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Zhendong Wang

Profilbild av Zhendong Wang

Postdoktor

Detaljer

Arbetar vid

Teknisk informationsvetenskap

Enhetens adress
Malvinas Väg 10
E-post
zhwang@kth.se
Rum
A:419

Forskare

Om mig

Postdoctoral Researcher at the School of Electrical Engineering and Computer Science (EECS) of KTH Royal Institute of Technology. Affiliated to Björn Nordlund's research group at the Department of Women's and Children's Health of Karolinska Institutet (KI).

Research Interests:

  • EXplainable Artificial Intelligence (XAI)

  • Temporal data mining

  • Machine learning for healthcare

Teaching Activities:

  • Thesis supervision:

    • 1 Master's (MSc) thesis (ongoing), EECS, KTH Royal Institute of Technology (2025-Present).

    • 2 Doctor of Medicine (MD) theses (ongoing, co-supervising), KBH, Karolinska Institutet (2025-Present).

    • 6 Master's (MSc) theses and 3 Bachelor's (BSc) theses, DSV, Stockholm University (2022-2024).

  • Guest lectured on ML Interpretability (Counterfactual Explanations) for the Research Topics in Data Science (DAMI II) course, DSV, Stockholm University (HT2023/HT2024).

  • Teaching assistant:

    • Research Topics in Data Science (DAMI II), DSV, Stockholm University (2022-2024).

    • Introduction to Machine Learning (732A95), Linköping University (2017-2018).

    • Neural Network and Learning Systems (TBMI26), Linköping University (2017-2018).

    • Computational Statistics (732A90), Linköping University (2017-2018).

Research Projects:

  • JSPS: Causal Machine Learning for Individualized Treatment Decision Support (2026 Jul-Sep).

  • A3S: AI-based Asthma App using Spirometer (Digital Futures, 2025-Present).

  • EXTREMUM: Explainable and Ethical Machine Learning for Knowledge Discovery from Medical Data Sources (Digital Futures, 2020-2024).

Research Activities:

Recent Publications:

  • Z. Wang, M. Jansson, S. Chatterjee, H Ljungberg, L. Myers, I. Miliou, B. Nordlund, "Utilising real-world temporal home spirometry data for predicting asthma exacerbations", European Respiratory Congress (European Respiratory Journal - Late Breaking Abstract), vol. 66, no. suppl 69, Nov. 2025, doi: 10.1183/13993003.congress-2025.PA2041.

  • D. G. Pérez,Z. Wang, and J. M. E. González, “CACTUS: A Context-Aware Framework for Counterfactual Explanations Across Diverse Prediction Domains”, in Discovery Science, Cham, 2025, pp. 460–475. doi: 10.1007/978-3-032-05461-6_30.

  • Z. Wang, I. Samsten, I. Miliou, R. Mochaourab, and P. Papapetrou, “Glacier: guided locally constrained counterfactual explanations for time series classification”, Machine Learning, vol. 113, no. 3, Mar. 2024, doi: 10.1007/s10994-023-06502-x.

  • Z. Wang, I. Samsten, I. Miliou, and P. Papapetrou, “COMET: Constrained Counterfactual Explanations for Patient Glucose Multivariate Forecasting”, in 2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS), Jun. 2024, pp. 502–507. doi: 10.1109/CBMS61543.2024.00089.

  • Z. Wang, I. Miliou, I. Samsten, and P. Papapetrou, “Counterfactual Explanations for Time Series Forecasting”, in 2023 IEEE International Conference on Data Mining (ICDM), Dec. 2023, pp. 1391–1396. doi: 10.1109/ICDM58522.2023.00180.

  • Z. Wang, I. Samsten, V. Kougia, and P. Papapetrou, ‘Style-transfer counterfactual explanations: An application to mortality prevention of ICU patients’, Artificial Intelligence in Medicine, p. 102457, Nov. 2022, doi: 10.1016/j.artmed.2022.102457.

  • Z. Wang, I. Samsten, and P. Papapetrou, ‘Counterfactual Explanations for Survival Prediction of Cardiovascular ICU Patients’, in Artificial Intelligence in Medicine, Cham, 2021, pp. 338–348. DOI: 10.1007/978-3-030-77211-6_38. (Best Student Paper Award)

Journal Reviewing:

  • Reviewer for Artificial Intelligence in Medicine (AIIM) (2025–Present).

Talks and Seminars:

  • Talk: "Explainable Machine Learning for Temporal Prediction Models in Healthcare", Department of System Design Engineering, Keio University (visit to Mitsukura Lab), July 2026.

  • Talk: "Predicting Asthma-Related Reduction Using Remote Real-world Temporal Home Spirometry Data", The Centre for Allergy (CfA), Karolinska Institute (CfA Day, Junior Faculty Talks), May 2026.

  • Seminar: "Explainable Machine Learning for Asthma Patient Management", Mayo Clinic (visit to KTH), October 2025.

  • Talk: "Counterfactual Explanations for Temporal Data in Healthcare", Department of Statistics, Stockholm University, May 2025.

Profilbild av Zhendong Wang