جست‌وجوی استاد و پژوهشگر

Sezgin Ayabakanمشاهده پروفایل

دانشیار

• Healthcare Analytics
• Business Value of Information Systems
• Data Analytics Techniques
• +۵ مورد دیگر

Dr. Sezgin Ayabakan is an Associate Professor in the Department of Management Information Systems at the Fox School of Business and Management, Temple University . He holds a PhD in Management Science from the University of Texas at Dallas, with a focus on Management Information Systems (MIS), an MS in Industrial and Systems Engineering from the University of Florida, and a BS in Industrial Engineering from Bilkent University in Turkey. His research focuses on healthcare analytics , particularly exploring how health information technology (HIT) impacts healthcare costs, quality, and utilization. Key research interests include data analytics applications in healthcare and social media, the business value of information systems, and open-source production strategies. He has examined topics such as telehealth efficacy, electronic health record (EHR) adoption challenges, hospital readmission reduction programs, and the interplay between healthcare IT and clinician well-being. Dr. Ayabakan teaches undergraduate and graduate courses in information systems, including MIS 2101: Digital Systems and SBM 3586: Diamond Peer Teachers - Internship II . His work has been published in top-tier journals like MIS Quarterly and Health Services Research and Management Epidemiology , with recent studies addressing telehealth utilization, EHR strategy impacts, and the role of organizational routines in clinician satisfaction. While no formal awards are listed, his contributions to healthcare IT research demonstrate significant academic impact. His advisory and grant activities are not detailed in the provided text, but his research often intersects with practical healthcare system challenges, suggesting potential collaborations with healthcare institutions and policy organizations.

Soroush Saghafianمشاهده پروفایل

دانشیار

• Operations Research
• Healthcare Delivery Optimization
• Public Policy Analytics
• +۳ مورد دیگر

Soroush Saghafian is an Associate Professor of Public Policy at Harvard Kennedy School, specializing in applying operations research and machine learning to address public health challenges. He leads the Public Impact Analytics Science Lab (PIAS-Lab), focusing on analytics-driven solutions for societal problems. His research spans healthcare delivery optimization, emergency department efficiency, and public health policy. Notable collaborations include Massachusetts General Hospital and Harvard's Center for Health Decision Science. Awards include the INFORMS MSOM Responsible Research Award and the Pierskalla Award for healthcare research. Recent work includes studies on hospital closures' impacts, predictive analytics for bipolar disorder using Fitbit data, and policy implications of race in disease risk models. He teaches courses on machine learning and big data for public impact.

• Medical Informatics
• Artificial Intelligence in Healthcare
• Healthcare Data Integration
• +۷ مورد دیگر

Prof. Martin Boeker is a Professor of Medical Informatics at the Technical University of Munich (TUM), affiliated with the TUM School of Medicine and Health. His work focuses on advancing healthcare through AI-driven solutions, interoperability frameworks, and precision medicine initiatives. Key projects include the German Medical Text Corpus (GeMTeX) and the MIRACUM DIFUTURE Alignment Hub. Expertise: Medical Informatics, AI in Healthcare, Federated Learning, Health Data Integration Key Contributions: FHIR-based systems, clinical decision support, patient-centered outcomes research Leadership: Director of the Institute for AI and Informatics in Medicine at TUM Hospital Right of the Isar Research emphasizes bridging clinical practice and data science through projects like modular health crawlers, automated guideline adherence monitoring, and cross-institutional medical NLP solutions. His work spans oncology informatics, rare disease management, and pandemic response data ecosystems. Recent articles highlight innovations in digital twins for precision oncology, federated analysis in oncology, and German-language medical NLP challenges. He collaborates internationally on EHR standardization and healthcare interoperability, contributing to the Medical Informatics Initiative (MII) and pandemic evidence ecosystems. Grants and collaborations involve the German Federal Ministry of Education and Research, European initiatives, and industry partnerships. Educational efforts focus on training future medical informatics professionals through MII competency programs.

Vishal Ahujaمشاهده پروفایل

دانشیار

• Healthcare Operations
• Operations Management
• Service Operations
• +۷ مورد دیگر

Vishal Ahuja is an Associate Professor and Corrigan Research Professor at Southern Methodist University's Cox School of Business, with adjunct faculty status at University of Texas Southwestern Medical Center. He focuses on decision analytic tools for healthcare improvement through operations management. PhD, University of Chicago Booth School of Business MBA, University of Chicago Booth School of Business His research interests span healthcare operations, service optimization, and AI applications in clinical decision-making. He collaborates with the Department of Veterans Affairs, Parkland Hospital, and pediatric institutions to address care quality and delivery efficiency. Recent publications emphasize predictive modeling for chronic disease management, adaptive clinical trial design, and regulatory healthcare policy. Awards include the Dlin/Fischer Clinical Research Award (2021), INFORMS Pierskalla Award (2012), and 2025 AI75 recognition for Dallas-Fort Worth AI leadership. D CEO Excellence in Healthcare Award - Outstanding Healthcare Innovator (2023) NSF Game Changer Academies for Advancing Research Innovation (2022) C. Jackson Grayson Faculty Innovation Award (2022-23) At SMU, he teaches graduate courses in operations, supply chain, and service management, integrating corporate sector experience from chemical and consumer goods industries. His work has been cited by the FDA in safety labeling changes workshops.

Pranav Rajpurkarمشاهده پروفایل

دانشیار

• Medical AI
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Pranav Rajpurkar is an Associate Professor at Harvard University, co-founder of a2z Radiology AI, and lead of the Rajpurkar Lab. His work pioneers AI systems that emulate physician-level expertise in medical tasks, with a focus on multi-modal medical AI and radiology. He joined Harvard faculty at age 25 and became Associate Professor at 30 after completing his Stanford PhD at 19. Education: Bachelor of Science (CS), Stanford University, 2015 Master of Science (CS), Stanford University, 2018 PhD (CS), Stanford University, 2021 Rajpurkar's research centers on building AI that thinks and communicates like doctors, with breakthrough work in ECG arrhythmia detection and chest X-ray interpretation. His lab develops foundational datasets (ReXGradient-160K, RadRevise) and benchmarks for medical AI, spanning computer vision, NLP, and multimodal systems. Current work focuses on generative AI for clinical workflows, voice-guided emergency assessment, and rigorous evaluation frameworks for medical LLMs. His 2025 publications reveal three dominant trends: (1) Generative medical AI for radiology report generation and editing, (2) Voice-enabled AI agents for prehospital care, and (3) Multimodal clinical monitoring systems. Key advancements include universal biomedical foundation models (UniBiomed), 3D CT segmentation from text reports, and frameworks for AI-human role separation in radiology. Scientific Awards: Forbes 30 Under 30 in Science (2022) MIT Tech Review Innovator Under 35 (2023) Nature Medicine Early-career Researcher To Watch (2022) Rajpurkar has mentored over 84,000 students through Harvard courses and Coursera's AI for Medicine program. His lab secures major NIH and NSF grants for medical AI development, with recent funding focused on multimodal emergency care systems (MC-MED) and radiologist-AI collaboration. He directs the Harvard-Stanford Medical AI Bootcamp and co-hosts The AI Health Podcast. The Rajpurkar Lab operates as a cross-institutional hub with collaborators at Stanford, MIT, and major hospitals. It drives initiatives like the MAIDA framework for global medical imaging data sharing and develops open-source tools including RadGraph for radiology report analysis. Current projects focus on voice AI for stroke assessment and generative models for non-invasive cancer management.

• Medical Education
• Internal Medicine
• Clinical Skills Assessment
• +۳ مورد دیگر

Caroline K. Milne, M.D., is Professor (Clinical) of Internal Medicine at the University of Utah School of Medicine, where she also serves as Vice Chair for Education and Program Director of the Internal Medicine Training Program. In addition, she directs the fourth-year sub-internship and leads clinical-skills education for medical students. Education & Training M.D., University of Wisconsin School of Medicine Residency & Chief Residency, Internal Medicine, University of Utah School of Medicine Fellowship in General Medicine / Medical Education Research, University of Pennsylvania M.B.A., Business Administration, University of Utah Fellowship in Executive Leadership in Health Care, Drexel University Research Focus Dr. Milne’s scholarly work centers on medical education research, particularly the assessment and development of clinical skills, evaluation of residency training programs, and policy studies on resident wellness and parental leave. Her investigations employ mixed-methods and multi-institutional survey designs to inform best practices in graduate medical education. Clinically, she practices general internal medicine at the VA Medical Center, integrating bedside teaching with outpatient and inpatient care. This dual role informs her research on optimizing educational experiences within clinical environments and improving systems of care for veterans. Publication Themes Across more than two decades, her peer-reviewed articles reveal consistent themes: evaluating learner performance, refining feedback mechanisms, exploring health-system responses (e.g., during COVID-19), and analyzing policies affecting residents’ well-being. The work bridges education science, health-services research, and quality improvement. Scientific Awards No specific awards are listed in the provided material. Advising & Grant Activity While formal student advisees are not enumerated, Dr. Milne’s roles as Program Director and Director of Clinical Skills imply extensive mentorship of residents and medical students. Grant details are not provided. Laboratories & Teams She collaborates with the Internal Medicine residency leadership team and the School of Medicine’s clinical-skills educators, operating primarily within the University of Utah’s academic medical center and the affiliated VA Medical Center.

Ping Heمشاهده پروفایل

استاد

• Plant Immunity
• Molecular Biology
• Genetic and Biochemical Approaches
• +۷ مورد دیگر

Ping He is a Professor in the Department of Molecular, Cellular, and Developmental Biology (MCDB) at the University of Michigan in Ann Arbor. His research focuses on plant immunity mechanisms, particularly using Arabidopsis as a model system to study pathogen defense activation, signaling pathways, and the interplay between immunity and environmental stress responses. He also leads the Molecular, Plant-Microbe Interaction Laboratory, applying interdisciplinary approaches (genetics, biochemistry, cellular biology) to enhance crop resilience through foundational plant science discoveries. His work bridges plant biology and computational biology, with recent contributions to AI-driven medical imaging applications such as bladder cancer treatment response assessment, lung cancer early detection, and breast tomosynthesis denoising. These efforts emphasize integrating machine learning into clinical workflows and establishing best practices for AI in healthcare. Research Highlights: Plant immunity signaling and environmental stress crosstalk Radiomics and deep learning for cancer diagnosis/prognosis AI model validation and multi-institutional clinical trials Medical imaging artifact correction (e.g., motion blur, noise) Publications emphasize AI applications in oncology imaging, radiologist decision support systems, and multimodal data fusion. He has contributed to AAPM task group guidelines for AI in computer-aided diagnosis and advocates for rigorous quality assurance frameworks in medical AI deployment.

• Health Equity
• Health Disparities
• Vulnerable Populations
• +۵ مورد دیگر

Melanie Molina, MD, MAS is an Assistant Professor of Emergency Medicine at the University of California, San Francisco (UCSF) and Affiliate Faculty of the Philip R. Lee Institute for Health Policy Studies. She serves as Co-Director of the Social Emergency Medicine and Health Equity Section and holds a secondary appointment in the Department of Medicine’s Division of Clinical Informatics and Digital Transformation. Clinically, she works at Zuckerberg San Francisco General Hospital and UCSF Medical Center. National Clinician Scholars Program Fellowship (2023) MAS in Clinical Research, UCSF (2023) Residency in Emergency Medicine, Harvard Medical School (2021) MD in Medicine, The University of Texas at Austin (2017) BS/BA in Biology and Hispanic Studies, The University of Texas at Austin (2012) Dr. Molina’s research centers on leveraging technology to address social determinants of health in emergency settings, with a focus on vulnerable populations. Her work spans health equity, opioid use disorder interventions, microaggressions in healthcare, and clinical informatics. She pioneers EHR-enabled tools to integrate social care into emergency clinical workflows while minimizing clinician burden. Her NIH-funded projects emphasize practical solutions for racial and ethnic health disparities, particularly in vaccine delivery and social risk documentation. Her recent publications (2024-2025) reveal three dominant trends: (1) Integration of AI and informatics for social risk screening and clinical decision support, (2) Health equity interventions targeting vaccine hesitancy and long COVID disparities, and (3) Critical analysis of DEI implementation challenges in academic emergency medicine. The work consistently bridges technical innovation with community-centered approaches to address systemic inequities. National Institutes of Health NIDA Loan Repayment Award (2024-2025) National Hispanic Medical Association Top 40 Under 40 (2024) UCSF John A. Watson Faculty Scholar (2023) National Institutes of Health NIAID Loan Repayment Award (2022-2024) Academy for Women in Academic Emergency Medicine Outstanding Research Publication Award (2021) Harvard Medical School Presidential Scholars Public Service Initiative Award (2017) Dr. Molina actively mentors medical students, residents, and fellows in health equity research. As Principal Investigator on multiple NIH and foundation grants—including the Harold Amos Medical Faculty Development Program grant ($825,575, 2024-2028) and an NIH/NIDA K23 award (2024-2029)—she leads projects developing EHR-integrated interventions for social risk documentation and opioid use disorder treatment. Her PROBOOSTVAXED trial addresses vaccine hesitancy through ED-based delivery across eight U.S. cities. She co-directs the Social Emergency Medicine and Health Equity Section within UCSF’s Department of Emergency Medicine, collaborating closely with the Action Research Center for Health Equity and the Philip R. Lee Institute for Health Policy Studies. Her team integrates clinical informatics expertise with community health workers to develop scalable solutions for social risk mitigation in safety-net emergency departments.

• Operations Management
• Manufacturing Systems
• Supply Chain Management
• +۵ مورد دیگر

Sunder Kekre is the Vasantrao Dempo Professor of Operations Management at Carnegie Mellon University’s Tepper School of Business , where he has held academic appointments since 1984. His research focuses on manufacturing systems, global supply chains, and healthcare operations management. Research Expertise : New product development structures, strategic costing, lean innovation, knowledge sharing in enterprise networks, and business analytics for coordinated supply chains. Key Publications : Contributions to journals like Management Science , Operations Research , and Production and Operations Management , with work on LNG storage valuation, RFID logistics, and healthcare disparities. Scientific Recognition : Dempo Chair Professorship Bosch Chair Professorship Best Paper Award (1995) Teaching : Courses in Operations Management, Strategic Management of the Enterprise, and Information Systems Project. Non-Academic Experience : Prior engineering roles at Tata Steel (1974-1980) and consulting engagements with Fortune 500 firms like Bosch, Caterpillar, and IBM.

• Breast Cancer Prevention
• Spatiotemporal Disease Modelling
• Health Economics
• +۳ مورد دیگر

Dr. Jannah Baker is a Research Fellow at the Sydney School of Public Health, University of Sydney. She holds a PhD in Statistics specializing in Bayesian spatiotemporal modelling of chronic diseases, alongside dual postgraduate diplomas in Public Health and Statistics. Her clinical background includes five years as a practicing physician. Her research focuses on cancer prevention (breast, endometrial, melanoma), spatiotemporal disease modeling, health economics, and clinical trial design. She has led projects on sepsis detection systems, diabetes management, and surgical outcomes analysis. Notable contributions include a seminal systematic review on fertility-sparing endometrial cancer treatments referenced in international guidelines. Jannah has attracted $6M+ in collaborative funding and oversees grants such as the 2023 NHMRC-funded ROADMAP trial and a Department of Health-funded study on pediatric sepsis management. Her work spans 50+ peer-reviewed articles across journals like Journal of Medical Internet Research and PLOS One . Professional activities include clinical trials statistics, health economics analysis, and implementation science lectures. She has mentored multiple research teams and maintains an ORCID profile (0000-0002-2208-6584).

• Medical Physics
• Artificial Intelligence in Medicine
• Radiation Therapy Treatment Planning
• +۷ مورد دیگر

Dan Nguyen, Ph.D., is a faculty member in the Department of Radiation Oncology at UT Southwestern Medical Center, where he is part of the Division of Medical Physics and Engineering. He is a founding member of the Medical Artificial Intelligence and Automation (MAIA) Laboratory, collaborating closely with Dr. Steve Jiang to advance AI applications in radiotherapy. His work focuses on deep learning for treatment planning, dose prediction, auto-segmentation, and adaptive radiotherapy. Ph.D. in Biomedical Physics, University of California, Los Angeles (UCLA), 2017 Mentor: Dr. Ke Sheng Faculty appointment at UT Southwestern since 2017 Dr. Nguyen’s research is centered on applying artificial intelligence to solve critical challenges in radiation oncology. His primary interests include deep learning-based dose prediction, auto-segmentation of anatomical structures, optimization of treatment plans, and real-time adaptive radiotherapy. He has pioneered work in direct aperture optimization, 4π radiotherapy, and uncertainty quantification in AI models. His research bridges the gap between AI innovation and clinical implementation, with a focus on improving plan quality, reducing planning time, and enhancing accessibility for less experienced clinicians. The most recent publications (2023–2025) demonstrate a consistent trend in developing fast, accurate, and robust deep learning models for radiotherapy. Key themes include dose prediction with transfer and meta-learning, adaptive segmentation using test-time optimization, uncertainty assessment in AI predictions, and mathematical modeling of radiotherapy-immunotherapy synergy. These works span high-impact journals in medical physics, AI, and oncology, reflecting interdisciplinary innovation. While no specific scientific awards are listed, Dr. Nguyen’s leadership in the MAIA Lab and extensive publication record in top-tier journals indicate significant recognition in the field of medical physics and AI in medicine. Dr. Nguyen has co-authored numerous studies involving mentoring and collaborative research, particularly with trainees and junior faculty in the MAIA Lab. His work is supported by institutional and likely federal funding, given the scale and scope of AI deployment studies. He has contributed to large-scale collaborative efforts such as OpenKBP-Opt, involving international teams evaluating knowledge-based planning pipelines. The MAIA Laboratory is a multi-investigator research group focused on innovating, developing, and applying artificial intelligence technologies to empower clinicians—especially those with less experience or limited resources—for improved patient care. The lab’s work spans machine learning, deep learning, reinforcement learning, and mathematical modeling in radiation oncology.

• Information Systems
• Operations Management
• Business Strategy
• +۵ مورد دیگر

Henrique O'Neill is an Associate Professor (with Habilitation) in the Department of Marketing, Operations and General Management at ISCTE - University Institute of Lisbon, Portugal. He is an Integrated Researcher at ISTAR-Iscte - Research Center in Information Sciences, Technologies and Architecture. His research focuses on information systems adoption, organizational strategy, and process optimization in healthcare, finance, and public administration. Education: PhD in Business Organization and Management - University of Cranfield (1995) Master's in Electrical and Computer Engineering - Higher Technical Institute (1987) Bachelor's in Electrical Engineering - Higher Technical Institute (1983) Research Interests: His work spans business/IT strategy, systems modeling, process analysis, and technology implementation. Key domains include healthcare informatics, banking systems, and Industry 4.0 applications. He emphasizes practical solutions for organizational performance through technology integration. Publication Trends: Recent articles explore intelligent business systems, telemedicine, design science methodologies, and supply chain innovation. His work consistently bridges theoretical frameworks with sector-specific applications in healthcare, education, and logistics. Professional Engagement: Member: Portuguese Telemedicine Association, Order of Engineers Commissioner: INEM (National Institute of Medical Emergency) reform study Director: Center for IT Development (2010-2014) Advising & Projects: Supervises 7 graduate students (1 PhD, 6 Master's). Leads EU-funded projects including: Atlantic Crossing (2024-2025): US-Portugal academic collaboration in AI/cybersecurity AAL4ALL (2011-2015): Ambient Assisted Living ecosystem UNITE (2000-2002): Ubiquitous teamwork platforms

John Z. Ayanianمشاهده پروفایل

استاد

• Health Equity
• Health Care Disparities
• Access to Care
• +۴ مورد دیگر

John Z. Ayanian serves as the Alice Hamilton Distinguished University Professor of Medicine and Healthcare Policy at the University of Michigan, holding joint appointments as Professor of Internal Medicine in the Medical School, Professor of Health Management and Policy in the School of Public Health, and Professor of Public Policy in the Gerald R Ford School of Public Policy. As inaugural Director of the Institute for Healthcare Policy and Innovation (IHPI), he leads a consortium of 700 faculty members across 15 schools and maintains clinical practice as a general internist at Michigan Medicine. His academic foundation includes a Bachelor of Arts in history and political science from Duke University (1982), medical degree from Harvard Medical School (1987), and master's in public policy from Harvard Kennedy School (1987), followed by residency and fellowship at Brigham and Women’s Hospital and post-doctoral training in health services research at Harvard School of Public Health. Dr. Ayanian's research program investigates health equity, access to care, and quality of care with particular attention to social determinants including race/ethnicity, gender, socioeconomic status, and insurance coverage. His work critically examines Medicaid expansion impacts, Medicare Advantage disparities, and policy responses to health inequities, often utilizing large-scale claims databases and cross-institutional collaborations. Current projects include the federally-authorized evaluation of Michigan's Medicaid expansion program serving over 700,000 adults. Analysis of his 15 most recent publications (2025) reveals three dominant research thrusts: (1) Medicare Advantage vs Traditional Medicare comparisons across diverse clinical conditions, (2) Medicaid policy evaluation including unwinding impacts and expansion effects, and (3) innovative measurement of health equity through new indices and AI applications. His work consistently emphasizes methodological rigor in health services research while maintaining strong policy relevance. His scientific honors include: Election to the National Academy of Medicine Master status in the American College of Physicians John Eisenberg National Award for Career Achievement in Research Distinguished Investigator Award from AcademyHealth Election to Alpha Omega Alpha and Association of American Physicians Dr. Ayanian leads the federally-funded Healthy Michigan Plan evaluation team of 15 faculty members and serves as founding Editor-in-Chief of JAMA Health Forum, previously holding editorial positions at the New England Journal of Medicine. His research receives substantial federal support focused on health policy evaluation, with particular emphasis on vulnerable populations. He actively mentors students and junior faculty across multiple disciplines. As Director of IHPI, he fosters interdisciplinary collaboration across 15 schools at the University of Michigan. His leadership extends to center memberships in AI and Digital Health Innovation, Caswell Diabetes Institute, and Center for Global Health Equity, where he promotes data-driven solutions to health disparities through cross-campus partnerships and innovative research methodologies.

Seokjun Younمشاهده پروفایل

استادیار

• Healthcare Operations Management
• Service and Retail Operations
• Health IT Management
• +۹ مورد دیگر

Seokjun Youn is an Assistant Professor in the Department of Management Information Systems at the Eller College of Management, University of Arizona . His research focuses on improving healthcare delivery systems through technological innovations and operational strategies, with additional expertise in supply chain logistics and platform business models. Education: PhD in Operations and Supply Chain Management from Texas A&M University; MS and BS in Industrial Engineering from Texas A&M University and Seoul National University, respectively. Research Areas: Healthcare operational efficiency, patient flow, health IT, human-AI collaboration, and supply chain management. Scientific Awards: DSI Best Theory-Driven Empirical Research Paper Award (2024) CMIH Grant (2020, 2021, 2023, 2024, 2025) POMS Emerging Scholars Program (2021, 2023) Professional Service: Editorial board member for Production and Operations Management and Decision Sciences journals; track chair for conferences like CHITA and DSI. His work combines econometric methods and optimization techniques to address challenges in healthcare systems, with findings published in top journals including Manufacturing & Service Operations Management and Journal of Operations Management .

• Clinical Informatics
• Emergency Medicine
• Electronic Health Records
• +۵ مورد دیگر

Mark Iscoe, MD, MHS is an Assistant Professor of Emergency Medicine and Biomedical Informatics and Data Science at Yale School of Medicine. He holds fully joint appointments in both the Department of Emergency Medicine and the Department of Biomedical Informatics & Data Science, reflecting his interdisciplinary work at the critical intersection of clinical emergency care and health informatics innovation. Dr. Iscoe completed his medical degree at Johns Hopkins University School of Medicine in 2017, followed by residency training in Emergency Medicine at New York University / Bellevue Hospital in 2021. He further specialized with a Master of Health Science (MHS) in Clinical Informatics from Yale School of Medicine in 2023. He is board certified in both Emergency Medicine (2022) and Clinical Informatics (2024). His research spans several interconnected domains with a focus on optimizing the interface between emergency physicians and health information technology. Key areas include electronic health record (EHR) optimization, artificial intelligence applications in emergency settings, clinical decision support systems, and medication safety protocols. His 2024 JAMA Network Open publication 'Benchmarking Emergency Physician EHR Time per Encounter Based on Patient and Clinical Factors' represents a significant contribution to understanding the digital burden on emergency clinicians. More recently, he has pioneered work applying large language models to emergency medicine challenges, with multiple 2025 publications on AI applications for deprescribing, symptom identification, and risk stratification. His research trajectory shows a clear evolution from foundational EHR usage studies toward increasingly sophisticated AI implementations that bridge theoretical informatics with practical clinical tools in high-pressure emergency settings. YCCI Scholar Award for AI Research on Drug Reactions (2024) Dr. Iscoe has received research funding from multiple prestigious sources including the National Institute on Drug Abuse (NIDA), the American Medical Association (AMA), the National Institutes of Health, and Yale New Haven Health System. His collaborative network includes prominent researchers such as Andrew Taylor (6 joint publications), Ted Melnick (5 joint publications), and Rohit Sangal (4 joint publications), reflecting his work's multidisciplinary nature spanning clinical departments, informatics specialists, and data scientists.