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In Kee Kim

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Assistant Professor, School of Computing

I am an Assistant Professor in the Computer Science at The University of Georgia. I have completed my Ph.D. in Computer Science in 2018 from the University of Virginia under the supervision of Prof. Marty Humphrey.


PhD, Computer Science, University of Virginia, 2018

Research Interests:

Current research interests are Cloud ComputingLarge-Scale Distributed Systems, and Edge/IoT. More specifically;

  • Systems research for cloud-scale machine learning/data science applications
  • Deep learning at the Edge
  • Edge computing for real-world IoT applications (e.g., Smart Home, Environmental Sensing, Transportation)
  • Cloud function and serverless computing
Selected Publications:

Shivani Arbats, Vinod K. Jayakumar, Jaewoo Lee, Wei Wang, In Kee KimWasserstein Adversarial Transformer for Cloud Workload PredictionIAAI-22 (Oral Presentation), Accepted, 2022

Sen He, Tianyi Liu, Palden Lama, Jaewoo Lee, In Kee Kim, Wei Wang, A Performance Testing for Cloud Computing with Dependent Data BootstrappingIEEE/ACM ASE (Accepted), 2021

Piyush Subedis, Jianwei HaosIn Kee Kim, Lakshmish Ramaswamy, AI Multi-Tenancy on Edge: Concurrent Deep Learning Model Executions and Dynamic Model Placements on Edge DevicesIEEE CLOUD , 2021

Jianwei Hao*s, Ting Jiang*s, Wei Wang, In Kee KimAn Empirical Analysis of VM Startup Times in Public IaaS CloudsIEEE CLOUD, 2021, [Full Version]

Omid Setayeshfar*, Karthika Subramani*, Xingzi Yuan, Raunak Dey, Dezhi Hong, Kyu Hyung Lee, In Kee KimChatterHub: Privacy Invasion via Smart Home HubIEEE SMARTCOMP, 2021

Jianwei Haos, Piyush SubedisIn Kee Kim, Lakshmish Ramaswamy, Characterizing Resource Heterogeneity in Edge Devices for Deep Learning InferencesACM SNTA@HPDC, 2021

Vinodh K. Jayakumar, Jaewoo Lee, In Kee Kim, Wei Wang, A Self-Optimized Generic Workload Prediction Framework for Cloud ComputingIEEE IPDPS, 2020

In Kee Kim, Wei Wang, Yanjun Qi, Marty Humphrey, Forecasting Cloud Application Workloads with CloudInsight for Predictive Resource ManagementIEEE Trans. on Cloud Computing (TCC), 2020

In Kee Kim, Jinho Hwang, Wei Wang, Marty Humphrey, Guaranteeing Performance SLAs of Cloud Applications under Resource StormsIEEE Trans. on Cloud Computing (TCC), 2020

Lei Xians, Samuel Dakota Vickerss, Amanda L. Giordano, Jaewoo Lee, In Kee Kim, Lakshmish Ramaswamy, #selfharm on Instagram: Quantitative Analysis and Classification of Non-Suicidal Self-InjuryIEEE CogMI, 2019

In Kee Kim, Dongmei Yan, Brian Park, Jianhua Guo, Traffic Flow Insight: A Novel Online Ensemble Model for Short-Term Traffic Volume Prediction, TRB, 2019

Of note:

I am always looking for motivated grad and undergrad students with a strong background/interest in cloud computing, computer and distributed systems, and IoT. If you are interested in working with me, please email me with your interest or stop by my office. We should talk!

Personal Website:

More of My Students

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