BIOGRAPHY
Daniel Vasilaky is a biomedical informatics specialist with a robust background in machine learning and neural networks. He earned his PhD in Biomedical Informatics from Rutgers University between 2008 and 2013, focusing his research on the application of machine learning techniques to medical imaging. His dissertation, titled “An Associative Memory Applied to Analysis of CT Images,” explored the development of neural network models for interpreting computed tomography scans, contributing to advancements in medical diagnostics.
Throughout his academic and professional journey, Daniel has demonstrated proficiency in a wide array of programming languages and tools essential for data analysis and system development. His technical expertise includes C++, Java, XML, R, PHP, Python, SQL, TensorFlow, Perl scripting, MatLab, and Linux administration. This diverse skill set has enabled him to engage in complex problem-solving and develop innovative solutions in the field of biomedical informatics.
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Showcases qualifications, expertise, credibility, career path, and skills.
Education
Showcases qualifications, expertise, credibility, career path, and skills.