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Dorsa Ziaei completed her Ph.D. program in Computer Science at the University of Maryland Baltimore County (UMBC) in 2020, with a focus on designing scalable and distributed deep
learning frameworks to process large high-resolution images. She received her BS and MS degrees in Computer Science major. Currently, she is working as a computational scientist II at Frederick National Laboratory for Cancer Research, NCI / NIH.
Research interests:
Data Science, Data Mining, Computer Vision, Applied Machine Learning, Deep Learning,
Scalable Deep Learning, Distributed Training, Timeseries Forecasting, Predictive Modeling
Awards:
- ORISE Fellow at Food and Drug Administration (FDA) for the project: Characterization of color normalization methods in digital pathology whole slide imaging
- Winner of SPIE Medical Imaging 2020, Best Paper Poster Award, Image Processing Conference, for “Segmentation of stem cell colonies in fluorescence microscopy images with transfer learning”
- NSF XSEDE Resource Award (2019) for “Machine Learning for very Large High-Resolution Images”, Access to Pittsburgh Supercomputing Center AI-GPU cluster with nine nodes each with 8 V100 GPUs
- Winner of F1000 Award: Outstanding Presentation Prize, “NYC Symposium: Deep Learning for Drug Discovery” for the project “Assessment of Deep Convolutional Neural Networks: Segmentation of Large High-Resolution Stem Cell Images”
Papers:
https://scholar.google.com/citations?user=874dtisAAAAJ&hl=en |
