Personal profile

Research interests

Dr. Yunlei Li studied data mining & bioinformatics at Delft University of Technology (TUD) under the supervision of Prof. Marcel Reinders and Prof. Lodewijk Wessels. She conducted her internship at the Netherlands Cancer Institute (NKI) under the supervision of Prof. Laura van ‘t Veer on breast cancer research. In 2004, she obtained her MSc degree with honor (cum laude). She performed her doctoral research at TUD with Prof. Marcel Reinders and Prof. Dick de Ridder and obtained her PhD in 2010 on “Exploiting noisy and incomplete biological data for prediction and knowledge discovery”. Since 2011, Dr. Li has been working at the Erasmus Medical Center (EMC) on multiple basic cancer research as well as health care-oriented projects covering a wide range of diseases (incl. leukemia, aneurysm, pancreatic cancer, lung cancer, glioblastoma, melanoma) and bioinformatics applications.

 

Currently she is leading the machine learning / artificial intelligence research line in the Department of Pathology & Clinical Bioinformatics at EMC. Her research focus is designing and applying novel artificial intelligence methods (data mining, machine learning, deep learning) in translational and clinical research settings to integrate and exploit multi-dimensional patient data (e.g. DNA, RNA, protein, image, clinical) for clinical cancer research and clinical trials, in order to gain insight of the diseases, discover biomarkers, improve diagnosis accuracies and stratification for personalized treatments.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

PhD, Exploiting noisy and incomplete biological data for prediction and knowledge discovery, Delft University of Technology

Sept 2005Sept 2009

Master, Classification in the presence of class noise, Delft University of Technology

Aug 2002Jul 2004

External positions

PhD researcher, Delft University of Technology

Sept 2005Sept 2009

Keywords

  • TK Electrical engineering. Electronics Nuclear engineering
  • Bioinformatics
  • Machine learning
  • Data mining
  • Artificial Intelligence
  • Deep learning
  • Cancer research

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