Andrew Wan Ju Kang

Bio

I am a postdoc working with Professor Isabelle Augenstein in the CopeNLU group, Department of Computer Science, University of Copenhagen. I am currently affiliated with the Pioneer Centre for AI. My research interests include knowledge conflicts, interpretable attribution of knowledge sources, and agent-assisted decision-making in high-stakes domains such as health and medicine. Feel free to connect with me and have a chat!

Education

• PhD, KAIST
  Kim Jaechul Graduate School of Artificial Intelligence, 2025
  Thesis: Evaluating Vision-Language Representations towards Bias Measurement
  Advisor: Professor Se-Young Yun
  
• BS, KAIST
  School of Electrical Engineering, 2017
  Double Major in Business Technology Management
  

Research

• MondegreensEval: A Phonetic Benchmark for Measuring Language-model Bias in Automatic Speech Recognition.
  Wan Ju Kang
  ICML Workshop on ML For Audio, 2026. [Paper | Code | Dataset | Poster | Slides]
• Benchmarking and Mitigating Modality Bias in Vision-language Models.
  Wan Ju Kang, Sumyeong Ahn, and Se-Young Yun.
  under review, 2026.
• Differential Diffusivity: Latent Diffusion Models as Zero-shot Evaluators of Image Descriptions.
  Wan Ju Kang, Ki Hoon Kwak, Haemin Choi, and James Thorne.
  under review, 2026.
• Are Large Vision-Language Models Ready to Guide Blind and Low-Vision Individuals?
  Na Min An, Eunki Kim, Wan Ju Kang, Sangryul Kim, Hyunjung Shim, and James Thorne.
  COLM, 2026. [Paper | Project]
• Sightation Counts: Leveraging Sighted User Feedback in Building a BLV-aligned Dataset of Diagram Descriptions.
  Wan Ju Kang, Eunki Kim, Na Min An, Sangryul Kim, Haemin Choi, Ki Hoon Kwak, and James Thorne.
  ACL (Main), 2025. [Paper | Dataset | Poster]
• Political Slant Estimation and Mitigation with LLMs: A Parallactical Study on News Articles and Video News Transcripts.
  Wan Ju Kang, Jiyoung Han, Jaemin Jung, and James Thorne.
  working paper, 2025.
• Sampling from Bounded Clusters for Diverse Relevant Argument Retrieval.
  Wan Ju Kang, Jiyoung Han, Jaemin Jung, and James Thorne.
  ACL Workshop on Argument Mining, 2024. [Paper | Poster]

• Curiosity-driven multi-agent exploration with mixed objectives.
  Roben Delos Reyes, Kyunghwan Son, Jinhwan Jung, Wan Ju Kang, and Yung Yi.
  arXiv preprint, 2022. [Paper]
• Reflect, not Regret: Understanding Regretful Smartphone Use with App Feature-Level Analysis.
  Hyunsung Cho, DaEun Choi, Donghwi Kim, Wan Ju Kang, Eun Kyoung Choe, and Sung-Ju Lee.
  ACM CSCW, 2021. [Paper]
• Inducing cooperation through reward reshaping based on peer evaluations in deep multi-agent reinforcement learning.
  David Earl Hostallero, Daewoo Kim, Sangwoo Moon, Kyunghwan Son, Wan Ju Kang, and Yung Yi.
  AAMAS, 2020. [Paper]
• Deep learning approaches to detect atrial fibrillation using photoplethysmographic signals: algorithms development study.
  Soonil Kwon, Joonki Hong, Eue-Keun Choi, Euijae Lee, David Earl Hostallero, Wan Ju Kang, Byunghwan Lee, Eui-Rim Jeong, Bon-Kwon Koo, Seil Oh and Yung Yi.
  JMIR mHealth and uHealth, 2019. [Paper]
• QTRAN: Learning to factorize with transformation for cooperative multi-agent reinforcement learning.
  Kyunghwan Son, Daewoo Kim, Wan Ju Kang, David Earl Hostallero and Yung Yi.
  ICML, 2019. [Paper]
• Learning to schedule communication in multi-agent reinforcement learning.
  Daewoo Kim, Sangwoo Moon, David Earl Hostallero, Wan Ju Kang, Taeyoung Lee, Kyunghwan Son, and Yung Yi.
  ICLR, 2019. [Paper | Slides]

Work & Teaching Experience

• NLP Specialist, NextUs (2023/07 - 2023/09)
  News curation service with political slant detection and measurement. Funded by the Korea Press Foundation.
• NLP Analyst, Seoul National University Asia Center (2022/01 - 2022/07)
  Political polarization trends in traditional and new media. Funded by the Seoul National University Asia Center.
• NLP and Generative AI Course Instructor
  Samsung Electronics (2024/02 - Present),
  [unnamed] (2026/07 - Present),
  KT (2025/06 - 2025/07),
  KAIST IT Academy (2023/01 - 2023/02),
  Daejeon Statistical Training Institute (2022/08),
  Incheon International Airport Academy (2022/08)
• Machine Learning Tutor
  Hyundai Motors (2023/11 - 2023/12),
  LG Chem (2021/12),
  SK Hynix (2019/07),
  Korea Institute of Communications and Information Sciences (2019/02)
• KAIST EE213 Discrete Methods for Electrical Engineering
  Head Teaching Assistant (2020/09 - 2020/12)
  
• KAIST CC500 Scientific Writing and HSS581 Graduate English Writing
  Teaching Assistant (2015/03 - 2017/12)
  
• The KAIST Herald (2012/09 - 2018/06)
  Editor-in-Chief

Honors and Awards

• Cohere Labs Catalyst Grant
  2025 Fall Cohort Recipient for Modality Utilization Imbalance in Multimodal Models (2025)
  
• Seocho AI College Grand Prize
  NLP-based Real-time Voice Phishing Detection in Phone Calls (2022)
  
• Samsung Humantech Award Bronze Prize
  Learning to Schedule Communication in Multi-agent Reinforcement Learning (2019)