Yuankai Huo
Jul. 21, 2025—91³Ô¹ÏÍø researchers have received a $1.2 million grant from the National Science Foundation to develop a smart microscope system that uses artificial intelligence to help scientists better understand how cells behave, particularly in diseases like cancer.
May. 7, 2024—91³Ô¹ÏÍø has created a transformational lab focused on leveraging immersive translational AI to drive discovery across disciplines ranging from medicine and materials science to the humanities, social science and education. Five VISE faculty affiliates will serve on the steering committee.
Jan. 10, 2024—A front-end lens, or meta-imager (see below), created at 91³Ô¹ÏÍø can potentially replace traditional imaging optics in machine-vision applications, producing images at higher speed and using less power.
VISE on the Road: 2023 MICCAI conference
Nov. 21, 2023— Members of six VISE labs affiliated with the 91³Ô¹ÏÍø Institute for Surgery and Engineering (VISE) traveled to Vancouver to take part in the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention. Like-minded scientists from around the world gather yearly at the MICCAI conference to share their work with one another on a...
Sep. 13, 2023—A $350,000 grant to develop next-generation archaeological mapping technology will let a 91³Ô¹ÏÍø-led research team reveal information about vast settlement systems and human-modified landscapes in the Andes.archaeology
Apr. 18, 2023—New applications of artificial intelligence (AI) to renal pathology have been driven by the widespread use of digital diagnostic imaging and interdisciplinary collaborations between computer scientists, nephrologists and renal pathologists with potential for major impacts in diagnosis and understanding of kidney diseases.
Apr. 13, 2022—The Scaling Success Grant supports faculty as they leverage their research into larger, more competitive awards from federal, foundation or industry sponsors.
Jun. 19, 2018—Abdominal ultrasound tests for organ abnormalities haven’t changed much in the past decade, with a doctor moving a wand over the patient’s abdomen to gaze at blurry images. But the process could get accelerated by a thousand times with improved accuracy, based on deep learning work by U.S. researchers.