George Tasdjian
About George Tasdjian
George Tasdjian is a Senior Machine Learning Scientist at Cofactor Genomics, where he has worked since 2018. He holds a PhD in Biomedical/Medical Engineering from the University of California, Berkeley, and an MS in Bioengineering and Biomedical Engineering from the University of California, San Diego.
Work at Cofactor Genomics
George Tasdjian has been employed at Cofactor Genomics as a Senior Machine Learning Scientist since 2018. In this role, he focuses on applying machine learning techniques to genomic data, contributing to advancements in precision medicine. His work involves developing algorithms that enhance the understanding of genetic information and its implications for health and disease.
Education and Expertise
George Tasdjian holds a Doctor of Philosophy (PhD) in Biomedical/Medical Engineering from the University of California, Berkeley. He also earned a Master of Science (MS) in Bioengineering and Biomedical Engineering from the University of California San Diego. His educational background provides a strong foundation in both engineering principles and biological sciences, equipping him with the skills necessary for his research and development work in machine learning.
Background
George Tasdjian has a robust academic background in engineering and biomedical fields. His studies at prestigious institutions such as UC Berkeley and UC San Diego have shaped his understanding of complex biological systems and the application of computational methods in healthcare. This background supports his current role in the rapidly evolving field of genomics.
Achievements
In his position at Cofactor Genomics, George Tasdjian has contributed to significant projects that leverage machine learning for genomic analysis. His expertise in biomedical engineering and machine learning has positioned him as a key player in initiatives aimed at improving genomic data interpretation and its applications in personalized medicine.