Ramkumar Hariharan, PhD is head of applied AI at Macro-Eyes, Inc. A science educator, computational biologist, and data scientist, he has led several successful biomedical and health care projects at world-renowned medical research institutions. He was team leader for multiple vaccine supply chain projects at Macro-Eyes, working closely with the Bill and Melinda Gates Foundation. Ram has worked as a principal data scientist at the Fred Hutchinson Cancer Research Center in Seattle and, as a research scientist at the Institute for Systems Biology in Seattle (where he worked with legendary geneticist Lee Hood). His areas of focus include all aspects of human longevity, advanced statistical data analyses, data visualization, and machine learning.
He has also focused on data-driven genomic investigations at the University of Oxford, UK, and at RIKEN, Japan where he was visiting scientist.
Ram originally started out as computational biology faculty at the Rajiv Gandhi Centre for Biotechnology, Trivandrum, a federal institute in India and has a PhD in the subject.
Ram’s honors and awards include being the only British Council Researcher Exchange Program award winner in 2007 from India, Young Scientist Award from the Government of India, University Gold Medalist for his Master’s, invited external grants reviewer for the Governments of Poland and Hong Kong. Ram has also been heavily involved in popularizing science on Television and National Radio in India, been a freelance science columnist for The Hindu, India’s National Daily. He has also won prizes for TV advertisement copywriting (English).
- PhD, Computational biology statistical modeling and simulation of biophysical data, machine learning, University of Kerala, Kerala, India, 2008
Aug 12, 2022
Ram Hariharan, an associate teaching professor and associate director of program management in Seattle, is using deep learning techniques to sift through a ton of medical data to find which are the most effective cancer treatments based on a person’s specific health. How deep learning is transforming the way we treat cancer patients Main Photo: […]