Software & Datasets

We have made the following software and datasets generated from our group's research publicly available. You are welcome to use them freely in your work. 

Note that (unless separated noted) all software and datasets are protected under the GPLv3 licence and we ask you to cite the proper publications when using them.

You can find most of our open source code through our github repository at

JaeYeon Park, Kichang Lee, Sungmin Lee, Mi Zhang, JeongGil Ko. "AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing", ACM UbiComp 2023

Swift-based motion logger software

Jungmo Ahn, Youngki Lee, Jeongseob Ahn, JeongGil Ko. "Server Load and Network-aware Adaptive Deep Learning Inference Offloading for Edge Platforms", Internet of Things, 2022.

Jaewon Choi, Seungchan Jeong, JeongGil Ko. "Emulating Your eXtended World: An Emulation Environment for XR App Development", IEEE MASS 2022

Hyunjun Kim, JeongGil Ko. "Memory-efficient DNN Training on Mobile Devices", ACM MobiSys 2022

Hyunjun Kim, JeongGil Ko. "Fast Monte-Carlo Approximation of the Attention Mechanism", AAAI 2022

Sinh Huynh, Rajesh Balan, JeongGil Ko. "iMon: Appearance-based Gaze Tracking System on Mobile Devices", ACM UbiComp 2022

Hyeonjung Park, Youngki Lee, JeongGil Ko. "Enabling Real-time Sign Language Translation on Mobile Platforms with On-board Depth Cameras", ACM UbiComp 2021

Huynh Nguyen Phan Sinh, Rajesh K. Balan, JeongGil Ko, Youngki Lee. "VitaMon: Measuring Heart Rate Variability Using the Smartphone Front Camera'', ACM SenSys 2019 

Eunseong Boo, Shahid Raza, Joel Höglund, JeongGil Ko. "FDTLS: Supporting DTLS-based Combined Storage and Communication Security for IoT Devices", IEEE MASS 2019