Safiye Celik

  Address: Paul G. Allen Center for Computer Science & Engineering Box 352350 185 Stevens Way Seattle, WA 98195-2350
  Email: safiye [at]

  Curriculum Vitae: [pdf]

I am a 6th-year Ph.D. student and Ph.D. candidate in Computer Science and Engineering at the University of Washington. I feel very lucky to be supervised by Prof. Su-In Lee. I received my most recent MS degree in Computer Science and Engineering in February 2014 from the University of Washington under the supervision of Prof. Su-In Lee. I got my previous MS degree in Computer Engineering in September 2012 from Bogazici University under the supervision of Prof. Ali Taylan Cemgil. I received my Bachelor's degree in Computer Engineering from Middle East Technical University.

I am interested in developing statistical machine learning algorithms which aim to address the problem of high-dimensionality in systems biology applications. Those include identifying expression features that are conserved across multiple independent gene expression datasets and are likely to represent important molecular events underlying the cancer; and identifying robust biomarkers that can predict sensitivity of cancer patients to different chemotherapy drugs, with the long-term goal of introducing a promising way for personalized therapy. In my PhD thesis, I am proposing to develop a novel network learning framework to discover important molecular events in Alzheimer's disease progression.


  • Su-In Lee*, Safiye Celik*, Benjamin A Logsdon, Scott M. Lundberg, Timothy J Martins, Vivian G Oehler, Elihu H Estey, Chris P Miller, Sylvia Chien, Akanksha Saxena, Anthony Blau and Pamela S Becker. A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia. Nature Communications 2018 Jan 3;9(42) (* means equal contribution). [paper link] [project website]

  • Safiye Celik, Benjamin A Logsdon, Stephanie Battle, Charles W Drescher, Mara Rendi, David Hawkins and Su-In Lee. Extracting a low-dimensional description of multiple gene expression datasets reveals a potential driver for tumor-associated stroma in ovarian cancer. Genome Medicine 2016 Jun 10;8(1):66. [paper link] [project website]
  • Safiye Celik, Benjamin A Logsdon and Su-In Lee. Efficient Dimensionality Reduction for High-Dimensional Network Estimation. 2014 International Conference on Machine Learning (ICML2014), Beijing, China. [pdf] [supplement] [project website]

  • Safiye Celik, Benjamin A Logsdon and Su-In Lee. Sparse Estimation of Module Gaussian Graphical Models with Applications to Cancer Systems Biology. 2013 NIPS Workshop on Machine Learning in Computational Biology (MLCB2013), Lake Tahoe, NV. [pdf]

    Professional Experience

    Between December 2010 and August 2012, I worked as a researcher at the Scientific and Technological Research Council of Turkey (TUBITAK), where I worked on the design and development of novel efficient data mining and pattern recognition algorithms to be applied on massive spatio-temporal datasets.

    Between March 2007 and April 2010, I worked as a software engineer at MilSOFT Software Technologies Inc.. At MilSOFT, I worked for the Turkish Unmanned Air Vehicle (UAV) project where I developed image processing tools to work on the data retrieved from various types of cameras located on the UAV. I also developed a compiler/parser for NATO Message Handling System for Search and Rescue ship communication tasks.