Data Science and Machine Learning Researcher at Scripps Institute of Oceanography - La Jolla, California, with experience developing convolutional neural network (CNN)-based automated imaging systems and analyzing large-…
Data Science and Machine Learning Researcher at Scripps Institute of Oceanography - La Jolla, California, with experience developing convolutional neural network (CNN)-based automated imaging systems and analyzing large-scale plankton image datasets. Previously a Data Science Intern at the Statistical Visual Computing Lab UC San Diego, building full-stack tools and data visualization solutions using SQL and web technologies. Holds a B.S. in Data Science from the University of California San Diego and is pursuing an M.S. in Computer Science at the University of California San Diego.
Developed automated imaging systems that use underwater microscopic cameras and convolutional neural networks (CNN) to foresee upcoming algae blooms that are harmful to the marine ecosystem.
Analyzed over 41000 images of plankton to provide robust quantification of the uncertainty range in the measurements and counts provided by the Scripps Plankton Camera System.
Achieved an average 90% accuracy on the CNN classifier, with above 90% correlation and low counting errors when compared to the traditionally established methods.
Developed automated imaging systems that use underwater microscopic cameras and convolutional neural networks (CNN) to foresee upcoming algae blooms that are harmful to the marine ecosystem.
Analyzed over 41000 images of plankton to provide robust quantification of the uncertainty range in the measurements and counts provided by the Scripps Plankton Camera System.
Achieved an average 90% accuracy on the CNN classifier, with above 90% correlation and low counting errors when compared to the traditionally established methods.
Engineered an online annotation tool through full stack development using React and Node.js for oceanographers from Scripps Institute of Oceanography to study marine plankton in real time.
Using SQL, queried over 6 years of daily updated counts and appearances data from the Scripps database, for 9 specific species of oceanic microorganisms.
Analyzed queried data for relevant temporal patterns and seasonal trends, and developed a data visualization website to showcase findings to the researchers.
Engineered an online annotation tool through full stack development using React and Node.js for oceanographers from Scripps Institute of Oceanography to study marine plankton in real time.
Using SQL, queried over 6 years of daily updated counts and appearances data from the Scripps database, for 9 specific species of oceanic microorganisms.
Analyzed queried data for relevant temporal patterns and seasonal trends, and developed a data visualization website to showcase findings to the researchers.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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