{"693612":{"#nid":"693612","#data":{"type":"news","title":"New Faculty Joins Tech to Advance Medicine and Science through AI","body":[{"value":"\u003Cp\u003EAs doctors increasingly rely on computational approaches to examine and treat patients, Georgia Tech is building its expertise at the intersection of healthcare, computer vision, and artificial intelligence (AI).\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/pwang.pw\/\u0022\u003EJiayun (Peter) Wang\u003C\/a\u003E began his tenure-track career on Oct. 15 as an assistant professor in the School of Computational Science and Engineering (\u003Ca href=\u0022https:\/\/cse.gatech.edu\/\u0022\u003ECSE\u003C\/a\u003E).\u003C\/p\u003E\u003Cp\u003EAt Georgia Tech, Wang will develop new AI tools to help doctors make better use of complex medical data. His research aims to transform information from medical images, clinical measurements, and patient records into clearer insights that improve diagnosis, treatment, and patient care.\u003C\/p\u003E\u003Cp\u003E\u201cI\u2019m excited to build a lab at Georgia Tech, and to work with students and collaborators on new ideas,\u201d Wang said. \u201cI hope our research can connect fundamental advances in AI with real challenges in healthcare and science.\u201d\u003C\/p\u003E\u003Cp\u003EBefore starting at Georgia Tech, Wang conducted postdoctoral research at Caltech and worked as a senior research scientist at Accenture. He earned his Ph.D. in 2023 from the University of California, Berkeley.\u003C\/p\u003E\u003Cp\u003EMuch of Wang\u2019s healthcare research builds on computer vision, which enables machines to interpret images and videos.\u003C\/p\u003E\u003Cp\u003EFor example, lung ultrasound is a fast, portable, and radiation-free way to check breathing problems. However, a drawback is that images can be hard to read.\u003C\/p\u003E\u003Cp\u003EWang led the development of\u0026nbsp;\u003Ca href=\u0022https:\/\/pwang.pw\/lungNO\/\u0022\u003ELUNA\u003C\/a\u003E, an AI method that converts raw ultrasound signals into maps showing how air is distributed in the lungs. This approach makes bedside lung exams more consistent and easier to interpret.\u003C\/p\u003E\u003Cp\u003EWang has also used AI to improve another common type of medical imaging: MRI.\u003C\/p\u003E\u003Cp\u003EMRI scans can take time to complete, and analyzing the results can take even longer. Patients may find it uncomfortable to lie still in a scanner and waiting for results can add stress during an already difficult time. Long scans and reviews can also make it harder for doctors to schedule procedures and consult specialists.\u003C\/p\u003E\u003Cp\u003ETo overcome this shortfall, Wang worked on a team that built a\u0026nbsp;\u003Ca href=\u0022https:\/\/arxiv.org\/abs\/2410.16290\u0022\u003Esingle, flexible AI model\u003C\/a\u003E that reconstructs high-quality MRI images from fewer measurements across different scanning settings. Along with enabling faster scans, the approach preserves the details doctors need to make informed decisions.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ESurgeon training is another way Wang has helped doctors using computer vision techniques.\u003C\/p\u003E\u003Cp\u003EDuring robot-assisted surgery, trainees receive guidance from experienced surgeons. However, it is difficult to know what advice improves techniques. A\u0026nbsp;\u003Ca href=\u0022https:\/\/proceedings.mlr.press\/v259\/gupta25a.html\u0022\u003Esurgical-training study\u003C\/a\u003E that Wang co-authored combined video and spoken feedback to assess trainee learning.\u003C\/p\u003E\u003Cp\u003EWang has used less serious clinical conditions to improve quality of life through AI. Dry eye is one of the most common reasons people visit eye clinics, yet the condition is difficult to assess.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EWorking with collaborators at UC Berkeley, Wang studied AI methods to analyze patient information alongside images of tiny glands in the eyelids. This work contributed to AI tools that assist in \u003Ca href=\u0022https:\/\/arxiv.org\/abs\/2410.00292\u0022\u003Ediagnosing ocular surface diseases\u003C\/a\u003E and\u0026nbsp;\u003Ca href=\u0022https:\/\/www.nature.com\/articles\/s41598-025-96778-x\u0022\u003Epredicting dry eye onset based on lifestyle factors\u003C\/a\u003E.\u003C\/p\u003E\u003Cp\u003EBeyond healthcare, Wang also works to make AI easier to train and use. His research helps models learn from images without extensive human labeling and build strong systems that require less computing power.\u003C\/p\u003E\u003Cp\u003E\u201cMedical measurements are often noisy, incomplete, or difficult to interpret. Yet they can carry information that matters for doctors and patients,\u201d said Wang.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cI\u2019m motivated by the opportunity to combine what we know about the physical world with new learning methods to build AI systems that are more reliable and useful.\u201d\u003C\/p\u003E\u003Cp\u003ELooking ahead, Wang is building the\u0026nbsp;\u003Ca href=\u0022https:\/\/swilab.cc.gatech.edu\/\u0022\u003ESWI Lab\u003C\/a\u003E (science, world models, and intelligence) at Georgia Tech.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe lab develops AI \u201cworld models\u201d that learn how physical and biological systems behave, predict how they change, and help researchers draw insights from incomplete measurements. This work connects fundamental AI advances with challenges in medicine and science.\u003C\/p\u003E\u003Cp\u003EPh.D. students\u0026nbsp;\u003Ca href=\u0022https:\/\/xfeng01.github.io\/\u0022\u003EXinsong Feng\u003C\/a\u003E and\u0026nbsp;\u003Ca href=\u0022https:\/\/zwt.zip\/\u0022\u003EWentao Zhou\u003C\/a\u003E joined SWI Lab this fall as its inaugural members. The lab welcomes prospective students, research interns, and visitors interested in world models and Wang\u2019s work.\u003C\/p\u003E\u003Cp\u003E\u201cThe opportunity to work across computing, engineering, and science attracted me most to Georgia Tech,\u201d Wang said.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cThe most interesting problems often require both new AI ideas and deep knowledge of their applications. I look forward to studying those problems through new relationships and collaborations.\u201d\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAs doctors increasingly rely on computational approaches to examine and treat patients, Georgia Tech is building its expertise at the intersection of healthcare, computer vision, and artificial intelligence (AI).\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022mailto:https:\/\/pwang.pw\/\u0022\u003EJiayun (Peter) Wang\u003C\/a\u003E began his tenure-track career on Oct. 15 as an assistant professor in the School of Computational Science and Engineering (\u003Ca href=\u0022mailto:https:\/\/cse.gatech.edu\/\u0022\u003ECSE\u003C\/a\u003E).\u003C\/p\u003E\u003Cp\u003EAt Georgia Tech, Wang will develop new AI tools to help doctors make better use of complex medical data. His research aims to transform information from medical images, clinical measurements, and patient records into clearer insights that improve diagnosis, treatment, and patient care.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Jiayun (Peter) Wang began his tenure-track career at Georgia Tech on Oct. 15. He is an assistant professor in the School of Computational Science and Engineering (CSE) specializing in computer vision and AI for healthcare, biology, and science."}],"uid":"36319","created_gmt":"2026-10-29 15:05:18","changed_gmt":"2026-10-29 15:44:35","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-10-29T00:00:00-04:00","iso_date":"2026-10-29T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"681588":{"id":"681588","type":"image","title":"PW3-Story-Head-Image.jpg","body":null,"created":"1793286333","gmt_created":"2026-10-29 15:05:33","changed":"1793286333","gmt_changed":"2026-10-29 15:05:33","alt":"CSE Peter Wang","file":{"fid":"266010","name":"PW3-Story-Head-Image.jpg","image_path":"\/sites\/default\/files\/2026\/10\/29\/PW3-Story-Head-Image.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/10\/29\/PW3-Story-Head-Image.jpg","mime":"image\/jpeg","size":125726,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/10\/29\/PW3-Story-Head-Image.jpg?itok=4ow99w4n"}}},"media_ids":["681588"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1188","name":"Research Horizons"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"138","name":"Biotechnology, Health, Bioengineering, Genetics"},{"id":"153","name":"Computer Science\/Information Technology and Security"},{"id":"135","name":"Research"}],"keywords":[{"id":"654","name":"College of Computing"},{"id":"166983","name":"School of Computational Science and Engineering"},{"id":"187915","name":"go-researchnews"},{"id":"9153","name":"Research Horizons"},{"id":"10199","name":"Daily Digest"},{"id":"181991","name":"Georgia Tech News Center"},{"id":"170447","name":"Institute for Data Engineering and Science"},{"id":"9167","name":"machine learning"},{"id":"187812","name":"artificial intelligence (AI)"},{"id":"192863","name":"go-ai"},{"id":"194384","name":"Tech AI"},{"id":"11506","name":"computer vision"},{"id":"194391","name":"AI in Healthcare"},{"id":"195233","name":"AI in medicine"}],"core_research_areas":[{"id":"193655","name":"Artificial Intelligence at Georgia Tech"},{"id":"39441","name":"Bioengineering and Bioscience"},{"id":"39431","name":"Data Engineering and Science"},{"id":"39501","name":"People and Technology"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EBryant Wine, Communications Officer\u003Cbr\u003E\u003Ca href=\u0022mailto:bryant.wine@cc.gatech.edu\u0022\u003Ebryant.wine@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}