Saeed Hassanpour, PhD, an assistant professor of biomedical data science and of epidemiology at Dartmouth’s Geisel School of Medicine, and of computer science at Dartmouth College, has received the 2019 Agilent Early Career Professor Award.
The award was created by Agilent Technologies, which focuses on analytical and diagnostic measurements, to promote and encourage research that advances important measurement technologies, and to establish strong, collaborative relationships between its researchers and leading professors early in their careers.
“I’m very humbled and excited about receiving this award because, first of all, it’s a recognition of our work here at Dartmouth,” says Hassanpour, whose application was chosen over hundreds of nominees and four other finalists— from Harvard, University of Michigan, Duke, and Weill Cornell. “And to actually be recognized as the winner over such an outstanding group of researchers is a great honor.”
With this year’s special focus on “Contributions to the development of breakthrough artificial intelligence (AI) solutions advancing cancer diagnostics based on image analysis of pathology slides,” Hassanpour has received an unrestricted research award of $100,000, based on “the quality, originality, and impact of his work and its alignment with the future measurement needs of Agilent and the world.”
“This will provide an opportunity to expand the AI research that we are doing in this domain to develop and evaluate new machine learning models for pathology image analysis and improving cancer care for patients,” says Hassanpour, whose current research explores the use of deep-learning technology to classify colorectal polyps and several subtypes of cancer on whole-slide microscopy images. “Being able to collaborate with researchers at one of the leaders in the field, in Agilent, will be great for our group, our research, and Dartmouth in general.
“It is a privilege to work with a brilliant group of colleagues, clinicians, and students at Dartmouth,” he says. “These collaborations and the great support from Norris Cotton Cancer Center, the pathology department, and my home departments fueled the research that led to this recognition.”
Since 2015, the Hassanpour Lab has been focused on developing computational methods and tools for extracting and organizing clinically meaningful information from a wide range of biomedical data. Broadly, its areas of emphasis include medical image understanding, natural language processing and machine learning for precision medicine, and digital health for behavioral interventions.
Prior to joining Dartmouth, Hassanpour worked as a research engineer at Microsoft in Mountain View, CA, where his research yielded multiple patents involving machine learning that have been incorporated into the company’s computing platforms for large-scale use. Earlier, during his doctoral and postdoctoral training at Stanford University Schools of Engineering and Medicine, he developed new machine-learning and data-driven models for biomedical applications. Altogether, his innovative work has been published in numerous clinical and informatics journals and has resulted in multiple honors and awards.
Hassanpour received his PhD in electrical engineering and biomedical informatics from Stanford University in 2012, his Master of Computer Science from the University of Waterloo in Canada in 2007, and his Bachelor of Science in computer engineering from Sharif University of Technology in Tehran, Iran in 2006.