Sungjoon Park

Sungjoon Park

Google Scholar · LinkedIn · CV (EN) · contact@sungjoonpark.me

Bio

I am an applied scientist working on AI systems for healthcare applications. I was previously co-founder and CEO of SoftlyAI. I received my Ph.D. from the School of Computing at KAIST, advised by Alice Oh, where my research was supported by the Google PhD Fellowship program. Prior to that, I obtained my B.A. and M.A. in Psychology from Seoul National University.

Research Interest

My research has focused on developing machine learning models that understand complex psychological characteristics from text and applying them to computational psychotherapy applications. I believe natural language serves as a powerful indicator of latent psychological states, as our daily language use encodes personality traits and mental states, even at the level of individual words and conversational patterns.

Given the intricate relationship between language and mental state, my earlier work employed carefully designed machine learning models trained on fine-grained data rather than rule-based approaches. My research agenda has encompassed three interconnected areas: (a) Learning Representation of Text, (b) Measuring Psychological Characteristics from Text, and (c) Developing Psychotherapy Applications. Once models can accurately capture these relationships, they enable psychotherapy programs that detect mental states and facilitate positive psychological changes.

More recently, my interest has expanded to clinical reasoning process modeling, particularly training and employing reasoning models in computational psychotherapy. I am passionate about developing medical intelligence systems that can assist clinical decision-making in real-time and collaborate effectively with healthcare professionals, particularly in mental healthcare and psychiatry. This work bridges natural language processing, computational psychotherapy, and clinical AI, with the ultimate goal of creating intelligent systems that augment human expertise in mental healthcare delivery.

Education

  • KAIST, Ph.D, Computer Science, Mar 2016 – Feb 2022
  • Seoul National University, M.S., Quantitative Psychology, Mar 2012 – Aug 2014
  • Seoul National University, B.S., Psychology, Mar 2007 – Feb 2012

Work Experience

  • CEO / co-founder, SoftlyAI (Jan 2022 – Present)
  • Research Engineer, Upstage (Oct 2020 – Oct 2021)
  • Research Intern, Google Research (July 2020 – Oct 2020)
  • Research Intern, KakaoBrain (Mar 2020 – July 2020)
  • Research Intern, Clova AI Research, Naver (Aug 2019 – Feb 2020)
  • Graduate Researcher, KAIST, U&I Lab (Dec 2014 – Feb 2016)
  • Research Assistant, SNU Asia Center (Jan 2014 – Aug 2014)

Awards

  • PhD Dissertation Award, Dept. of Computing, KAIST
  • Google Ph.D Fellowship, Natural Language Processing, Sep 2019 - Aug 2020

Publications

  1. Park, K., Baik, M.J., Hwang, Y.J., Shin, Y., Lee, H.J., Lee, R., Lee, S.M., Park, S., et al. (2024) Harmful Suicide Content Detection arXiv preprint arXiv:2407.13942
    Arxiv
  2. Lee, D.H., Cho, H., Jin, W., Moon, J., Park, S., Röttger, P., Pujara, J., Lee, R.K.W. (2024) Improving Covert Toxicity Detection by Retrieving and Generating References In Proceedings of the 8th Workshop on Online Abuse and Harms (WOAH 2024)
    PDF
  3. Shin, J., Yoon, H., Lee, S., Park, S., Liu, Y., Choi, J.D., Lee, S.J. (2023) FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)
    PDF
  4. Moon, J., Lee, D.H., Cho, H., Jin, W., Park, C.Y., Kim, M., May, J., Pujara, J., Park, S. (2023) Analyzing Norm Violations in Live-Stream Chat In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)
    PDF
  5. Yoon, S., Park, S., Kim, G., Cho, J., Park, K., Kim, G., Seo, M., Oh, A. (2023) Towards Standardizing Korean Grammatical Error Correction: Datasets and Annotation In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)
    PDF
  6. Jeong, Y., Oh, J., Lee, J., Ahn, J., Moon, J., Park, S., Oh, A. (2022) KOLD: Korean Offensive Language Dataset In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)
    PDF
  7. Park, S.*, Moon, J.*, Kim, S.*, Cho, W.*, Han, J., Park, J., Song, C., Kim, J., Song, Y., Oh, T., Lee, J., Oh, J., Lyu, S., Jeong, Y., Lee, I., Seo, S., Lee, D., Kim, H., Lee, M., Jang, S., Do, S., Kim, S., Lim, K., Lee, J., Park, K., Shin, J., Kim, S., Park, L., Oh, A., Ha, J., Cho, K. (2021) KLUE: Korean Language Understanding Evaluation In NeurIPS 2021 Datasets and Benchmarks Track (Neurips 2021) *equal contribution
    Neurips Arxiv Github Leaderboard
  8. Park, S., Kim, J., Ye, S., Jeon, J., Park, H., Oh, A. (2021) Dimensional Emotion Detection in Categorical Emotion In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)
    PDF Data
  9. Park, S.*, Park, K.*, Ahn, J. Oh, A. (2020) Suicidal Risk Detection for Military Personnel In Proceedings of the in the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) *equal contribution
    PDF Data
  10. Park, C., Shin, J., Park, S., Lim, J., Lee, C. (2019) Fast End-to-end Coreference Resolution for Korean In Proceedings of the Findings of 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020 - Findings)
    PDF
  11. Seonwoo, Y., Park, S., Kim, D., Oh, A. (2019) Additive Compositionality of Word Vectors In Workshop on Noisy User-generated Text (W-NUT) @EMNLP 2019
    PDF
  12. Park, S., Park, H., Kim, C. (2019) A Comparison between Factor Structure and Semantic Representation of Personality Test Items Using Latent Semantic Analysis Korean Journal of Cognitive Science, 30(3)
    PDF
  13. Park, S., Kim, D., Oh, A. (2019) Conversation Model Fine-Tuning for Classifying Client Utterances in Counseling Dialogues In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2019)
    PDF
  14. Park, S., Seonwoo, Y., Kim, J., Kim, J., Oh, A. (2019) Denoising Recurrent Neural Networks for Classifying Crash-related Events IEEE Transactions of Intelligent Transportation Systems.
    PDF
  15. Seonwoo, Y., Park, S., Oh, A. (2018) Hierarchical Dirichlet Gaussian Marked Hawkes Process for Narrative Reconstruction in Continuous Time Domain In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018)
    PDF
  16. Park, S., Byun, J., Baek, S., Cho, Y., Oh, A. (2018) Subword-level Word Vector Representations for Korean In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018)
    PDF Data
  17. Park, S., Bak, J., Oh, A. (2017) Rotated Word Vector Representations and their Interpretability. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2017)
    PDF Source
  18. Kim, S., Park, S., Hale, S. A., Kim, S., Byun, J., & Oh, A. H. (2016). Understanding editing behaviors in multilingual Wikipedia. PLOS ONE, 11(5), e0155305.
    Article
  19. Kim, J., Keegan, B. C., Park, S., & Oh, A. (2016). The Proficiency-Congruency Dilemma: Virtual Team Design and Performance in Multiplayer Online Games. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI 2016)
    PDF
  20. Park, S., Kim, S., Hale, S. A., Kim, S., Byun, J., & Oh, A. (2015). Multilingual Wikipedia: Editors of Primary Language Contribute to More Complex Articles. In Ninth International AAAI Conference on Web and Social Media.(Wiki-ICWSM Workshop in ICWCM 2015)
    PDF

Talks / Presentations

  • 2020.7.30 Conversation Model Fine-Tuning for Classifying Client Utterances in Counseling Dialogues, Google Ph.D Fellowship Summit.
  • 2018.9.10 Subword-level Word Vector Representations for Korean & Learning Client's Information from Counseling Conversations, Facebook AI Research, Paris.
  • 2017.10.19. Rotated Word Vector Representations and their Interpretability (Poster), Samsung AI Forum 2017.
  • 2016.11.18 Chung, M., Park, S., Kim, M., & Harris, C. R. Medical Embarrassment: A Cross-cultural Perspective. Poster presented at the Psychonomics 2016, Boston, MA.

Teaching Experiences

  • SEP592 Special Topics in Software (Introduction to Data Science), KAIST, Head TA, (Spring, 2019)
  • CS570 Artificial Intelligence & Machine Learning, KAIST, Head TA, (Spring, 2017)
  • CS206 Data Structure, KAIST, TA, (Fall, 2016)
  • Advanced Psychological Statistics, Seoul National University, TA, (Spring, 2013)
  • Psychological Statistics, Seoul National University, TA, (Spring, 2012)

Academic Services

  • Reviewer, EMNLP 2022, EMNLP 2020, EMNLP 2019, ACL 2019
  • Invited Reviewer, WWW 2019
  • Subreviewer, EACL 2017

References

  • Prof. Alice Haeyun Oh, Department of Computing, KAIST, alice.oh@kaist.edu