In Kee Kim

Associate Professor of Computer Science
School of Computing, University of Georgia
Email: inkee.kim@uga.edu
Office: Boyd Graduate Studies Research Center, Room 802

About

I am an Associate Professor in the School of Computing at the University of Georgiaa. I completed my Ph.D. in Computer Science in 2018 at the University of Virginia.
My research interests lie in addressing performance and resource management problems in various computing systems (e.g., cloud, HPC, edge, and IoT). My research is supported by various funding agencies (e.g., NSF, DoD, Army Research Labs, NIFA/USDA).

Research Interests

Edge AI: System-level optimization for boosting inference, training, and compression workloads at the edge.
Serverless Workflow Management: Cost-performance optimization in collaborative edge and cloud environments.
Reproducible Benchmarking and Measurement: Characterizing various workloads, focusing on performance, reliability, energy consumption, and environmental impact across cloud, HPC, edge, and IoT.

Teaching

Current (Fall 2025)

CSCI 4730/6730: Operating Systems
Course Website Syllabus

Publications

(Name: a student author under my supervision)

2025

Convergo: Multi-SLO-Aware Scheduling for Heterogeneous AI Accelerators on Edge Devices
Ting Jiang, Jianwei Hao, Sushruth Harsha, Rakandhiya D. Rachmanto, Arief Setyanto, Lakshmish Ramaswamy, In Kee Kim
IEEE International Conference on Edge Computing and Communications (EDGE), 2025
Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing
Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya D. Rachmanto, Affan Ardana, In Kee Kim
IEEE Access, 2025

2024

An Empirical Evaluation of the Impact of Solar Correction in NeRFs for Satellite Imagery
Devjyoti Chakraborty, Kriti Ghosh, Zaki Sukma, In Kee Kim, Lakshmish Ramaswamy, Suchendra Bhandarkar, Deepak Mishra
27th International Conference on Pattern Recognition (ICPR), 2024
Characterizing Deep Learning Model Compression with Post-Training Quantization on Accelerated Edge Devices
Rakandhiya D. Rachmanto, Zaki Sukma, Ahmad N. L. Nabhaan, Arief Setyanto, Ting Jiang, In Kee Kim
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
Hyejin Cha, In Kee Kim, Taeseok Kim
Springer Computing, 2024
Near-Edge Computing Aware Object Detection: A Review
Arief Setyanto, Theo Sasongko, Muhammad Ainul Fikri, In Kee Kim
IEEE Access, 2025

2023

CNT: Semi-Automatic Translation from CWL to Nextflow for Genomic Workflows
Martin L. Putra, In Kee Kim, Haryadi S. Gunawi, Robert L. Grossman
IEEE International Conference on Bioinformatics and Bioengineering (BIBE), 2023
DynaES: Dynamic Energy Scheduling for Energy Harvesting Environmental Sensors
Jianwei Hao, Emmanuel Oni, In Kee Kim, Lakshmish Ramaswamy
IEEE International Performance, Computing, and Communications Conference (IPCCC), 2023
Toward Low-Cost and Sustainable IoT Systems for Soil Monitoring in Coastal Wetlands
Jianwei Hao, Rajneesh Sharma, Mary B. Fleming, In Kee Kim, Deepak R. Mishra, et al.
IEEE International Conference on Collaboration and Internet Computing (CIC), 2023
A Study of Java Microbenchmark Tail Latencies
Sen He, In Kee Kim, Wei Wang
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
Jianwei Hao, Piyush Subedi, Lakshmish Ramaswamy, In Kee Kim
ACM Transactions on Internet Technology, 2023

2022

CloudBruno: A Low-Overhead Online Workload Prediction Framework for Cloud Computing
Vinodh K. Jayakumar, Shivani Arbat, In Kee Kim, Wei Wang
IEEE International Conference on Cloud Engineering (IC2E), 2022
Privacy invasion via smart-home hub in personal area networks
Omid Setayeshfar, Karthika Subramani, Xingzi Yuan, Raunak Dey, Dezhi Hong, In Kee Kim, Kyu Hyung Lee
Pervasive and Mobile Computing, 2022
EdgeFaaSBench: Benchmarking Edge Devices Using Serverless Computing
Kaustubh R. Rajput, Chinmay D. Kulkarni, Byungjin Cho, Wei Wang, In Kee Kim
IEEE International Conference on Edge Computing and Communications (EDGE), 2022
Wasserstein Adversarial Transformer for Cloud Workload Prediction
Shivani Arbat, Vinodh K. Jayakumar, Jaewoo Lee, Wei Wang, In Kee Kim
The 34th Annual Conference on Innovative Applications of Artificial Intelligence (AAAI/IAAI), 2022

2021

AI Multi-Tenancy on Edge: Concurrent Deep Learning Model Executions and Dynamic Model Placements on Edge Devices
Piyush Subedi, Jianwei Hao, In Kee Kim, Lakshmish Ramaswamy
IEEE International Conference on Cloud Computing (CLOUD), 2021
An Empirical Analysis of VM Startup Times in Public IaaS Clouds
Jianwei Hao, Ting Jiang, Wei Wang, In Kee Kim
IEEE International Conference on Cloud Computing (CLOUD), 2021
An Empirical Analysis of VM Startup Times in Public IaaS Clouds: Extended Report
Jianwei Hao, Ting Jiang, Wei Wang, In Kee Kim
arXiv, 2021
Performance Testing for Cloud Computing with Dependent Data Bootstrapping
Sen He, Tianyi Liu, Palden Lama, Jaewoo Lee, In Kee Kim, Wei Wang
IEEE/ACM International Conference on Automated Software Engineering (ASE), 2021
ChatterHub: Privacy Invasion via Smart Home Hub
Omid Setayeshfar, Karthika Subramani, Xingzi Yuan, Raunak Dey, Dezhi Hong, Kyu Hyung Lee, In Kee Kim
IEEE International Conference on Smart Computing (SMARTCOMP), 2021
Characterizing Resource Heterogeneity in Edge Devices for Deep Learning Inferences
Jianwei Hao, Piyush Subedi, In Kee Kim, Lakshmish Ramaswamy
ACM International Workshop on System and Network Telemetry and Analytics (ACM SNTA@HPDC), 2021

2020 or before

A Self-Optimized Generic Workload Prediction Framework for Cloud Computing
Vinodh K. Jayakumar, Jaewoo Lee, In Kee Kim, Wei Wang
IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020
Forecasting Cloud Application Workloads With CloudInsight for Predictive Resource Management
In Kee Kim, Wei Wang, Yanjun Qi, Marty Humphrey
IEEE Transactions on Cloud Computing, 2020
Guaranteeing Performance SLAs of Cloud Applications Under Resource Storms
In Kee Kim, Jinho Hwang, Wei Wang, Marty Humphrey
IEEE Transactions on Cloud Computing, 2019
CloudInsight: Utilizing a Council of Experts to Predict Future Cloud Application Workloads
In Kee Kim, Wei Wang, Yanjun Qi, Marty Humphrey
IEEE International Conference on Cloud Computing (CLOUD), 2018
Orchestra: Guaranteeing Performance SLAs for Cloud Applications by Avoiding Resource Storms
In Kee Kim, Jinho Hwang, Wei Wang, Marty Humphrey
IEEE International Symposium on Parallel and Distributed Computing (ISPDC), 2018
iCSI: A Cloud Garbage VM Collector for Addressing Inactive VMs with Machine Learning
In Kee Kim, Sai Zeng, Christopher Young, Jinho Hwang, Marty Humphrey
IEEE International Conference on Cloud Engineering (IC2E), 2017
A Supervised Learning Model for Identifying Inactive VMs in Private Cloud Data Centers
In Kee Kim, Sai Zeng, Christopher Young, Jinho Hwang, Marty Humphrey
ACM/IFIP/USENIX International Middleware Conference (Middleware), 2016
Empirical Evaluation of Workload Forecasting Techniques for Predictive Cloud Resource Scaling
In Kee Kim, Wei Wang, Yanjun Qi, Marty Humphrey
IEEE International Conference on Cloud Computing (CLOUD), 2016
WDCloud: An End to End System for Large-Scale Watershed Delineation on Cloud
In Kee Kim, Jacob Steele, Anthony M Castronova, Jonathan Goodall, Marty Humphrey
IEEE International Conference on Big Data (IEEE BigData), 2015
PICS: A Public IaaS Cloud Simulator
In Kee Kim, Wei Wang, Marty Humphrey
IEEE International Conference on Cloud Computing (CLOUD), 2015
Comprehensive Elastic Resource Management to Ensure Predictable Performance for Scientific Applications on Public IaaS Clouds
In Kee Kim, Jacob Steele, Yanjun Qi, Marty Humphrey
IEEE/ACM International Conference on Utility and Cloud Computing, (UCC), 2014
Adaptive and Mobility-predictive Quantization-based Communication Data Management for High Performance Distributed Computing
In Kee Kim, Sung Ho Jang and Jong Sik Lee,
SIMULATION: Transactions of The Society for Modeling and Simulation International, 2007

© 2025 In Kee Kim. Last updated: July 2025.