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The Epistemic Intelligence & Computation (EPIC) Lab is dedicated to understanding the underlying principles to develop uncertainty-aware intelligent systems that can recognise and communicate the limits of their knowledge. Specifically, we ask how should epistemic uncertainty be mathematically represented, quantified, evaluated, compared, and explained? To achieve that, our research spans a variety of topics between machine learning and statistical methodologies, including:
  • Imprecise Probabilistic Machine Learning
  • Axiomatic Model Explainability
  • Probabilistic reasoning with Kernel methods and Gaussian Processes
  • Decision-making under Epistemic Uncertainty

We have openings for PhD students in Aug 2026 to be based in Singapore and are looking for candidates with strong mathematical, statistical, or machine learning background, please get in touch if you are interested.

Current Members

  • Kaizheng Wang, Postdoctoral research fellow @ NTU
    • Previously PhD student @ KU Lueven, Belgium
    • Topic: Imprecise probabilistic machine learning
  • Clayton Chong, PhD student @ NTU
    • Previously Masters in Mathematics @ University of Oxford, United Kingdom
    • Topic: Decision-making under Epistemic Uncertainty for Cooperative Games
  • Yuqi Zhang, PhD student @ HKU (Main supervisor: Prof. Edwin Fong)
    • Previously Masters in Mathematics & Statistics @ University of Oxford, United Kingdom
    • Topic: Uncertainty-aware Causal Inference
  • Xiaotao Liu, Undergraduate Research Student @ NTU
    • Topics: Decision-making under Epistemic Uncertainty

Postdocs/PhD Students closely working with me

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