SeoulTech HAI Lab

Alumni

Visiting Faculty 3

Alumni M.S. 8

Sabin Lee

2026.08

Sabin Lee

Dissertation CodeFlow: A Cognitive-Aware Proactive AI Programming Assistant for Enhancing Developers’ Productivity and Experiences

Paper works 4
  1. Lee, D., Lee, S., Fels, S. S., & Seo, K. (2025, April). How Students' Self-Regulated Learning Abilities Influence Intents and Engagement Goals in Chatbot-Assisted Writing. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1–7).
  2. Lee, S., Lee, D., & Seo, K. (2025). ArguePro: Enhancing argumentation skills through active learning with chatbots. 한국 HCI 학회 학술대회, 326–331.
  3. Lee, D., Lee, S., & Seo, K. (2025). Active learning with chatbot: How students engage in argumentative writing with chatbot. 한국 HCI 학회 학술대회, 320–325.
  4. Lee, S., Park, B., Kim, D., & Seo, K. (2024). Artificial intelligence-based heritage tree disease diagnosis using transfer learning: A case study of zelkova serrata. 한국 HCI 학회 학술대회, 211–219.
Minyoung Park

2026.02

Minyoung Park

Dissertation Designing empathetic self-disclosure in LLM-based chatbots to enhance students' self-reflection, engagement, and assessment accuracy

Paper works 5
  1. Park, M., Fels, S., & Seo, K. (2025). Enhancing academic stress assessment through self-disclosure chatbots: effects on engagement, accuracy, and self-reflection. International Journal of Educational Technology in Higher Education, 22(1), 28.
  2. Park, M., Park, B., & Seo, K. (2025, April). How Self-Disclosing Chatbots Influence Student Engagement, Assessment Accuracy, and Self-Reflection in Academic Stress Assessment. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1–10).
  3. Park, M., Park, B., & Seo, K. (2025). The impact of self-disclosing chatbots for academic stress assessment on student self-reflection. 한국 HCI 학회 학술대회, 560–568.
  4. Song, C., Park, M., Kim, D., & Seo, K. (2024). ChatGPT as an assistant of human teacher: Student competency analysis through prompt engineering. 한국 HCI 학회 학술대회, 175–182.
  5. Park, M., & Seo, K. (2023). Passive vs. Active: Which behavior is better for predicting at-risk students in online learning? 한국 HCI 학회 학술대회, 815–821.
Hyeonju Keum

2026.02

Hyeonju Keum

Dissertation Enhancing the reliability of LLM-as-a-Judge by generating rubrics with types tailored to evaluation contexts

Paper works 1
  1. Keum, H., Kim, Y., You, D., & Seo, K. (2025). A deep learning model for stress level recognition utilizing neutral and stress state of remote photoplethysmography. 한국 HCI 학회 학술대회, 31–36.
Dana You

2026.02

Dana You

Dissertation LLM-based Virtual Counselor: A Comparison of Socratic and Didactic Counseling Styles for Academic Stress Management

Paper works 4
  1. You, D., Kim, Y., & Seo, K. (2025, April). Tailored Virtual Agent Guidance for Stress Management: Comparing Directive and Non-Directive Approaches by Alexithymia Status. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1–8).
  2. You, D., Kim, Y., & Seo, K. (2025). Digital mental health intervention with virtual agent: impact of guidance approaches on stress reduction in young adults. 한국 HCI 학회 학술대회, 350–356.
  3. Keum, H., Kim, Y., You, D., & Seo, K. (2025). A deep learning model for stress level recognition utilizing neutral and stress state of remote photoplethysmography. 한국 HCI 학회 학술대회, 31–36.
  4. You, D., Kim, S. Y., & Seo, K. (2024). Enhancing memory through increased social presence via active interaction with a virtual agent in VR memory training task: feasibility and usability study. 한국 HCI 학회 학술대회, 68–73.
Hyerim Han

2025.08

Hyerim Han

Dissertation Enhancing students’ career decision-making and motivation with a self-determination theory-based career counseling chatbot

Paper works 1
  1. Han, H., Park, B., & Seo, K. (2025, April). A Self-Determination Theory-based Career Counseling Chatbot: Motivational Interactions to Address Career Decision-Making Difficulties and Enhance Engagement. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1–9).
Doo Soung Choi

2025.02

Doo Soung Choi

Dissertation Improving counseling effectiveness with virtual counselors through nonverbal compassion involving eye contact, facial mimicry, and head-nodding

Paper works 1
  1. Choi, D. S., Park, J., Loeser, M., & Seo, K. (2024). Improving counseling effectiveness with virtual counselors through nonverbal compassion involving eye contact, facial mimicry, and head-nodding. Scientific Reports, 14(1), 506.
Dongyub Lee

2025.02

Dongyub Lee

Dissertation Active learning with chatbot: The impact of self-regulated learning on students’ engagement in argumentative writing

Paper works 3
  1. Lee, D., Lee, S., & Seo, K. (2025). Active learning with chatbot: How students engage in argumentative writing with chatbot. 한국 HCI 학회 학술대회, 320–325.
  2. Lee, S., Lee, D., & Seo, K. (2025). ArguePro: Enhancing argumentation skills through active learning with chatbots. 한국 HCI 학회 학술대회, 326–331.
  3. Lee, D., Kim, D., Loeser, M., & Seo, K. (2025, January). How Large Language Models are Transforming Teachers' Assessment of Student Competency: A Case Study on LLM-Based Report Writing. In 2025 International Conference on Electronics, Information, and Communication (ICEIC) (pp. 1–4). IEEE.
Dohyun Kim

2024.08

Dohyun Kim

Dissertation Utilization of EEG-SSVEP Neurological Biomarkers and Machine Learning for Early Detection of Mild Cognitive Impairment

Paper works 4
  1. Kim, D., Park, J., Choi, H., Ryu, H., Loeser, M., & Seo, K. (2024). Early Detection of Patients With Mild Cognitive Impairment Through EEG-SSVEP-Based Machine Learning Model. IEEE Access.
  2. Kim, D., Kim, Y., Park, J., Choi, H., Ryu, H., Loeser, M., & Seo, K. (2024). Exploring the relationship between behavioral and neurological impairments due to mild cognitive impairment: Correlation study between virtual kiosk test and EEG-SSVEP. Sensors, 24(11), 3543.
  3. Kim, S. Y., Park, B., Kim, D., Choi, H., Park, J., Ryu, H., & Seo, K. (2024, January). Early screening of mild cognitive impairment using multimodal VR-EP-EEG-MRI (VEEM) biomarkers via machine learning. In 2024 International Conference on Electronics, Information, and Communication (ICEIC) (pp. 1–4). IEEE.
  4. Kim, D., Park, J. S., Choi, H., Ryu, H., & Seo, K. (2023). Deep learning model for early screening of patients with Alzheimer's disease and mild cognitive impairment using EEG-SSVEP. 한국 HCI 학회 학술대회, 781–787.