Review', IEEE Access, 2024
- - 'CNT: Semi-Automatic Translation from CWL to Nextflow for Genomic Workflows', IEEE International Conference on Bioinformatics and Bioengineering (BIBE), 2023
- - 'DynaES: Dynamic Energy Scheduling for Energy Harvesting Environmental Sensors', IEEE International Performance, Computing, and Communications Conference (IPCCC), 2023
- - 'Toward Low-Cost and Sustainable IoT Systems for Soil Monitoring in Coastal Wetlands', IEEE International Conference on Collaboration and Internet Computing (CIC), 2023
- - 'A Study of Java Microbenchmark Tail Latencies', ACM/SPEC International Conference on Performance Engineering (ICPE), Data Challenge Track, 2023
- - 'Reaching for the Sky: Maximizing Deep Learning Inference Throughput on Edge Devices with AI Multi-Tenancy', ACM Transactions on Internet Technology, 2023
Research Experience
- Associate Professor in the School of Computing at the University of Georgia. Involved in multiple research projects in areas such as edge computing, high-performance computing, and IoT.
Education
- Ph.D. in Computer Science from the University of Virginia in 2018.
Background
- Research interests: Addressing performance and resource management problems in various computing systems (e.g., cloud, HPC, edge, and IoT). Specific areas include Edge AI, Serverless Workflow Management, and Reproducible Benchmarking and Measurement.
Miscellany
- Teaching: CSCI 4730/6730: Operating Systems
