Architecture-aware automatic computation offload for native applications. - Gwangmu Lee; Hyunjoon Park; Seonyeong Heo; Kyung-Ah Chang; Hyogun Lee; Hanjun Kim 001 (MICRO, 2015)

Heterogeneous Distributed Shared Memory for Lightweight Internet of Things Devices. - Bongjun Kim; Seonyeong Heo; Gyeongmin Lee; Soyeon Park; Hanjun Kim 001; Jong Kim 001 (IEEE Micro, 2016)

Integrated IoT programming with selective abstraction. - Gyeongmin Lee; Seonyeong Heo; Bongjun Kim; Jong Kim 001; Hanjun Kim 001 (LCTES, 2017)

Rapid prototyping of IoT applications with Esperanto compiler. - Gyeongmin Lee; Seonyeong Heo; Bongjun Kim; Jong Kim 001; Hanjun Kim 001 (RSP, 2017)

RT-IFTTT: Real-Time IoT Framework with Trigger Condition-Aware Flexible Polling Intervals. - Seonyeong Heo; Seungbin Song; Jong Kim 001; Hanjun Kim 001 (RTSS, 2017)

Spinal code: automatic code extraction for near-user computation in fogs. - Bongjun Kim; Seonyeong Heo; Gyeongmin Lee; Seungbin Song; Jong Kim 001; Hanjun Kim 001 (CC, 2019)

Real-Time Object Detection System with Multi-Path Neural Networks. - Seonyeong Heo; Sungjun Cho; Youngsok Kim; Hanjun Kim 001 (RTAS, 2020)

Sharing-aware Data Acquisition Scheduling for Multiple Rules in the IoT. - Seonyeong Heo; Seungbin Song; Bongjun Kim; Hanjun Kim 001 (RTAS, 2020)

Compiler-Assisted Semantic-Aware Encryption for Efficient and Secure Serverless Computing. - Bongjun Kim; Seonyeong Heo; Jaeho Lee 005; Shinnung Jeong; Yongwoo Lee 001; Hanjun Kim 001 (IEEE Internet Things J., 2021)

ComFlex: Composable and Flexible Resource Management for the IoT. - Gyeongmin Lee; Bongjun Kim; Seungbin Song; Seonyeong Heo; Hanjun Kim 001 (IEEE Internet Things J., 2021)

HECATE: Performance-Aware Scale Optimization for Homomorphic Encryption Compiler. - Yongwoo Lee 001; Seonyeong Heo; Seonyoung Cheon; Shinnung Jeong; Changsu Kim 004; Eunkyung Kim 002; Dongyoon Lee; Hanjun Kim 001 (CGO, 2022)

RTScale: Sensitivity-Aware Adaptive Image Scaling for Real-Time Object Detection. - Seonyeong Heo; Shinnung Jeong; Hanjun Kim 001 (ECRTS, 2022)

Predictive Energy-Aware Adaptive Sampling with Deep Reinforcement Learning. - Seonyeong Heo; Philipp Mayer; Michele Magno (ICECS 2022, 2022)

Low-cost Smart Raven Deterrent System with Tiny Machine Learning for Smart Agriculture. - Seonyeong Heo; Nicolas Baumann; Carla Margelisch; Marco Giordano; Michele Magno (I2MTC, 2023)

Enhancing Lightweight Neural Networks for Small Object Detection in IoT Applications. - Liam Boyle; Nicolas Baumann; Seonyeong Heo; Michele Magno (SENSORS, 2023)

CR2: Community-aware Compressed Regular Representation for Graph Processing on a GPU. - Shinnung Jeong; Sungjun Cho; Yongwoo Lee 001; Hyunjun Park; Seonyeong Heo; Gwangsun Kim; Youngsok Kim; Hanjun Kim 001 (ICPP, 2024)

TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems. - Byungchul Chae; Jiae Kim; Seonyeong Heo (LCTES, 2024)

One-Shot Sparse Neural Architecture Search for Resource-Constrained Devices. - Shenghui Song 003; Jan-Nico Zaech; Seonyeong Heo (RTCSA, 2024)

DSORT-MCU: Detecting Small Objects in Real-Time on Microcontroller Units. - Liam Boyle; Julian Moosmann; Nicolas Baumann; Seonyeong Heo; Michele Magno (CoRR, 2024)

TinyMo: Graph-Level Memory Optimizer for Tiny Machine Learning. - Byungchul Chae; Seonyeong Heo (IEEE Embed. Syst. Lett., 2025)