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National Cancer Institute Employee Reviews for Visiting Fellow

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5.0
Average Rating
(based on 1 Visiting Fellow Review Rating)
Visiting Fellow
in Bethesda, MD

"software development. Over the past 5~6 years, I have dedicated a considerable amount of time and effort to develop computeraided design and software to help people in other area. During my PhD and undergraduate study, I have taken a number of statistics and software course, and I possess strong data analysis, image understanding, and software techniques. I am currently a visiting fellow in the laboratories at NCI/NIH, where I use my machine learning and software background to help biologistst of indn ovelc ell-biologicalm echanisms. As theo nlyc omputer-relatedm ajorr esearcherh ere,I h avep rimarilyd eveloped image analysis software by using a state of art image understanding/machine learning background such as Mask R-CNN, UNET by using Python-Tensorflow/Keras/OpenCV and KNIME framework. I am helping biologists on the experimental set-up and to assist and help them in every phase of the automated imaging workflow. This work includes: • Develop and implement image analysis/deep learning workflows for biological/medical image applications. • Develop machine learning software on high-performance multiple NVIDIA CUDA-support GPUs. (e.g., the number of GPUs: 16~24 NVIDIA K40 GPUs) (Python-Tensorflow) • Data analysis and statistical understanding of medical/biological dataset. • Software and pipeline development of the application of image bioinformatics. • Work closely with doctors/biologists. As a former PhD graduate student and postdoctoral fellow under the guidance of Professor Shuvra S. Bhattacharyya and Professor Rong Chen at University of Maryland (area: PhD: Computer Engineering, postdoc: University of Maryland Medical Center), I primarily focused on the development of machine learning software system frameworks for detecting people and vehicles by data fusing from a multimodal, unattended sensor node. This research includes: • Machine learning model implementations (e.g., CNN, DNN, SVM, and Mask R-CNN) for target classification, detection, and analysis. (MATLAB"

Person You Work For 5 / 5 People You Work With 5 / 5 Work Setting 5 / 5
Support You Get 5 / 5 Rewards You Receive 5 / 5 Growth Opportunities 5 / 5
Company Culture 5 / 5 Way You Work 5 / 5
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