02 Aug 2023
Can an algorithm help us eat better?
That’s the question I’ll be discussing with my guest today, Professor Eran Segal, a professor at the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science (WIS), heading a lab with computational biologists and experimental scientists who have extensive experience in machine learning and computational biology allowing them to decipher how something as complex as diet, interacts with something infinitely more complex … us.
Our genes, microbes, and unique environments are obviously going to impact how we respond to different foods and diets and Professor Segal is on a mission to figure out how we can use his favouroite tool, algorithms, to help us eat according to our unique biology.
We first dive into our unique blood sugar responses and their seminal paper published in Cell that demonstrated the drastically different responses we all have and potential reasons why.
How we calculate GI and GL index and what’s wrong these, what happens when we have high blood sugar excursions (after a high refined carb meal for example) and the dangers of gameifying our diet too much.
Plus we look into the future with the Human Phenotype Project, the role of faecal transplants and I invite Professor to give us a snapshot of how we practice nutritional self-care in the future with all the ‘omics’.
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Professor in the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science in Israel working on the microbiome, nutrition and genetics, and their effect on health and disease.
A professor at the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science (WIS), heading a lab with a multi-disciplinary team of computational biologists and experimental scientists in the area of computational and systems biology. His group has extensive experience in machine learning, computational biology, and analysis of heterogeneous high-throughput genomic data.
He was elected as an EMBO member and as a member of the young Israeli academy of science. During the COVID-19 pandemic, Segal developed models for analyzing the dynamics of the pandemic and served as an advisor to the government of Israel.
He was elected as an EMBO member and as a member of the young Israeli academy of science. During the COVID-19 pandemic, Segal developed models for analyzing the dynamics of the pandemic and served as an advisor to the government of Israel.
Segal was awarded a B.Sc. in Computer Science summa cum laude from Tel-Aviv University, and a Ph.D. in Computer Science and Genetics, from Stanford University. Before joining the Weizmann Institute, Segal held an independent research position at Rockefeller University, New York.
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