EchoNous Hires Two Top Machine Learning Scientists To Accelerate Ongoing Development of Intelligent Medical Tools

Forerunners in natural language processing and deep learning now focused on building transcendent new intelligent medical tools for heart and lung assessment

EchoNous, a developer of intelligent medical tools, announces the hiring of Dipankar Ray, PhD and Allen Lu, PhD – two leading minds in modern machine learning to bolster the 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 world-class 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 world-class 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 a world-class AI team to execute on our ease-of-use mission,” said Niko Pagoulatos PhD, EchoNous COO. “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.”

Dipankar 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% 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, where he led efforts to build a voice-based assistant for doctors.

As a machine learning researcher at Yale University, Allen 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 holds a Bachelor of Science in Electrical Engineering and Mathematical Economic Analysis from Rice University and is completing a PhD 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.”