Distributed data Intensive Systems Lab
I am a fourth-year Ph.D. student in the School of Computer Science at Georgia Institute of Technology, under Prof. Ling Liu‘s supervision at the Distributed Data Intensive Systems Lab (DiSL). Before joining Georgia Tech, I obtained my Bachelor’s degree in Computer Engineering at the HanYang University and I worked as a Senior Software Engineer at LG Electronics.
Research Interest
- Systems for ML and AI
- ML Algorithms for Performance Optimization of Cloud and Cluster Computing Systems
- ML and Data Analytics Algorithms for Big Data Applications and Services
Publications [Google Scholar]
Juhyun Bae, Ling Liu, Ka Ho Chow, Yanzhao Wu, Gong Su, Arun Iyengar, “Transparent Network Memory Storage for Efficient Container Execution in Big Data Clouds”, IEEE BigData, 2021
Juhyun Bae, Ling Liu, Yanzhao Wu, Gong Su, Arun Iyengar, “RDMAbox : Optimizing RDMA for Memory Intensive Workload”, IEEE CIC, 2021 [Won the Best Paper Award]
Ling Liu, Juhyun Bae, Wenqi Cao, Semih Sahin, Yanzhao Wu, Qi Zhang, “Huge Data Analytics with Transparent In-Network Memory Computing (White Paper)”, NSF Large Scale Networking (LSN) workshop on Huge Data, 2020 [PDF]
Yanzhao Wu, Juhyun Bae, Ka Ho Chow, Wenqi Wei, Ling Liu, “Promoting high diversity ensemble learning with ensemblebench”, IEEE CogMI, 2020.
Ka-Ho Chow, Ling Liu, Margaret Loper, Juhyun Bae, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu, “Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems”, IEEE TPS, 2020.
Semih Sahin, Ling Liu, Wenqi Cao, Yanzhao Wu, Juhyun Bae, “Memory Abstraction and Optimization for Distributed Executors”, IEEE CIC 2020.
Vikram Krishnamurthy, Kusha Nezafati, Juhyun Bae, Emre Gursoy, Mian Zhong, Vikrant Singh, “Classification of Driving Behavior Events Utilizing Kinematic Classification and Machine Learning for Down Sampled Time Series Data”, IEEE International Conference on Big Data (Big Data), 2019 [PDF]
Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu, Qi Zhang, “Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks” IEEE International Conference on Big Data (Big Data), 2019 [PDF]
Ling Liu, Wenqi Cao, Semih Sahin, Qi Zhang, Juhyun Bae, Yanzhao Wu, “Memory Disaggregation: Research Problems and Opportunities”, IEEE 39th International Conference on Distributed Computing Systems (ICDCS), 2019 [PDF]
Research and Industry Experience
- Georgia Institute of Technology, Georgia, USA
- Graduate Research Assistant (Aug 2018 – Present)
- Distributed data Intensive Systems Lab
- Graduate Teaching Assistant (Sep 2019 – Present)
- CS6675 : Advanced Internet Computing Systems and Application Development (Spring 2020)
- CS 6220: Big Data Systems and Analytics (Fall 2019)
- CS6365 : Introduction to Enterprise Computing (Spring 2019)
- Graduate Research Assistant (Aug 2018 – Present)
- IBM Thomas J. Watson Research, New York, USA
- Research Intern (Summer 2019, Summer 2020, Summer 2021)
- Supervisor : Donna N Dillenberger
- Nissan Research Center–Silicon Valley, California, USA
- Research Intern (Summer 2018)
- Supervisor : Dr. Vikram Krishnamurthy
- Georgia Institute of Technology Atlanta, USA
- MS in Computer Science (Changed to Ph.D program in 2018) 2017- 2018
- LG ELECTRONICS, Seoul, South Korea
- Senior Software Engineer (2010 – 2017)
- BSP Department, TE Group, Mobile Communications Company
Awards
- Early Identified Pool (EIP), LG Electronics (2013, 2014, 2015)
- Cum Laude, Hanyang University, (2010)
- Honor Scholarship for Excellent Academic records, Hanyang University (2006, 2007, 2008)
Reviewer
- UCC 2018, “Machine Learning Approach for Live Migration Cost Prediction in VMware Environments”