Sejin Kim

30 papers B 1C 3Journal 19Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
An efficient multiscale coupling method for simulations of reactor-scale chemical vapor deposition with microstructural features.
Adv. Eng. Softw.
Taegeun Kim, Hyoungsoo Ko, Jaewon Jang, Sejin Kim, SunYoung Park, Jae Myung Choe, Young-Gu Kim, Dae Sin Kim, Sangseung Lee, Donghyun You
2025 J jnl
Deep reinforcement learning-based control algorithm for flight kinematics of insect-scale flyers.
Adv. Eng. Softw.
Seungpyo Hong, Sejin Kim, Innyoung Kim, Donghyun You
2025 J jnl
Learning the Inverse Ryu-Takayanagi Formula with Transformers.
CoRR
Sejin Kim
2025 — conf
Phoneme Classification in Imagined Speech Using Explainable Machine Learning.
BCI
Sejin Kim, Hyunwook Kang, Ji-Hoon Jeong, Minji Lee
2025 J jnl
Solution Augmentation for ARC Problems Using GFlowNet: A Probabilistic Exploration Approach.
Trans. Mach. Learn. Res.
Sanha Hwang, Seungpil Lee, Sejin Kim, Sundong Kim
2024 — conf
A Fast and Simple Method for Sleep Breathing Cycle Segmentation in Time Domain.
IMCOM
Rayoung Park, Heonzoo Lee, Tan Loc Nguyen, Sejin Kim, Yonggwan Won
2024 J jnl
Data-driven development of cycle prediction models for lithium metal batteries using multi modal mining.
CoRR
Jaewoong Lee, Junhee Woo, Sejin Kim, Cinthya Paulina, Hyunmin Park, Hee-Tak Kim, Steve Park, Jihan Kim
2024 J jnl
Non-iterative generation of an optimal mesh for a blade passage using deep reinforcement learning.
Comput. Phys. Commun.
Innyoung Kim, Sejin Kim, Donghyun You
2024 J jnl
Phase Diagram from Nonlinear Interaction between Superconducting Order and Density: Toward Data-Based Holographic Superconductor.
CoRR
Sejin Kim, Kyung Kiu Kim, Yunseok Seo
2023 J jnl
Interference-aware execution framework with Co-scheML on GPU clusters.
Clust. Comput.
Sejin Kim, Yoonhee Kim
2023 — conf
Privacy-Preserving Dashboard for F.A.I.R Head and Neck Cancer data supporting multi-centered collaborations.
SWAT4HCLS
Varsha Gouthamchand, Ananya Choudhury, Frank Hoebers, Frederik Wesseling, Mattea Welch, Sejin Kim, Benjamin Haibe-Kains, Joanna Kazmierska, Andre Dekker, Johan van Soest, Leonard Wee
2022 J jnl
FastCPH: Efficient Survival Analysis for Neural Networks.
CoRR
Xuelin Yang, Louis Abraham, Sejin Kim, Petr Smirnov, Feng Ruan, Benjamin Haibe-Kains, Robert Tibshirani
2022 J jnl
K-Scheduler: dynamic intra-SM multitasking management with execution profiles on GPUs.
Clust. Comput.
Sejin Kim, Yoonhee Kim
2022 J jnl
Multi-condition multi-objective optimization using deep reinforcement learning.
J. Comput. Phys.
Sejin Kim, Innyoung Kim, Donghyun You
2022 J jnl
Optimal mesh generation for a blade passage using deep reinforcement learning.
CoRR
Innyoung Kim, Sejin Kim, Donghyun You
2022 J jnl
SEMS: Scalable Embedding Memory System for Accelerating Embedding-Based DNNs.
IEEE Comput. Archit. Lett.
Sejin Kim, Jungwoo Kim, Yongjoo Jang, Jaeha Kung, Sungjin Lee
2021 J jnl
A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Data.
CoRR
Michal Kazmierski, Mattea Welch, Sejin Kim, Chris McIntosh, Katrina Rey-McIntyre, Shao-Hui Huang, Tirth Patel, Tony Tadic, Michael F. Milosevic, Fei-Fei Liu, Andrew Hope, Scott V. Bratman, Benjamin Haibe-Kains
2021 B conf
Appreciating interleaved benefits: The effect of metacognitive activities on the selection of learning strategy.
CogSci
Sejin Kim, Hee Seung Lee
2021 J jnl
Control of a fly-mimicking flyer in complex flow using deep reinforcement learning.
CoRR
Seungpyo Hong, Sejin Kim, Donghyun You
2021 J jnl
Deep Partitioned Training From Near-Storage Computing to DNN Accelerators.
IEEE Comput. Archit. Lett.
Yongjoo Jang, Sejin Kim, Daehoon Kim, Sungjin Lee, Jaeha Kung
2021 — conf
Deep-CR MTLR: a Multi-Modal Approach for Cancer Survival Prediction with Competing Risks.
SPACA
Sejin Kim, Michal Kazmierski, Benjamin Haibe-Kains
2021 J jnl
Multi-condition multi-objective optimization using deep reinforcement learning.
CoRR
Sejin Kim, Innyoung Kim, Donghyun You
2020 C conf
Co-scheML: Interference-aware Container Co-scheduling Scheme Using Machine Learning Application Profiles for GPU Clusters.
CLUSTER
Sejin Kim, Yoonhee Kim
2020 J jnl
Deep-CR MTLR: a Multi-Modal Approach for Cancer Survival Prediction with Competing Risks.
CoRR
Sejin Kim, Michal Kazmierski, Benjamin Haibe-Kains
2020 C conf
Exploiting Interference-aware GPU Container Concurrency Learning from Resource Usage of Application Execution.
APNOMS
Sejin Kim, Yoonhee Kim
2020 — conf
Toward Interference-aware GPU Container Co-scheduling Learning from Application Profiles.
ACSOS Companion
Sejin Kim, Yoonhee Kim
2020 — conf
XGBoost based Packer Identification study using Entry point.
ICEA
Sejin Kim, TaeJin Lee
2019 C conf
Data Provenance for Experiment Management of Scientific Applications on GPU.
APNOMS
Sejin Kim, Jisun Oh, Yoonhee Kim
2018 — conf
Formation-Based Tracking Method for Human Following Robot.
UR
Joonwoo Ahn, Minsung Kim, Sejin Kim, Sangyup Lee, Jaeheung Park
2015 J jnl
A trust value-based scheme for efficient contents sharing over mobile P2P networks.
J. Supercomput.
Sejin Kim, Hyerim Kim, Sung Jo Kim