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Education

• University of Washington, 2021 (expected)
  • Ph.D in Biomedical Informatics
• Georgia Institute of Technology, 2017
  • B.S. in Biomedical Engineering (cum laude)
  • Minor in Computing and Intelligence

Publications

• 11C-PIB PET Image Analysis for Automated Alzheimer’s Diagnosis Using Weighted Voting Ensembles
  Wenjun Wu, Janani Venugopalan, May D. Wang.
  Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017. [Slides]
• The Advantages of Viscous Dissipation Rate over Simplified Power Loss as a Fontan Hemodynamic Metric
  Zhenglun Alan Wei, Michael Tree, Phillip M Trusty, Wenjun Wu, Shelly Singh-Gryzbon, Ajit Yoganathan
  Annals of biomedical engineering (2017): 1-13.

Research Experience

• [Sept 2017–Current] UW Graphics and Imaging Laboratory, UW
  Advisor: Linda Shapiro
  • {Applying \textbf{transfer learning}, multi-scale fusion CNN and generative Adversarial Networks (GAN) for ISIC 2018 Data Challenge of skin lesion diagnosis.
  • Used CNN and Adaboost classifier to detect cellular-level entities (e.g. nuclei, melanocytes and etc.) and structural entities (e.g. mid-level features like melanocyte bridges, etc.) in digitized whole slide images of melanocytic skin lesions.
  • Developing an automated diagnosis system from structural and cellular-level entities that can classify digitized slide images into one of five possible diagnostic classes: atypical lesions; melanoma in situ; invasive melanoma stage T1a; and invasive melanoma stage $\geq$T1b.
• The Bio-Medical Informatics and Bio-Imaging Laboratory, Georgia Tech
  Advisor: May Wang
  • Extracted 3D image features from processed PET images; applied weighted and unweighted voting ensembles of baseline classifiers to classify PET images into categories that correspond to diagnosis of Alzheimer’s disease. The paper was accepted to EMBC 2017.
• The Cardiovascular Fluid Mechanics Lab (CFM Lab), Georgia Tech
  Advisor: Zhenglun Wei and Ajit Yoganathan
  • Performed computational fluid dynamics simulations using ANSYS Fluent (ANSYS, PA) on pre-surgery and post-surgery patient under both time-averaged and pulsatile boundary conditions; evaluated flow efficiency using simplified power loss or a viscous dissipation rate metric. The paper was accepted to Annals of Biomedical Engineering.

Internship

• Siemens Corporate Research, Graduate Research Intern [June 2018 - Sept 2018]
  

  Applied reinforcement learning to automate manufacturing process.

Teaching Experience

• Teaching Assistant, Data Sturctures and Algorithms. Instructor: Evan McCarty.
• (Current) Teaching Assistant, Data Sturctures and Algorithms. Instructor: Michael Lee.

Projects

• Language Identication using RNN [Jan 2018 - Mar 2018]
  Using RNN to Identify the language of the written text taken from Twitter, written in nine European languages: English, Spanish, Portuguese, Galician, Basque, Catalan, French, Italian and German.
• AirTech - iOS application for lung function monitoring [ Jan 2017 - May 2017]
  Developed a lung function monitoring device for chronic lung disease patients that quantifies air flow rate and exhaled gas components, conducts test validity check, and automatically records test results to compatible iOS application.
  [ Code ] [Demo]
• Cancer Stage Diagnosis using Biomedical Image processing [ Jan 2016 - May 2016]
  Developed supervised and unsupervised segmentation of cellular structures using classification algorithms; extracted various types of features and adopted multiple dimensionality reduction methods; used extracted features to build various classifiers for diagnosing cancer stage from breast biopsy histological images and achieved F1 score of about 0.9.
  [Demo]
• Robotics [ Jan 2016 - May 2016]
  Programmed a scribbler robot to perform task in image processing (exploration of surrounding areas using image stitching) and in navigation (obstacle identification, path planning and robot localization).
• PTT Advisor+ [May 2016 - Sept 2016]
  Collaborated with CDC (Centers for Disease Control and Prevention) and administered the implementation and design of iOS mobile app to provide guidance for physicians to prescribe anticoagulant drug and test.
  [App Store link]

Skills

Programming: Python, C/C++, Java, MATLAB, R
Engineering: Signal Processing, Image Processing (MRI, PET and Histopathology Images), Statistics, Fluid mechanics
Software/Tools: OpenCV, NLTK, BrainSuite, SPM12 Toolbox, Free Surfer, FSL, xcode, ANSYS Workbench Fluent, LABVIEW, Solidworks, STAR CCM+, Paraview, SPSS, Excel, Microsoft Suite