📬 Contact
👤 Profile
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AI researcher specializing in Battery AI through the integration of electrochemistry and machine learning.
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- Current Member of NICELAB, Sogang University
🔬 Research Interests
- Battery AI (electrochemistry + machine learning)
- Battery state/health diagnosis & anomaly detection
- Neural surrogate modeling & data-driven parameter identification
- Battery Electrochemistry + LLM
💼 Work Experience
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Visiting Student (Jan. 2025 - Jun. 2025)
University of Toronto
- Dispatch Training and Applied project (Supported by IITP)
- Applied Project: FASTe: Framework with Application-driven Spatio-Temporal Efficiency for Video Anomaly Detection (with LOREX Corporation US)
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Teaching Assistant
- 2024.09 - 2024.12: Advanced Electronic Circuit Laboratory II
- 2022.09 - 2022.12: Advanced Electronic Circuit Laboratory II
- 2021.09 - 2021.12: Advanced Engineering Mathematics II
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📝 Publications
🌍 International
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Battery Usage-Agnostic Multi-Task Diagnostics Using Contrastive Learning and Knowledge-guided Voltage Relaxation
J. Jeon, H. Cheon, M. Kim, H. Seo, and H. Kim, Journal of Energy Storage, pp.1-11, Jul. 2026
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Battery Health Diagnosis via Neural Surrogate Model: From Lab to Field
H. Cheon, J. Jeon, B. Jung, and H. Kim, Energies, pp.1-15, Mar. 2025
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ProADD: Proactive Battery Anomaly Dual Detection Leveraging Denoising Convolutional Autoencoder and Incremental Voltage Analysis
J. Jeon, H. Cheon, B. Jung and H. Kim, Applied Energy, pp.1-14, Nov. 2024.
On going
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Fixed Point Neural Acceleration and Inverse Surrogate Model for Battery Parameter Identification
H. Cheon, H. Seo, J. Jeon, and H. Kim, under revision, Applied Energy