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Full-Time, Part-Time, Remote
Employement Details
Postdoctoral Researcher
University of Florida
Oct 2020 - Dec 2021
Full-time
I constructed a deep learning pipeline to automate the fruit fly image segmentation using Convolutional neural networks.
The pipeline accurately segments fly photos, improving the phenotyping efficiency by at least 10 folds and solving the inconsistency and subjectiveness of human observers. This tool is now frequently used by our lab and the collaborating labs.I constructed a deep learning pipeline to automate the fruit fly image segmentation using Convolutional neural networks. The pipeline accurately segments fly photos, improving the phenotyping efficiency by at least 10 folds and solving the inconsistency and subjectiveness of human observers. This tool is now frequently used by our lab and the collaborating labs.
Skills: SQL · MySQL · Scikit-Learn · Deep Learning · TensorFlow
Postdoctoral Researcher
UC Irvine
Oct 2019 - Oct 2020
I analyzed the relationship between gene expression and their copy number variation and their distance to Topological Association Domain in several fruit fly species using statistical methods.I analyzed the relationship between gene expression and their copy number variation and their distance to Topological Association Domain in several fruit fly species using statistical methods.
Skills: Data Visualization · Statistics · Bioinformatics · Python (Programming Language) · R (Programming Language)
Software Engineer
DIGIOTAI Solutions
Jan 2023 - Present
Full-time
Remote
I Designed and developed a declarative model for simplifying the configuration and deployment of IoT solutions of potable edge systems.
I also developed a web application for clients to input configs and control the status of their IoT components. The front-end of the application is built with Vue.js, the back-end is built with python, mqtt and influxdb.I Designed and developed a declarative model for simplifying the configuration and deployment of IoT solutions of potable edge systems. I also developed a web application for clients to input configs and control the status of their IoT components. The front-end of the application is built with Vue.js, the back-end is built with python, mqtt and influxdb.
