Zhiliang Wu | 吴志良

LMU Munich. Siemens AG.

Munich, Germany

I am a Ph.D. student under the supervision of Prof. Volker Tresp since 2018. The work is generously supported by the MLwin project at LMU Munich and Siemens AG.

My research focuses on machine learning and deep learning in healthcare applications. We are especially interested in developing state-of-the-art clinical decision support systems to address the challenges in the high-dimensional, sparse, and sequential Electronic Health Record (EHR) data.

Before joining LMU Munich & Siemens AG, I received my master’s degree in Electrical Engineering and Information Technology from the Technical University of Munich in 2018. I spent six months at Mercateo AG to conduct my master’s thesis about Recommender Systems under the supervision of PD. Martin Kleinsteuber.

news

Jun 5, 2021 Our paper about uncertainty-aware Time-to-event Prediction is accepted to MLHC 2021!
May 1, 2021 Our paper about Deep Kernel Learning on medical imaging data got accepted to ICHI 2021!
Dec 1, 2020 Our paper received the best paper award at the ICHI 2020!
Nov 30, 2020 My first collaboration work with Jindong was presented at ACCV2020!
Jun 10, 2019 My first collaboration work with Yinchong and Volker got published at ICHI 2019!
Nov 1, 2018 I started my Ph.D.!!!

selected publications

  1. ICHI2020
    Best Paper Award
    Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score
    In 2020 IEEE International Conference on Healthcare Informatics (ICHI) 2020
  2. ICHI2021
    Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning
    In 2021 IEEE International Conference on Healthcare Informatics (ICHI) 2021
  3. MLHC2021
    Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models
    In Machine Learning for Healthcare Conference 2021