CV
Curriculum vitae of SooHwan Eom.
Contact Information
| Name | SooHwan Eom |
| Professional Title | PhD Student, Electrical Engineering, KAIST |
| sean1105@kaist.ac.kr |
Professional Summary
PhD student in Electrical Engineering at KAIST, advised by Prof. Chang D. Yoo. Research interests span large language model alignment and reasoning, multimodal learning, and self-supervised speech representation learning, with a focus on principled methods for adapting and improving foundation models under limited, noisy, or structured supervision.
Education
- 2024 – Present
- Advisor: Prof. Chang D. Yoo (U-AIM Lab)
- GPA: 4.06 / 4.3
- 2022 – 2024
- Advisor: Prof. Chang D. Yoo (U-AIM Lab)
- Thesis: Adaptive Maximum Entropy Regularization for Connectionist Temporal Classification
- GPA: 4.0 / 4.3
- 2017 – 2022
- GPA: 3.49 / 4.3
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High School Diploma
Korean Minjok Leadership Academy (KMLA)
2014 – 2017
Research Experience
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Research Student
Artificial Intelligence & Machine Learning Lab (U-AIM), KAIST
2022 – Present -
Research Intern
Artificial Intelligence & Machine Learning Lab (U-AIM), KAIST
2021 – 2022
Awards
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National Government Scholarship (full payment for M.S. program)
2022 – 2024 -
National Government Scholarship (full payment for Ph.D. program)
2024 – Present
Academic Services
Conference Reviewing
- International Conference on Machine Learning (ICML): 2026 (Gold Reviewer; top 25%)
- International Conference on Acoustics, Speech & Signal Processing (ICASSP): 2024, 2025, 2026
Teaching Assistance
- KAIST EE.40012 Foundation of Big Data Analytics (2024 Fall)
- KAIST EE.50031 Statistical Learning Theory (2024 Spring, 2025 Spring, 2026 Spring)
- KAIST EE.30031 Introduction to Machine Learning (2023 Fall, 2025 Fall)
- KAIST EE.20002 Signals and Systems (2023 Spring, 2022 Fall)
- Hwaseong City-KAIST AI Specialized Curriculum - Large Language Models: 2024
- Seongnam-KAIST Next Generation ICT Research Center EE Co-op+ Joint Research Program: 2022 Fall, 2024 Fall
- Seongnam-KAIST Next Generation ICT Research Center Machine Learning and Big Data Course: 2022
Projects
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Research on Scene Understanding and Causal Inference for Video-Based Surveillance and Reconnaissance
Operator · 2023 – 2026
- Supported by the Center for Applied Research in Artificial Intelligence (CARAI) grant funded by DAPA and ADD, Korea.
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Circuit Foundation Model for DRAM Design
Co-operator · 2025 – Present
- Supported by Samsung Electronics Device Solution.
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Agentic AI System for Autonomous Root Cause Analysis and Verification in Display Manufacturing Process
Supporter · 2025 – Present
- Supported by Samsung Display Co., Ltd.
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Development of Causal AI through Video Understanding and Reinforcement Learning, and Its Applications to Real Environments
Supporter · 2022 – Present
- Supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea Government (MSIT).
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Development and Study of AI Technologies to Inexpensively Conform to Evolving Policy on Ethics
Supporter · 2022 – Present
- Supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea Government (MSIT).
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Development of Uncertainty-Aware Agents Learning by Asking Questions
Supporter · 2022 – Present
- Supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea Government (MSIT).
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Multi-modal Generative AI for Summarization
Supporter · 2023 – 2024
- Supported by Samsung Speech Recognition & Natural Language Processing Lab.
Interests
Research: LLM alignment & reasoning, multimodal learning, self-supervised speech representation, parameter-efficient adaptation of foundation models