EchoNous Hires Two Top Machine Learning Scientists

EchoNous, a developer of intelligent medical tools, has hired Dipankar Ray, Ph.D., and Allen Lu, Ph.D.— two leading minds in modern machine learning to bolster execution of the company’s mission to solve everyday problems in healthcare through converging artificial intelligence (AI) methods and extreme ultrasound miniaturization. The addition of Ray and Lu continues EchoNous’ build-out of a team of AI engineers to complement the company’s existing expertise in the development of highly miniaturized medical ultrasound technologies.
 
“For ultrasound to fulfill its potential and become the ubiquitous tool in medicine that it deserves to be, we need to solve for two elements: access and ease-of-use. We have been building our team around these two pillars. Having already built a team in extreme ultrasound miniaturization to execute on our mission of ultimate access to high-performance ultrasound-based clinical tools, we are now intensifying our efforts on building an AI team to execute on our ease-of-use mission,” said Niko Pagoulatos Ph.D., EchoNous chief operating officer. “Modern AI methods based on machine learning, such as deep learning, can revolutionize ease-of-use in ultrasound and dramatically reduce the learning curves associated with clinicians being able to routinely and confidently use ultrasound to solve common everyday problems in healthcare. We are excited to have Dipankar and Allen join us in our mission of taking ease-of-use in ultrasound to unprecedented levels and allowing for its ubiquitous use in medicine.”
 
Ray has more than 10 years of industry experience in building Machine Learning and Natural Language Processing (ML/NLP) systems, primarily working on semantic understanding of text. At Microsoft, he was a senior applied scientist in Bing Ads, where he was a key member of the core team that helped drive Bing to profitability including as much as 40 percent year-over-year growth from 2012 to 2016. Most recently, he was vice president of ML/NLP at Saykara, a Madrona Venture Group-funded startup in Seattle, Wash., where he led efforts to build a voice-based assistant for doctors.
 
As a machine learning researcher at Yale University, Lu developed deep learning-based methods for automated cardiac motion analysis algorithms based on 3D ultrasound images while under the tutelage of Dr. James Duncan, a renowned expert in the analysis of biomedical imaging. Previously, while at IBM’s Almaden Research Center in support of the company’s Watson Health Imaging project, he developed AI algorithms designed to detect cardiac abnormalities. Allen has a bachelor of science degree in electrical engineering and mathematical economic analysis from Rice University and is completing a Ph.D. in biomedical engineering at Yale.
 
“Having spent more than a decade as a key engineer for one of the global leaders in machine learning, Dipankar brings a unique AI skill set, including natural language processing, that will help us enable bold new possibilities in frictionless usability and clinical expansion with ultrasound technologies,” said EchoNous CEO Kevin Goodwin. “Allen combines a career in breakthrough research in cardiac imaging and the development of machine learning algorithms to bring a highly specialized and unmatched knowledge base to our team.”
 

Headquartered in Seattle, EchoNous, a KKR portfolio company and parent company of Signostics, is developing an expanding family of intelligent medical tools to help healthcare professionals solve common everyday problems in healthcare. Beginning with the soon to be released EchoNous Vein vascular access tool (pending U.S. Food and Drug Administration approval) and the Uscan intelligent bladder scanner, EchoNous is applying a layer of artificial intelligence methods with the extreme miniaturized ultrasound technology to provide nurses, doctors and clinicians with high-quality, easy-to-use tools simplifying the task at hand. Goodwin and Pagoulatos direct the company based on decades of successful experience and new category creation in the ultrasound industry.