<!-- Generated from the canonical HTML during the site build. -->

Canonical URL: [https://www.taislab.co.kr/teaching/](https://www.taislab.co.kr/teaching/)

# Teaching

University courses, teaching evidence, and selected additional teaching.

Formal courses

## University Teaching

### Spring 2026

9-credit teaching load

#### Python Programming

Sungshin Women's University

Undergraduate common-curriculum course

Section 003 · 3 credits

#### Python Programming

Sungshin Women's University

Undergraduate common-curriculum course

Section 004 · 3 credits

#### Artificial Intelligence Basics

Sungshin Women's University

Undergraduate core course

Section 001 · 3 credits

### Autumn 2025

9-credit teaching load

#### Artificial Intelligence Security

Sungshin Women's University

Advanced undergraduate course

Section 001 · 3 credits

#### Database Security

Sungshin Women's University

Advanced undergraduate course

Section 002 · 3 credits

#### Cybersecurity Monitoring

Sungshin Women's University

Advanced undergraduate course, taught in weeks 9–15

Section 001 · team-taught

#### Cybersecurity Monitoring

Sungshin Women's University

Advanced undergraduate course, taught in weeks 1–8

Section 002 · team-taught

### Spring 2025

9-credit teaching load

#### Python Programming

Sungshin Women's University

Undergraduate common-curriculum course

Section 003 · 3 credits

#### Python Programming

Sungshin Women's University

Undergraduate common-curriculum course

Section 005 · 3 credits

#### Artificial Intelligence Basics

Sungshin Women's University

Undergraduate core course

Section 001 · 3 credits

### Autumn 2024

9-credit teaching load

#### Artificial Intelligence Security

Sungshin Women's University

Advanced undergraduate course

Section 001 · 3 credits

#### Database Security

Sungshin Women's University

Advanced undergraduate course

Section 003 · 3 credits

#### Introduction to Information Security Technology

Sungshin Women's University

Postgraduate course using lectures, paper presentations, discussion, and projects

Section 001 · 3 credits

### Spring 2024

Postgraduate teaching

#### AI Programming

Soongsil University

Postgraduate course

#### Machine Learning-Based Communication Network Security

Sungshin Women's University

Postgraduate course

Evaluation and development

## Teaching Evidence

- Across 11 independently taught course sections audited from 2024 to 2026, final course-evaluation averages ranged from 4.41 to 4.88 out of 5, based on 373 responses, with a response-weighted mean of 4.60.
- In Spring 2026, Artificial Intelligence Basics received 4.60 out of 5 in the final evaluation with 95 of 100 students responding. Python Programming sections received 4.57 and 4.77 out of 5.
- Teaching combines conceptual foundations with coding, practical attack-and-defence exercises, research papers, presentations, and projects. Formal CQI feedback is used to improve pacing, materials, practical work, and explanation of technical terminology.

Postgraduate, international, and invited teaching

## Additional Teaching

### Convergence Technology Seminar

Sungshin Women's University

Two sessions in shared master's and doctoral seminars on LLM agents and healthcare AI agents

Spring 2026

### LLM Security: RAG Poisoning Attacks and Defences

Modulabs Everyone's Lab

Invited lecture

Apr 2026

### AI Security: Leveraging Large Language Models to Address Security Challenges

Korea–Central Asia STEM Youth Silk Road programme

Three-hour English-medium international lecture

Jan 2026

### LLM-Based Automated Vulnerability Detection and Patch Generation

Ulsan National Institute of Science and Technology

Invited lecture

2025

### AI Agents and Automation: Current Research Trends and Innovative Applications

Korea Information Processing Society

Invited short-course lecture

2025

### AI Project Programme

Soongsil University AI Convergence Research Institute

Three invited teaching sessions

Jun–Aug 2024

### AI Security

Sungshin Women's University

Six-week postgraduate lecture series covering adversarial examples, model extraction, federated-learning security, model inversion, and differential privacy

Sep–Oct 2023
