How AI is Transforming Healthcare

As many industries are just now learning about AI and its potential, healthcare has been on the frontlines for some time, using it to solve critical problems impacting humanity at large. Three startups – Athelas , Bay Labs, and Genetesis -- are leading the way, illuminating how deep learning, the fastest growing segment of AI, can accelerate medical progress at an unprecedented rate.

Watch this replay to gain insight on how todays innovators are applying groundbreaking AI technology, and revolutionizing the healthcare industry.
  1. Hear from the CEO of Athelas, which uses computer vision and deep learning algorithms to create a machine to identify white blood cell count, the key to detecting infections, leukemia and other problems.
  2. Learn how Genetesis is building biomagnetic solutions that allow physicians to detect and localize sources of abnormality in the heart to revolutionize triage in the emergency department.
  3. Understand how today’s enterprises, inside or outside the healthcare industry, can partner with startups to leverage the power of deep learning and solve business challenges.
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Presented By
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Tanay Tandon
CEO, Co-Founder Athelas

Tanay Tandon is co-founder and CEO of Athelas, a biotechnology company based in Mountain View, CA. He began work in machine learning as a high schooler in Richard Socher’s Stanford AI lab team with research in image processing and natural language processing, eventually working with many groups within the lab. Before attending Stanford University, his paper on deep learning for malaria classification was selected as an Intel STS Finalist, and his work on ‘Clipped’ - a natural language processing engine for summarization using RNNs - was briefly one of the most-used mobile news readers in the world. Tandon is the youngest founder to ever be backed by Sequoia Capital, and is excited to be working with the whole Athelas team to bring lab-grade medical systems to consumers.
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Raj Muchhala
Machine Learning Engineer, Genetesis

Raj Muchhala is a Machine Learning Engineer leading the AI and deep learning research at Genetesis, a clinical stage medical device company solving the problem of chest pain triage. His current interests include AI, machine learning and healthcare. He received his Bachelors degree in Electronics engineering from Mumbai, India in 2014 and got his Masters degree in Computer engineering, with a focus in Machine Learning and Artificial Intelligence, from Rochester Institute of Technology in 2016. After graduation, he joined a seed stage fashion startup as an intern and helped them build a visual search engine app for fashion using deep learning. Currently, Raj is living in Cincinnati, Ohio.
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Nina Miolane
Ph.D - Machine Learning Engineer, Bay Labs

Nina graduated from her Ph.D in Mathematics for Computational Medicine from Inria & Stanford University in 2016 and joined Bay Labs' Machine Learning team early 2017. She works, in collaboration with other Bay Labs engineers, on Deep Learning pipelines to automatically assess cardiac function from Echography. Bay Labs' goal is to make diagnosis and medical imaging universally accessible to improve healthcare.
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Abdul Hamid Al Halabi
WW Business Development Lead, Healthcare and Life Sciences, NVIDIA

Abdul Hamid Al Halabi is responsible for helping drive NVIDIA’s growth and innovation strategies across the healthcare ecosystem. With nearly 20 years of experience in advanced technologies, he partners with thought leaders and world-class organizations to transform healthcare through the application of deep learning and high performance computing to enable precision medicine initiatives and evidence-based medicine. Prior to this role, Abdul previously served in leadership positions as senior physical design engineer and VLSI project lead for NVIDIA.

An accomplished speaker, Abdul earned his Bachelor’s degree in computer engineering from the University of Toronto, and an MBA degree from Texas A&M University-Commerce. Additionally, he holds a Master’s degree in management science and engineering from Stanford University, where he is currently a Ph.D. candidate.