{"response":{"award":[{"abstractText":"The Industry-University Cooperative Research Center (IUCRC) for Accessible Healthcare through AI-Augmented Decisions (AHeAD) will develop reliable and usable AI technologies, so quality care is accessible by all populations. AHeAD is a multi-university research partnership between UL Lafayette (lead), Tulane, University of Florida and Georgia Tech. The center’s research will create validated AI-enabled systems, quality assurance frameworks, and best practices that enable healthcare organizations to offer quality care for all, reducing healthcare gaps while saving costs. By training the next-generation AI workforce and releasing open-source AI models, the center will drive innovation, create new jobs, and grow the American economy.\r\n\r\nAHeaD's goal is to develop reliable AI technologies that improve healthcare access and outcomes for all populations. Research focuses on creating privacy-preserving, interoperable, explainable and resource-efficient AI models for healthcare. The center's multidisciplinary program includes AI/ML, data science, systems engineering, and health sciences, supported by computational infrastructure and real-world health data through industry partnerships. Research will advance reliable AI, privacy-aware data integration, behavioral context modeling, and human-AI integration. The center will foster workforce development through student training and industry collaborations, building a skilled talent pool to accelerate healthcare AI translation from research to practice. UL Lafayette’s research focus includes federated learning, data science and engineering, conversational agents, intelligent systems engineering, and health informatics. Furthermore, the university leverages strong partnerships with public health agencies, various healthcare organizations, and local/state-level economic development entities to translate AI research into practical applications. AHeAD will address critical national healthcare challenges and advance U.S. competitiveness in AI-enabled healthcare. The Center creates a rich environment for training next-generation professionals through integrating industry-relevant AI applications into curriculum development and providing direct experience solving healthcare challenges with real-world data. The Center will create and maintain standardized healthcare datasets, publish open-source software and research outputs, and advance technologies with broad healthcare applications. This multifaceted approach promises to improve the health of millions of Americans while generating substantial cost savings for both government and industry.\r\n\r\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.","activeAwd":"true","agency":"NSF","awardAgencyCode":"4900","awardee":"UNIVERSITY OF LOUISIANA AT LAFAYETTE","awardeeAddress":"104 E UNIVERSITY AVE","awardeeCity":"LAFAYETTE","awardeeCountryCode":"US","awardeeDistrict":"03","awardeeDistrictCode":"LA03","awardeeName":"University of Louisiana at Lafayette","awardeePhone":"3374825811","awardeeStateCode":"LA","awardeeZipCode":"705032014","cfdaNumber":"47.041, 47.070, 47.084","coPDPI":["Xiali Hei c00404592@louisiana.edu","Ravi Teja Bhupatiraju raviteja@louisiana.edu","Scott Sittig scott.sittig@louisiana.edu","Gabriela Mustata Wilson gabriela.wilson@louisiana.edu"],"date":"07/13/2025","dirAbbr":"CSE","divAbbr":"CST","estimatedTotalAmt":"19999","expDate":"06/30/2028","fundAgencyCode":"4900","fundProgramName":"IUCRC-Indust-Univ Coop Res Ctr","fundsObligated":["FY 2025 = $19,999.00","FY 2026 = $3,998.00"],"fundsObligatedAmt":"23997","histAwd":"false","id":"2515284","initAmendmentDate":"07/13/2025","jrnl":[{"artTitl":"AdvOSD: Adversarial One-Step Diffusion for Generalizable and Efficient Fake Image Detection","auth":"Shan, Liqun and Han, Kaiying and Tu, Yazhou and Hei, Xiali","authIndCode":"N","dgtlObjId":"https://doi.org/10.1109/ACSAC67867.2025.00082","jrnlYr":"2025","parPblcId":"10690470"},{"artTitl":"Purified Distillation Slimming (PDS) for Robust Backdoor Defense","auth":"Shan, Liqun and Han, Kaiying and Tu, Yazhou and Lee, Insup and Hei, Xiali","authIndCode":"N","dgtlObjId":"https://doi.org/10.1145/3779208.3785283","jrnlYr":"2026","parPblcId":"10690469"},{"artTitl":"MHDash: An Online Platform for Benchmarking Mental HealthAware AI Assistants","auth":"Zhang, Yihe and Mohawk, Finn and Han, Kaiying and Tida, Vijay Srinivas and Li, Manyu and Hei, Xiali","authIndCode":"N","dgtlObjId":"https://doi.org/10.1109/SoutheastCon63549.2026.11476505","jrnlYr":"2026","parPblcId":"10690473"}],"latestAmendmentDate":"08/03/2026","managingPec":"576100","orgCodeDir":"05000000","orgCodeDiv":"05250000","orgLongName":"Directorate for Computer and Information Science and Engineering","orgLongName2":"Center Scale & Testbeds","orgUrl":"https://www.nsf.gov/cise","parentUeiNumber":"","pdPIName":"Raju Gottumukkala","perfAddress":"104 E UNIVERSITY AVE","perfCity":"LAFAYETTE","perfCountryCode":"US","perfDistrict":"03","perfDistrictCode":"LA03","perfLocation":"University of Louisiana at Lafayette","perfStateCode":"LA","perfZipCode":"705032014","pi":["Raju Gottumukkala raju@louisiana.edu"],"piEmail":"raju@louisiana.edu","piFirstName":"Raju","piId":"269879017","piLastName":"Gottumukkala","poEmail":"haliu@nsf.gov","poName":"Hang Liu","poPhone":"7032925139","primaryProgram":["01002526DB NSF RESEARCH & RELATED ACTIVIT","01002627DB NSF RESEARCH & RELATED ACTIVIT"],"progEleCode":"576100","program":"INDUSTRY/UNIV COOP RES CENTERS, EXP PROG TO STIM COMP RES","progRefCode":"5761, 9150","publicAccessMandate":"1","publicationResearch":["2025~Shan, Liqun and Han, Kaiying and Tu, Yazhou and Hei, Xiali~https://doi.org/10.1109/ACSAC67867.2025.00082~AdvOSD: Adversarial One-Step Diffusion for Generalizable and Efficient Fake Image Detection~N~10690470~10690470~OSTI~2026-06-13 17:29:25.986","2026~Shan, Liqun and Han, Kaiying and Tu, Yazhou and Lee, Insup and Hei, Xiali~https://doi.org/10.1145/3779208.3785283~Purified Distillation Slimming (PDS) for Robust Backdoor Defense~N~10690469~10690469~OSTI~2026-06-13 17:23:50.323","2026~Zhang, Yihe and Mohawk, Finn and Han, Kaiying and Tida, Vijay Srinivas and Li, Manyu and Hei, Xiali~https://doi.org/10.1109/SoutheastCon63549.2026.11476505~MHDash: An Online Platform for Benchmarking Mental HealthAware AI Assistants~N~10690473~10690473~OSTI~2026-06-13 17:47:11.99"],"startDate":"07/01/2025","title":"IUCRC Planning Grant University of Louisiana at Lafayette (Lead Site): Center for Accessible Healthcare through AI-Augmented Decisions (AHeAD)","transType":"Standard Grant","ueiNumber":"C169K7T4QZ96"}],"metadata":{"offset":0,"rpp":25,"totalCount":1}}}