About Melanie

Melanie is a coder at heart and a dedicated data engineering professional.
She was also a member of the Data Science Research Lab during her graduate studies in computer science.

Interests

• Javascript and Golang
• Scientific computing with Python (Numpy, Scipy, Pandas, Scikit-learn, Tensorflow)
• ETL stuff, Data science, applied machine learning, A.I., and big data analytics
• Working on unstructured data on distributed systems



Publications

• M. Kwon, M. Kuko, V. Martin, T. H. Kim, S. E. Martin, M. Pourhomayoun, “Multi-label Classification of Single and Clustered Cervical Cells Using Deep Convolutional Networks,” The 14th Int. Conference on Data Science (ICDATA’18), 2018. [Link to paper]



Research Projects

1. Applied Deep Learning for Computer-Aided Diagnosis of Cervical Cytology:
   • In partnership with pathologists of Los Angeles County + USC/Keck Hospital of USC, we aim to explore how the diagnostic performance of convolutional neural networks can be compared to the human-level expertise of licensed pathologists.
   
   

   Mohammad Pourhomayoun, Ph.D.	Principal Investigator
   Sue Ellen Martin, MD, Ph.D.	Principal Investigator
   Melanie Kwon, MSCS	Research Project Manager
   Vanessa Martin, MD	Co-Investigator
   Tae Hun Kim, MD	Co-Investigator
   Adam Berman, MSCS	Co-Investigator




“Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning stays young.” – Henry Ford




“Either write something worth reading or do something worth writing.”
– Benjamin Franklin