Curriculum Vitae

Junhee Kim

M.S. Student in Statistics & Data Science at Inha University

I work on Bayesian machine learning, uncertainty quantification, molecular toxicity prediction, and time-series anomaly detection. My recent research focuses on reliable probabilistic modeling for sensor, molecular, and domain-informed prediction problems.

Junhee Kim portrait
Uncertainty Quantification Molecular Toxicity Time-Series Anomaly Detection

Current Role

Graduate Research Assistant

Bayesian Inference Lab, Inha University

Research Focus

Bayesian ML & Uncertainty Quantification

Probabilistic modeling for sensor, molecular, and time-series data

Output

4 Publications · 3 Talks · 1 Patent

Molecular modeling, Bayesian optimization, time-series analysis, and domain-informed learning

Highlights

4 Awards

AI challenge, hackathon, conference paper, and project recognition

01

Education

Academic background in statistics, data science, and software convergence.

Feb. 2025 - Feb. 2027 (expected)

M.S. in Statistics & Data Science

Inha University · GPA 4.43 / 4.50

Bayesian Inference Lab, advised by Seongil Jo.

Mar. 2019 - Jul. 2023

B.S. in Statistics

Inha University · GPA 4.14 / 4.50

Interdisciplinary major in Samsung Convergence Software Course.

02

Experience

Research positions spanning Bayesian statistics, HCI, and deployable AI systems.

Feb. 2025 - Present

Graduate Research Assistant

Bayesian Inference Lab · Department of Statistics, Inha University

  • Researching machine learning and deep learning methods for complex data including multi-channel gas sensors, molecular toxicity data, and time-series anomaly detection tasks.
  • Developing Bayesian ML, Gaussian process, and probabilistic AI models to quantify predictive uncertainty and improve reliability.
  • Serving as a teaching assistant for Data Visualization Lab (Spring 2025) and Regression Analysis Lab (Fall 2025).

Sep. 2023 - Jul. 2024

Undergraduate Research Intern

Human Computer Interaction Lab · Department of Computer Engineering, Inha University

  • Applied deep learning models to real-world sensor data including vibration and accelerometer signals.
  • Handled the end-to-end pipeline from data collection and preprocessing to model implementation and edge deployment.

Jul. 2024 - Feb. 2025

Undergraduate Research Intern

Bayesian Inference Lab · Department of Statistics, Inha University

  • Implemented advanced statistical models including Bayesian methods and graphical models.
  • Focused on probabilistic approaches for prediction and structured data analysis.

03

Research Output

Publications, presentations, and intellectual property across applied AI and statistical modeling.

Publication

Research on Driving Pattern Analysis Techniques Using Contrastive Learning Method

Hoe Jun Jeong, Seung Ha Kim, Junhee Kim, Jang Woo Kwon

Journal of the Korea Institute of Intelligent Transport Systems, Feb. 2024

Publication

Submitted

A Domain-Informed Composite Kernel Gaussian Process Classifier for Molecular Toxicity Prediction with Principled Uncertainty Quantification

Junhee Kim, Seongil Jo, Jooyeon Lee, Jahyun Koo, and Keunhong Jeong

Journal of Cheminformatics, May 2026

Publication

Under Revision

One-class Classification Using Bayesian Optimization

Junhee Kim, Inyoung Baek, Yeongmin Lee, Jaeoh Kim, and Seongil Jo

Computational Statistics, May 2026

Presentations

  • Bayesian Kernel Ridge on GAT Embeddings for Molecular Prediction
    BayesComp 2025, Singapore · Poster Presentation · Jun. 2025
  • Predicting Movement Paths in Search and Rescue Operations Using Reinforcement Learning
    The 12th IASC-ARS Conference, Taipei · Poster Presentation · Dec. 2024
  • Driver Drowsiness Detection System Improving SwinTransformer
    2024 ITS Korea Spring Conference · Oral Presentation · Dec. 2023

Patent

Method and System for Predicting Movement Paths in Search and Rescue Operations

Patent No. 10-2024-2864144

Filing title: AI-based movement path prediction system for search and rescue operations.

04

Awards

Recognition across research, competition, and conference settings.

2025

Inha AI Challenge

Grand Award, Inha University AI Convergence Research Center

2025

LG Aimers On Offline AI Hackathon

Finalist, 7th place

2024

Best Paper Award

Anomaly Detection in Driving Patterns Using Contrastive Learning, 2023 ITS Korea Fall Conference

2023

Bronze Prize

Road Surface Detection System Using Smartphone Accelerometer Sensors, Fall 2023 VIP Presentation

05

Skills

Tooling and modeling stack for statistical research and machine learning systems.

Programming

Python R

ML / DL Frameworks

PyTorch TensorFlow Scikit-learn Pandas Polars SciPy

Tools & Platforms

Git GitHub Docker VS Code RStudio Notion