Dr. Kira Radinsky is the chairperson and CTO of Diagnostic Robotics, where the most advanced technologies in the field of artificial intelligence are harnessed to make healthcare better, cheaper, and more widely available. Dr. Radinsky has founded SalesPredict, acquired by eBay in 2016 and served as eBay Chief Scientist (IL). She gained international recognition for her work at the Technion and Microsoft Research for developing predictive algorithms that recognized the early warning signs of globally impactful events, as disease epidemics and political unrests. In 2013, she was named one of MIT Technology Review’s 35 Young Innovators Under 35 and in 2015 Forbes included her as “30 Under 30 Rising Stars in Enterprise Tech”. She is a frequent presenter at global tech and industry conferences, including TEDx, Wired, Strata Data Science, Techcrunch and publishes in HBR. Radinsky also serves as a board member in Israel Securities Authority and technology board of HSBC bank. She also holds a visiting professor position at the Technion focusing on the application of predictive data mining in medicine.
November 17, 2020 04:00 PM PT
Dr. Kira Radinsky
Chairwoman & CTO , Diagnostic Robotics
How do we predict future events, such as pandemics, and also make personalized predictions in healthcare?
Dr. Radinsky talks about gathering data on 150 years of news articles, billions of tweets and millions of web searches and using that data to extract causality. She then combines this data with correlation infrastructure to predict events like a Cholera outbreak in Cuba.
While this method has been successful at preparing for disaster, Kira has more recently focused on automated triaging in the primary care system for standard medical conditions, until COVID-19 broke out. Her work now focuses on predicting COVID-19 in certain geographies and flattening the curve by increasing the supply of testing services in those areas.
CEO, 3DR, Founder DIYRobocars and DIYDrones
For a century the car industry has used racing to drive innovation. But with self-driving cars, it's not happening. Companies are more concerned about embarrassing and expensive failures than speed and nimbleness, so much so that the biggest risk of robocars on the roads is slowing and blocking traffic. Fortunately, we don't have to wait for the big robocar makers to put their pedal to the metal -- we can do it ourselves. Ten years ago, I helped kickstart the modern drone industry by adding the letters "DIY" to what was until then the sole domain of governments and aerospace companies, and today we have millions of DIY drones in the air. Now the same thing is happening with autonomous cars, where for less than $400 you can make your own small autonomous car that uses the same kinds of sensors and AI code as the full-size one, but can be used safely indoors.
In this talk I'll talk about how DIY Robocars cars and races work, including edge AI, simulation, computer vision and various deep learning training techniques that have allowed us to beat the fastest humans at this scale.