جست‌وجوی استاد و پژوهشگر

Burcu ÇARKLI YAVUZمشاهده پروفایل

استادیار

• Data Mining
• Bioinformatics
• Artificial Intelligence
• +۳ مورد دیگر

Burcu ÇARKLI YAVUZ serves as an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Information Systems Engineering. Her academic career spans over a decade with continuous contributions since 2013, including current administrative roles as Dean's Assistant (2023-2024) and Department Vice Chair (2021-2023). Education: PhD in Computer and Information Engineering (2019), Sakarya University - Thesis: 'Hemoglobin Protein Secondary Structure Prediction by Improved Clonal Selection Algorithm' MS in Computer and Information Engineering (2010), Sakarya University - Thesis: 'A Data Mining Application with Apriori Algorithm in the Healthcare Sector' BSc in Mathematics-Computer Programming (2005), Istanbul Cultural University Her research integrates artificial intelligence with critical applications across healthcare and renewable energy. Specializing in data mining and bioinformatics, she develops novel algorithms for protein structure prediction, medical diagnostics, and photovoltaic system optimization. Current work focuses on Marine Predators Algorithm applications for perinatal mental health screening and adaptive MPPT techniques for solar energy systems, demonstrating interdisciplinary impact from biomedical engineering to climate change mitigation. Publication analysis reveals three dominant research thrusts: (1) AI-driven healthcare solutions (depression/anxiety detection, diabetes diagnosis), (2) Photovoltaic optimization (MPPT algorithms, flicker analysis), and (3) Bioinformatics (protein structure prediction using clonal selection). Her work consistently bridges theoretical algorithm development with practical implementations, evidenced by industry collaborations like the 2023 'Electric Vehicle Regulation-Compliant Sound Alert Systems' project. Teaching responsibilities include graduate and undergraduate courses in Deep Learning, Python Programming, Operations Research, and Introduction to AI. She has supervised numerous graduation projects and taught specialized courses like 'Big Data Technologies' in collaboration with Havelsan. Her editorial service for IEEE Access (2018-2020) and conference organization roles demonstrate academic leadership beyond teaching and research.

Mark Wallaceمشاهده پروفایل

استاد

• Optimization
• Constraint Programming
• Artificial Intelligence
• +۵ مورد دیگر

Professor Mark Wallace is a renowned academic at Monash University , specializing in modelling and software platforms for planning, scheduling, and optimization problems . He has led groundbreaking projects such as the development of the ECLiPSe constraint programming platform (acquired by Cisco Systems) and the G12 hybrid optimization platform , which was commercialized through his company, Opturion . His research consistently bridges theoretical innovation with real-world applications, supported by industry funding from major companies like British Airways, Qantas, and Woodside Energy. Education: MA in Mathematics and Philosophy from Oxford University; MSc in Artificial Intelligence from Queen Mary College, London; PhD in Communicating with Databases in Natural Language from Southampton University. His work focuses on application-driven research in constraint programming, hybrid optimization systems, and decision support technologies. Recent publications highlight advancements in public transport routing , autonomous vehicle fairness constraints , and human-centred feasibility restoration . He actively collaborates with industry partners on projects involving Melbourne Water , Woodside , and the Alertness CRC , driving innovations in smart infrastructure and transport systems.

• Privacy-friendly home-based monitoring
• Unobtrusive sensing solutions
• Activity recognition and classification
• +۸ مورد دیگر

Dr. Idongesit Ekerete (FHEA, IEEE/IPEM member) is a Lecturer in Computing Science at the School of Computing , Ulster University. He serves as Lab Manager for the Pervasive Computing Research Centre and co-investigator in a £3.3M Advanced Research and Engineering Centre project focused on FinCrime. His academic background includes a B.Eng. (First Class) in Electrical/Electronic Engineering from University of Uyo (2011), M.Sc. in Biomedical Engineering from University of Strathclyde (2017), and a PhD in Unobtrusive Sensing from Ulster University (2021). Current role: Lecturer in Computing Science (Ulster University, since 2021) Past role: Lecturer in Electrical/Electronic Engineering (University of Uyo, 2011–2021) Professional: Vice-Chair of IEEE SMC UK-Ireland Chapter His research focuses on privacy-preserving home monitoring systems using unobtrusive sensing , sensor fusion , and AI activity modeling . Recent publications explore thermal sensor applications for mood detection, federated learning for financial crime detection, and gait analysis for elderly wellbeing. Key themes include human-computer interaction , digital twins , and control systems engineering applied to healthcare contexts. Scientific contributions include: Learning and Teaching Award 2024 for student support UNIUYO Best Graduating Student Award Prof. Hilary’s Academic Excellence Award He has authored 20+ research outputs and led collaborations across biomedical engineering, pervasive computing, and financial crime detection domains.

Tobias Grundgeigerمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Psychological Ergonomics
• User Experience Design
• +۷ مورد دیگر

Dr. Tobias Grundgeiger is an Associate Professor in Human-Computer Interaction at Julius-Maximilians-University Würzburg, where he serves as an Academic Councillor in the Faculty of Human Sciences. He leads research in the Institute for Human-Computer-Media, specifically within the Psychological Ergonomics group under Prof. Dr. Jörn Hurtienne. Additionally, he holds an Associate Professor/Honorary Research Fellow position at The University of Queensland, Brisbane, Australia. His educational background includes: PhD studies at The University of Queensland, Brisbane, Australia (2007-2010) Psychology studies at the University of Regensburg (2001-2006) Habilitation/Associate Professor qualification in Human-Computer Interaction (2022) Dr. Grundgeiger's research focuses on the interaction between people and technology in socio-technical systems, particularly in healthcare environments such as hospitals, control rooms, and aviation. His work examines how technology can be designed and integrated into complex systems to maximize user benefits while maintaining safety. A secondary research interest explores technology's role in relation to dying and death, aiming to develop technologies that transform engagement with these experiences into meaningful, eudaimonic encounters. His methodological approach combines empirical studies in real-world settings with theoretical frameworks from activity theory, embodied interaction, and psychological need satisfaction. His recent publications reveal a strong focus on AI applications in anesthesiology, human-AI teaming, augmented reality interfaces, and interruption management in safety-critical contexts. A significant portion of his work examines how technology can support clinicians during high-stress medical procedures while maintaining workflow integrity. His research demonstrates how cognitive aids, documentation assistants, and monitoring systems can be designed to align with clinical workflows rather than disrupt them. Dr. Grundgeiger is actively involved in several major research projects, most notably as contact person for the CASSANDRA project (2022-2025), which develops an AI team member for anesthesiology. This €1.34 million project, funded by the German Federal Ministry of Education and Research, aims to create a voice-based virtual agent that supports anesthesia teams through automated documentation and clinical decision support. His teaching responsibilities span both undergraduate and graduate levels, covering Human-Computer Systems, Psychological Ergonomics, Healthcare Usability & User Experience, Eye-Tracking methods, and Theories of Human-Computer Interaction. His pedagogical approach emphasizes practical applications of theoretical concepts in real-world settings.

Eric Gon-Chee Poonمشاهده پروفایل

استاد

• Health Information Technology
• Patient Safety
• Clinical Decision Support
• +۳ مورد دیگر

Eric Gon-Chee Poon serves as Professor of Medicine and Professor of Biostatistics and Bioinformatics at Duke University School of Medicine, while concurrently holding the executive position of Chief Health Information Officer for Duke Medicine. He maintains active clinical practice in primary care internal medicine at Duke Primary Care's Durham Medical Center. His educational foundation includes an M.D. from Harvard Medical School (1998), M.P.H. from Harvard University (2003), and clinical training at Brigham and Women's Hospital encompassing Internal Medicine residency (1998-2001) and General Internal Medicine fellowship (2001-2003). Professional appointments include Associate Editor roles for New England Journal of Medicine Catalyst (2024-2025) and Journal of the American Medical Informatics Association (2017-2025). Dr. Poon's research program centers on health information technology applications for quality improvement and patient safety across clinical settings. Early work optimized diagnostic test management through clinical decision support systems and secure patient portals, while hospital-based studies examined computerized physician order entry adoption and barcode medication safety systems. Recent scholarship pivots to artificial intelligence implementation challenges, addressing ethical frameworks, clinician acceptance strategies, and large language model validation in clinical workflows. His 2025 publication in JAMIA analyzing health system AI priorities reflects ongoing leadership in this emerging domain. Analysis of his 2020-2025 publications reveals concentrated expertise in AI deployment barriers, with 70% of recent work focusing on ethical governance, clinician burnout mitigation, and practical implementation frameworks for predictive models. Key themes include adapting social media engagement principles to clinical decision support and developing hybrid assessment methodologies for AI-drafted communications. Scientific Awards: No awards explicitly listed in source materials Dr. Poon's operational leadership as CHIO involves strategic oversight of Duke Medicine's Maestro Care (Epic) EHR optimization, requiring partnership with clinical and administrative stakeholders to align technology solutions with organizational objectives. His research program leverages these operational insights to investigate socio-technical impacts of health IT, though specific grant details remain unreported in available materials. As highlighted in Duke's news feature "Bringing Order to the 'Wild West' of Artificial Intelligence in Medicine," Dr. Poon champions structured approaches to AI adoption, emphasizing ethical deployment frameworks and clinician-centered design principles to navigate healthcare's rapidly evolving technological landscape.

Yaw Adu-Gyamfiمشاهده پروفایل

دانشیار

• Traffic Operations
• Intelligent Transportation Systems
• Civil Infrastructure Systems
• +۳ مورد دیگر

Yaw Adu-Gyamfi is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Missouri-Columbia , specializing in Traffic Operations , Intelligent Transportation Systems , and Big Data Analytics . His research leverages Artificial Intelligence and LiDAR for infrastructure health monitoring and road safety innovations. Education : PhD and MCE from the University of Delaware; BSC in Geomatic Engineering from Kwame Nkrumah University of Science and Technology. His work focuses on real-time traffic analytics , cloud-based solutions , and automated pavement distress classification , supported by grants from the NSF , U.S. DOT , and state agencies. He co-founded Tiger Eye Engineering, LLC , offering road distress monitoring services, and has developed tools like PaveSAM for segmentation and Deep InSight for driver-state estimation. Recent research includes generative adversarial networks for pavement assessments, 3D object detection with LiDAR, and resource-efficient damage detection using YOLOv10. His projects emphasize scalable, low-cost solutions for transportation challenges. Scientific Awards NSF CAREER Award (2021) Spirit Award from NSF I-Corps Program He has collaborated with Mizzou Engineering , MoDOT , and international partners on safety systems, including autonomous alerts for work zones and predictive models for road maintenance. His team conducted over 100 interviews to refine tools for transportation officials.

• Health Informatics
• Machine Learning in Healthcare
• Clinical Decision Support Systems
• +۳ مورد دیگر

Genevieve Melton-Meaux is a Professor at the University of Minnesota's Division of Colon & Rectal Surgery, Director of the Center for Learning Health System Sciences, and Senior Associate Dean for Health Informatics and Data Science. She serves as Chief Health Informatics and AI Officer at Fairview Health Services, integrating informatics and artificial intelligence into clinical practice. Her research focuses on health informatics , machine learning applications in healthcare , and clinical NLP , with recent work on mortality prediction algorithms, telestroke implementation, and opioid management tools. She has developed AI diagnostic systems for chest X-rays and studied diabetes-related hospital outcomes. Article Trends : Her publications highlight AI in clinical decision support , NLP for EHR analysis , and health equity through social determinant detection . Work spans multicenter AI validation automated trauma record analysis medication safety systems preventive screening optimization Administrative Roles : Director, Center for Learning Health System Sciences Senior Associate Dean for Health Informatics and Data Science Chief Health Informatics and AI Officer, Fairview Health Services

Ling Chuمشاهده پروفایل

دانشیار

• Medical Informatics
• Ambulatory Care
• Clinical Informatics
• +۳ مورد دیگر

Ling Chu, M.D. serves as Associate Professor in the Department of Internal Medicine at UT Southwestern Medical Center and holds the dual leadership role of Assistant Vice President and Chief Medical Informatics Officer (CMIO) for Ambulatory Services within the UT Southwestern Health System. Her work uniquely bridges clinical practice in primary care with health informatics innovation to optimize patient-centered care delivery. Her educational foundation includes a bachelor's degree in pharmacy and medical degree from the University of Colorado, where she also completed her internal medicine residency training. This combined background in pharmacy and medicine informs her interdisciplinary approach to healthcare systems improvement. Dr. Chu's research program focuses on leveraging health information technology to solve real-world clinical challenges. Key emphases include electronic health record (EHR) optimization, patient portal implementation, predictive analytics for care coordination, and mitigating healthcare disparities through informatics solutions. She maintains board certification in clinical informatics from the American Board of Preventive Medicine, validating her expertise in this specialized domain. Analysis of her 2018-2024 publications reveals consistent thematic threads: pandemic impacts on preventive care, EHR usability enhancements, and standardized clinical phenotyping using SNOMED CT hierarchies. Her work demonstrates strong translational focus—converting informatics research into practical tools for ambulatory settings, particularly in no-show prediction, patient recruitment equity, and clinical workflow optimization. In her administrative capacity, Dr. Chu directs informatics strategy across UT Southwestern's ambulatory network, driving initiatives that connect frontline clinical operations with information technology infrastructure. Her leadership within the William T. and Gay F. Solomon Division of General Internal Medicine positions her at the nexus of academic medicine and healthcare system innovation.

• Medication Safety
• Health Informatics
• Patient-Provider Communication
• +۵ مورد دیگر

Bruce L Lambert is a Professor in Medical Social Sciences (Intervention Science) at Northwestern University's Feinberg School of Medicine and concurrently holds a Professor position at the School of Communication. His work bridges clinical medicine, health informatics, and communication science with appointments across multiple institutes including the Center for Diabetes and Metabolism, Institute for Public Health and Medicine (IPHAM), and Northwestern University Clinical and Translational Sciences Institute (NUCATS). His research focuses on medication safety systems, electronic health record (EHR) design, and health communication. Key interests include preventing drug name confusion errors, optimizing indication-based prescribing, and developing clinical decision support tools. Lambert employs psycholinguistic testing to predict real-world medication errors and investigates secure messaging networks in healthcare settings. His work demonstrates how EHR interface design directly impacts wrong-patient and wrong-drug error rates. Analysis of his recent publications reveals strong emphasis on opioid safety in emergency departments, Veterans Health Administration prescribing patterns, and multimodal approaches to medication error prevention. His scholarship consistently addresses system-level interventions rather than individual provider blame, advocating for human factors engineering solutions in healthcare technology. Lambert actively contributes to medication safety policy, having published on Tall Man lettering limitations and the need for comprehensive immune monitoring in vaccine trials. His research directly informs EHR design standards and clinical workflow improvements across multiple healthcare systems. As an educator, he integrates principles of conservative prescribing and health literacy into medical training. His work on pharmacy deserts in minority communities highlights health equity concerns in medication access. Lambert's PhD from University of Illinois at Urbana-Champaign (1992) established his foundation in communication science applied to healthcare contexts.

• Artificial Intelligence
• Data Mining
• Data Science
• +۸ مورد دیگر

Richard Andrew Taylor, MD, MHS, is an Adjunct Associate Professor at Yale University's Biomedical Informatics and Data Science department within the Yale School of Public Health. He also holds an Assistant Professor appointment in Emergency Medicine and serves as Director of Artificial Intelligence and Data Science at Yale. Dr. Taylor leads the Yale Interdisciplinary AI & Medicine Lab (Y-IAML), a cross-disciplinary initiative integrating AI, cognitive science, and ethics into healthcare delivery. Education: MD from Emory University (2007), MHS in Informatics from Yale (2015), fellowships in clinical informatics (Yale, 2015) and ultrasound (Yale, 2011). Dr. Taylor's research spans AI applications in emergency medicine, focusing on predictive analytics, data mining, and decision theory. His work addresses cognitive errors in high-pressure clinical environments through machine learning integration, with specific emphasis on electronic health records (EHR) analysis, point-of-care ultrasound outcomes, and health equity in opioid treatment. Recent publications highlight trends in AI-driven triage optimization , EHR-based dementia detection , and language model applications for medical calculations. His lab develops tools for automated clinical scoring , phenotype discovery , and equitable treatment pathways . Scientific Awards: University of St Andrews Global Fellow (2023) Dr. Taylor's grants include NIH funding (NIDA, NIA, NLM), AHRQ, and industry partnerships. He collaborates with experts in biostatistics, ethics, and clinical implementation science. Y-IAML actively engages in multidisciplinary research , combining design, behavioral economics, and computational methods to create implementable AI solutions for emergency care.

Gyorgy Baffyمشاهده پروفایل

دانشیار

• Fatty Liver Disease
• Portal Hypertension
• Liver Cancer
• +۳ مورد دیگر

Dr. Gyorgy Baffy serves as Associate Professor of Medicine at Harvard Medical School and Chief of Gastroenterology at the VA Boston Healthcare System, where he directs clinical services and research initiatives focused on liver disease pathophysiology. His dual academic-clinical role bridges Harvard's Department of Medicine with Veterans Affairs healthcare delivery, emphasizing translational research in metabolic liver disorders. His educational trajectory includes doctoral training at the University of Pennsylvania as an NIH Fogarty Fellow studying hepatocyte calcium signaling, followed by gastroenterology fellowship at the University of Michigan and Brigham and Women's Hospital. This foundation supports his current leadership in hepatology education and clinical innovation. Research interests center on fatty liver disease mechanisms, particularly risk stratification biomarkers, cancer bioenergetics in hepatocellular carcinoma, and portal hypertension development. His work explores obesity-liver disease interactions through gut microbiota studies, metabolic dysregulation in cirrhosis, and AI applications for polyp histology classification. Recent publications emphasize MASLD terminology standardization and systemic implications of liver fibrosis. Analysis of his 15 most recent publications reveals dominant themes in metabolic liver disease classification (33%), gut-liver axis mechanisms (27%), and healthcare system optimization for liver conditions (20%), with emerging focus on AI diagnostics (13%) and veteran-specific GI care (7%). Scientific recognition includes: Fellowships in four major medical colleges (American College of Physicians, American College of Gastroenterology, American Gastroenterological Association, American Association for Study of Liver Diseases) Madaus Prize from Madaus Liver Foundation Hetényi Medal and Pro Optimo Merito Award from Hungarian Gastroenterological Association Fulbright US Scholar designation (2014) As VA Boston Gastroenterology Chief, he leads system-wide initiatives including cirrhosis care standardization and FIB-4 implementation for diabetes-related liver screening. His leadership addresses critical workforce challenges in VA gastroenterology through national consensus-building, while his research program investigates gut microbiota modulation for portal hypertension and develops biomarkers for liver cancer risk stratification. Operational leadership spans VA Boston's gastroenterology division and Harvard Medical School's hepatology research consortia, with active participation in European obesity research networks and Veterans Health Administration quality improvement frameworks.

• Internet of Things
• System Dynamics Modeling
• Programming Languages
• +۳ مورد دیگر

Siniša Sovilj is an Associate Professor at the Faculty of Informatics in Pula (FIPU), part of the University of Pula in Croatia. He maintains an active teaching position with an office at Alda Negrija Street 6, room 012, and can be contacted at sinisa.sovilj@unipu.hr. His professional profile is available on LinkedIn. Dr. Sovilj's teaching responsibilities span multiple computing disciplines: Programming on the Java Virtual Machine (undergraduate) Data Analysis and Information Processing (graduate) Internet of Things (graduate) Mobile Applications (graduate) IT Solution Development (graduate) Graduation thesis supervision His research demonstrates significant interdisciplinary breadth with a progression from biomedical engineering toward computational and economic modeling. Early in his career, Dr. Sovilj focused on cardiac electrical activity modeling and ECG analysis, developing real-time P-wave detectors and predictive models for atrial fibrillation. More recently, his work has centered on Internet of Things systems, programming language analysis, and system dynamics approaches to economic and business problems. Dr. Sovilj's scholarly output reveals an interesting trajectory from specialized biomedical applications to broader computational frameworks. His recent publications (2021-2024) particularly highlight work on Kotlin-based system dynamics modeling, covariance analysis in object-oriented languages, and IoT educational platforms like the "Food Computer" demonstration system. His notable contributions include: Development of IoT monitoring systems for environmental applications Analysis of congestion mechanisms in IoT networks System dynamics modeling approaches for economic analysis Early work on cardiac electrical modeling and ECG analysis techniques As an educator, Dr. Sovilj has developed curriculum content across multiple computing disciplines, reflecting the evolving landscape of computer science education from traditional programming to emerging IoT technologies.

• Human-Computer Interaction
• User Experience
• Mobile Devices
• +۴ مورد دیگر

Peter Fröhlich serves as a Research Associate at the Institute for Marketing within the Faculty of Business at the University of Applied Sciences Wiener Neustadt (FH Wiener Neustadt). Based at the Wieselburg Campus, he maintains an active research profile with continuous scholarly output since 2005. His academic credentials include Mag. Dr. (Master's and Doctoral degrees in the Austrian system) and an MBA. Dr. Fröhlich's research focuses on human-computer interaction, with particular expertise in user experience design, mobile interfaces, and automotive human-machine interaction. His scholarly fingerprint reveals strong specialization in User Interface (100%), Interaction Technique (76%), Mobile Device (76%), and User Experience (69%) research domains. Recent work has examined touchscreen interfaces in extreme environments, takeover requests in automated driving, and design frameworks for automated material handling vehicles. His publication record shows consistent scholarly productivity with 119 documented publications between 2005 and 2025. The output has accelerated in recent years, with 10 publications in 2020, 10 in 2021, 7 in 2022, and 12 in 2023, demonstrating growing research activity. His work appears in reputable venues including Frontiers in Robotics and AI, CEAS Space Journal, and proceedings of the Automotive User Interfaces conference. Dr. Fröhlich maintains active research collaborations across multiple institutions, with co-authorship patterns indicating interdisciplinary work bridging computer science, human factors engineering, and business perspectives. His methodological approach emphasizes empirical user studies and experimental design to evaluate interaction techniques in real-world contexts.

• Entrepreneurship
• Incubators
• Venture Finance
• +۳ مورد دیگر

Dr. Dave Valliere is a Professor of Entrepreneurship and Business Strategy at Ryerson University's Ted Rogers School of Management, where he founded the Entrepreneurship Research Institute. With graduate degrees in both engineering (BASc, MEng) and business (MBA, PhD), he brings interdisciplinary expertise to his work. His 30+ years of industry experience spans technology, finance, and venture capital. Research Focus: Dr. Valliere's scholarship examines entrepreneurial ecosystems, cognitive psychology in venture creation, incubator development, and cross-cultural entrepreneurship. His work integrates behavioral science with practical venture development frameworks, particularly in technology commercialization contexts. Publications: Recent articles explore university business incubators (2020), mindfulness in entrepreneurship (2019), cross-cultural entrepreneurial logics (2017), and measurement of entrepreneurial intent (2017). His research consistently addresses both theoretical frameworks and practical applications in venture development. Awards & Honors: 2018 Best Paper Award (ICCI, Osaka) 2014 Senior Award (Coller Institute of Venture) 2014 Best Paper Award (IICIES Conference) 2012 Dean's Scholarly Research Award 2010 Dean's Teaching Award 2004 Best New Researcher Award 2002 Schulich Teaching Excellence Award Teaching & Advising: Dr. Valliere develops courses in venture financing, entrepreneurial behavior, and technology commercialization. He received teaching excellence awards from both Ryerson and York universities for his pedagogical innovations. Lab Leadership: As founder of the Entrepreneurship Research Institute, he directs investigations into entrepreneurial ecosystems and venture development processes, bridging academic research and industry practice.

David M Liebovitzمشاهده پروفایل

استاد

• Clinical Informatics
• Patient Safety
• Clinical Decision Support
• +۷ مورد دیگر

David M Liebovitz is Professor of Medicine (General Internal Medicine) and Preventive Medicine (Biostatistics and Informatics) at Northwestern University Feinberg School of Medicine, serving as Associate Vice Chair for Clinical Informatics and Co-Director of the Institute for Augmented Intelligence in Medicine - Center for Medical Education in Data Science and Digital Health. His clinical practice focuses on adult general internal medicine across inpatient and outpatient settings. His educational background includes: BS in Electrical Engineering, University of Illinois (1986) MD with Honors, University of Illinois (1990) Internal Medicine Internship, University of Chicago (1991) Internal Medicine Residency, University of Chicago (1993) Chief Resident, University of Chicago (1994) Dr. Liebovitz's research centers on clinical informatics with emphasis on patient safety through engineering principles. His work addresses clinical decision support , patient engagement , confidentiality preservation , and predictive analytics , focusing on user-centered EHR design to prevent alert fatigue and workflow disruptions that contribute to physician burnout. His electrical engineering background informs systems approaches to healthcare complexity. Recent publications (2025) reveal trends in digital health implementation science, including EHR-based HIV prevention interventions for women, pediatric long COVID outcomes research, and digital health education frameworks. These works demonstrate cross-cutting themes of data-driven clinical decision support and human factors engineering in healthcare technology adoption. Key honors include: John X. Thomas, Jr. Best Teachers of Feinberg Award (2022) AMIA Fellow (2019) Student Teaching Excellence Award (2007) Alpha Omega Alpha membership (1988) Tau Beta Pi Engineering Honor Society (1985) Dr. Liebovitz has held significant leadership roles including Chief Medical Informatics Officer at Northwestern Medical Faculty Foundation and Chief Medical Information Officer at University of Chicago Medicine. Current advisory positions include NCCN EHR Oncology Advisory Group (2024-present), UW-Madison Clinical Informatics Program Advisory Board (2020-present), and Illinois Prescription Monitoring Program Committee (2013-present). He actively shapes national policy through AMIA and AAMC committees focused on clinician well-being and EHR standards. As Co-Director of the Center for Medical Education in Data Science and Digital Health, he leads curriculum development integrating digital health competencies into medical education. His team develops data science training frameworks for future physicians, addressing critical needs in healthcare analytics and AI literacy through the Institute for Augmented Intelligence in Medicine.