جستجوی استاد راهنمای دانشگاهی

Stephanie B. Wheelerمشاهده پروفایل

استاد

• Cancer
• Health disparities/health equity
• Social epidemiology
• +۵ مورد دیگر

Dr. Stephanie B. Wheeler is the Michael S. O’Malley Distinguished Professor in the Department of Health Policy and Management at the UNC Gillings School of Global Public Health. She serves as Associate Director of Community Outreach and Engagement at the UNC Lineberger Comprehensive Cancer Center and a Research Fellow at the UNC Center for Health Promotion and Disease Prevention. Her research focuses on cancer care delivery, health disparities, and systems science, with expertise in economic evaluation, simulation modeling, and large dataset analysis. Education: BA (Honors) in Theatre, College of Charleston, 2003 BS (Honors) in Biology, College of Charleston, 2003 MPH in Public Health and Family Medicine, University of Cape Town, 2007 PhD in Health Policy and Management, UNC-CH, 2010 Research Interests: Dr. Wheeler’s work addresses healthcare access, quality, value, and equity, particularly in cancer care. She uses methods like comparative effectiveness research, systems modeling, and 'big data' analytics to study cancer screening implementation, financial toxicity, and health policy interventions. Her projects are funded by NCI, the American Cancer Society, and CDC. Key Leadership Roles: Director of the Office of Community Outreach and Engagement, UNC Lineberger PI of the CDC-funded Cancer Prevention and Control Research Network Coordinating Center Co-Director of the NCI-funded T32 Cancer Care Quality Training Program Associate Editor, Journal of Clinical Oncology Awards: 2017 Hettleman Prize for Scholarly and Artistic Achievement 2017 ASPPH Early Career Award Grants & Projects: Leads/co-leads studies on colorectal cancer screening, financial navigation interventions, HPV vaccine communication, and cancer care quality surveillance. Her work emphasizes reducing disparities in rural and urban settings through evidence-based strategies. Labs & Teams: Active in the Gillings Innovation Labs and part of the Lineberger Equity Council, focusing on community-engaged research and policy translation.

Jessica Robertsمشاهده پروفایل

استادیار

• Learning Sciences & Technologies
• Geospatial Analysis
• Data Visualization
• +۶ مورد دیگر

Jessica Roberts is an Assistant Professor in the School of Interactive Computing at Georgia Tech. She holds a PhD in the Learning Sciences and directs the Technology-Integrated Learning Environments (TILEs) Lab. Her work focuses on technology-mediated learning in informal environments like museums and citizen science projects, emphasizing geospatial analysis, data visualization, and accessibility. Prior to academia, she was a middle school teacher. Education: PhD in Learning Sciences (specific institution not listed) Postdoctoral research at Carnegie Mellon University's Human-Computer Interaction Institute Postdoctoral work at Northwestern University's Tidal Lab Research Interests: Dr. Roberts explores how interactive technologies can foster inclusive, socially meaningful learning experiences. Her projects include: Data sonification systems for visually impaired audiences AI literacy frameworks for K-12 classrooms Citizen science platforms that democratize environmental data exploration Embodied interaction designs to enhance public engagement with scientific data Article Trends: Recent work highlights innovations in AI education, climate data visualization, and accessibility technologies. Over half of her 2023-2025 publications address data sonification systems for marginalized audiences or AI literacy challenges in K-12 contexts. Awards: Brook Byers Institute for Sustainable Systems Faculty Fellow Advising & Grants: Leads the TILEs Lab, which collaborates with institutions like the Field Museum of Natural History. Projects have been exhibited at major science museums, indicating significant external partnerships. Labs/Teams: Director of the TILEs Lab, affiliated with GVU Center at Georgia Tech. Collaborates with interdisciplinary teams across education, computer science, and environmental science domains.

Syeda Amna Sohailمشاهده پروفایل

مدرس

• Process Mining
• Data Privacy
• Metadata Management
• +۳ مورد دیگر

Syeda Amna Sohail is an Lecturer at the University of Twente , affiliated with the Public Administration school and the Datamanagement & Biometrics department. Her research focuses on process mining, metadata management, and privacy-preserving techniques in healthcare contexts. She actively contributes to interdisciplinary projects addressing ethical challenges in AI and data governance. Key research interests include: Data privacy in healthcare processes Process mining applications for metadata analysis Ontology-based frameworks for FAIR data principles Ethical AI and surveillance technologies Recent work highlights collaborations with institutions like CAiSE and VMBO workshops. She has presented at conferences such as the 33rd International Conference on Advanced Information Systems Engineering and delivered invited talks on privacy value modeling. Her research has been published in peer-reviewed venues including Lecture Notes in Computer Science and MDPI journals. Professional activities include organizing workshops, contributing to conference proceedings, and participating in multidisciplinary initiatives aligning with UN Sustainable Development Goals. Her work emphasizes practical solutions for balancing privacy and utility in healthcare data systems.

Li Songمشاهده پروفایل

استاد

• Building Energy System Optimization
• HVAC System Fault Detection
• Energy Efficiency Technology
• +۳ مورد دیگر

Li Song is a Professor and holds the Lesch Centennial Chair & Lloyd G. and Joyce Austin Presidential Professor at the University of Oklahoma's Aerospace & Mechanical Engineering Department. He leads the Building Energy Efficiency Lab and serves as AME Associate Director for Research. His expertise spans building energy systems, HVAC optimization, and fault detection technologies. Education: Ph.D. (Thermal/Fluid Science, 2004) from University of Nebraska-Lincoln; M.S. (Thermal/Fluid Science, 1996) from Harbin Institute of Technology; B.S. (Thermal Energy Systems, 1993) from Shengyang University of Civil Engineering and Architecture. Research focuses on energy-efficient HVAC systems, fault detection algorithms, and building performance analytics. Notable contributions include the ULEM-FDD system for high-performance buildings and virtual sensor technologies for airflow/water flow measurement. Awards include the ConocoPhillips Energy Prize (2011 finalist) and Bes-Tech Innovation Award (2006). Publications emphasize HVAC control strategies, energy modeling, and IoT-enabled diagnostics. Courses taught include Thermodynamics, Energy Efficient Building Systems Design, and HVAC Systems Engineering.

Kaiqun Fuمشاهده پروفایل

استادیار

• Spatial Data Mining
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Dr. Kaiqun Fu is an Assistant Professor in the McComish Department of Electrical Engineering and Computer Science at South Dakota State University (SDSU). He holds a Ph.D. and M.S. in Computer Science from Virginia Tech (2021 and 2016). His research focuses on spatial data mining, spatiotemporal event analysis, graph neural networks, and urban computing applications such as traffic impact prediction and social media-driven insights. He also explores physics-informed machine learning for power systems and interdisciplinary topics like 'deaths of despair' in rural areas. Education: Ph.D. in Computer Science, Virginia Tech, 2021 M.S. in Computer Science, Virginia Tech, 2016 Research Interests: His work emphasizes machine learning and deep learning applications in spatial-temporal domains, including: Graph neural networks for traffic incident prediction Social media analysis for urban challenges Physics-informed models for power grid stability Citation forecasting in scientific publications Grants & Projects: NSF CRII ($174,734): Spatiotemporal impacts of traffic events via graph neural networks (2024–2026) NSF EAGER ($300,000): Socio-economic impacts of emerging technologies (2024–2026) SDSU RSCA ($10,118): Graph transformer-based location learning (2023–2024) Professional Involvement: He chairs ACM SIGSPATIAL's SRC committee, serves on SDSU's Computer Science curriculum committees, and is an IEEE member. He co-edits Frontiers in Big Data and advises on interdisciplinary projects like climate-impacted grid security (NSF RII Track-2, $750,000). Labs/Teams: Collaborates with interdisciplinary groups focusing on smart cities, data-driven infrastructure resilience, and GeoAI applications.

Zohreh Shamsمشاهده پروفایل

پژوهشگر

• ML Interpretability
• Explainable AI
• Knowledge Discovery
• +۵ مورد دیگر

Zohreh Shams is a Visiting Fellow at the Computer Laboratory, University of Cambridge, and Chief Scientific Officer at Leap Labs. Previously, she served as a Senior Research Associate at the University of Cambridge and held roles at Babylon Health as a Senior ML Scientist. Her research focuses on ML interpretability, explainable AI, knowledge discovery, and automated reasoning with applications in healthcare and safety-critical systems. Dr. Shams completed her PhD in Artificial Intelligence at the University of Bath, specializing in explanatory decision-making in multi-agent systems using Argumentation Theory. Her work bridges cognitive science and AI, collaborating with institutions like the University of Brighton on projects such as Accessible Reasoning with Diagrams , which explores explainable ontology reasoning systems. Her research interests include generative modeling, concept-based representations, and the integration of domain knowledge into AI systems. Notable contributions include developing frameworks like CGXplain for neural network explanations and REM for healthcare data analysis. Her publications span venues such as ECCV, AAAI, and TMLR. Shams has contributed to interdisciplinary projects, including the Integrated Cancer Medicine initiative, and maintains affiliations with Wolfson College as a former Junior Research Fellow. Her work emphasizes ethical AI practices, clinician collaboration, and the societal impact of explainable AI systems.

• American Political Development
• US Public Policy
• Health Care Policy
• +۳ مورد دیگر

Andrew S. Kelly is an Assistant Professor in the Department of Public Health at California State University, East Bay. His research focuses on American political development and US public policy, particularly in health care, public health, and science policy. Dr. Kelly holds a PhD in Political Science from Northwestern University and has held postdoctoral positions at the University of California, Berkeley (as a Robert Wood Johnson Health Policy Research Scholar), Johns Hopkins University, and the University of California, San Francisco. His work appears in journals such as Health Affairs , Journal of Health Politics, Policy, and Law , and Publius: The Journal of Federalism . Key topics include Medicare-Medicaid dynamics, Affordable Care Act implementation, all-payer claims databases, and the political dimensions of healthcare pricing. Education: PhD in Political Science (Northwestern University) Awards: Robert Wood Johnson Health Policy Research Scholar Professional Experience: Postdoctoral roles at UC Berkeley, Johns Hopkins, and UCSF His research emphasizes intergovernmental policy innovation and the resilience of major healthcare programs amid political shifts. Grants and service activities are not detailed in the provided text.

Misa Faezipourمشاهده پروفایل

دانشیار

• System Dynamics Modeling
• Healthcare Systems Engineering
• Complex Systems Modeling
• +۳ مورد دیگر

Dr. Misa Faezipour is an Associate Professor in the Department of Engineering Technology at Middle Tennessee State University (MTSU) and director of the Systems Engineering Lab (SEL). She holds a Ph.D. and M.Sc. in Industrial Engineering and Engineering Management from the University of Texas at Arlington and a B.Sc. in Software Engineering from Islamic Azad University North Tehran Branch. Her research focuses on system dynamics modeling, healthcare systems engineering, complex systems, and sustainability optimization. Dr. Faezipour has advised numerous graduate students in M.S. and Ph.D. programs, focusing on topics such as healthcare disparities, AI robustness, and policy impact analysis. She teaches courses including Engineering Economy, Operations Management, and Engineering Management Systems. Her work spans collaborations with institutions like NASA, the Systems Engineering Research Center, and healthcare organizations. Her recent publications emphasize AI-driven healthcare solutions, system dynamics applications in policy analysis, and optimizing healthcare delivery through data-driven models. She actively contributes to professional organizations such as INCOSE, IEEE, and the System Dynamics Society. Dr. Faezipour’s lab, SEL, develops innovative tools for healthcare informatics, including diagnostic recommenders and policy simulation frameworks. Her research bridges systems engineering with healthcare challenges, addressing issues like racial health inequities and pandemic response strategies.

• Food Science
• Nutrition
• Functional Foods
• +۷ مورد دیگر

Alberta N.A. Aryee, PhD is an Associate Professor in the Department of Human Ecology (Food Science & Biotechnology) at Delaware State University (DSU). She holds a PhD from McGill University and completed postdoctoral research at Agriculture and Agri-Food Canada. Her research focuses on the impact of natural products and bioactive compounds on nutrition, health, and metabolic diseases, with particular emphasis on food processing effects, functional food development, and biofortification strategies. Education: Postdoctoral Research: Agriculture and Agri-Food Canada PhD: McGill University (Dissertation: Enzyme Immobilization and Biodiesel Production) MSc: McGill University (Thesis: Lipase Purification) BSc (Hons): Kwame Nkrumah University of Science and Technology Research Interests: Food science, functional ingredients, nutraceuticals, fermentation science, lipid technology, and sustainable food systems. She explores how processing impacts food matrices, bioavailability of nutrients, and the application of nanotechnology and machine learning in food analysis. Recent Research Trends: Her work spans encapsulation of bioactives, plant-based food innovation, and leveraging AI for nutrient prediction. Studies include optimizing hempseed processing, analyzing fermented cassava chemistry, and designing smart food packaging. Awards: 2020 DSU Faculty Excellence in Research 2018 Hornet Award (Early College High School) Mini Grant for hands-on food science education Advising & Grants: Mentors students in food chemistry and product development. Collaborates on grants focused on value-added food products from agricultural byproducts. Leads experiential learning programs integrating global food challenges. Labs & Teams: Based in DSU’s Baker Annex, her lab focuses on lipid science and functional food formulation. Collaborates with industry partners on sustainable food technologies and nanodelivery systems.

• Nursing Research
• Global Health
• HIV/AIDS Care
• +۳ مورد دیگر

Jennifer Gray, Ph.D., is the Dean of the College of Sciences and Education at Oklahoma Christian University (OC) and holds the rank of Professor of Nursing. She has over four decades of experience in nursing, research, and education, with a focus on global health, HIV/AIDS care, and evidence-based practice. Her career includes roles as Associate Dean at the University of Texas at Arlington (UTA), where she developed courses and led international outreach programs in Uganda. She is a Fellow of the American Academy of Nursing (2013) and a Professor Emeritus of the UTA System (2015). Her research spans nursing education, healthcare disparities, and international collaboration, with notable work in Africa. She co-authors influential nursing research textbooks, including Burns & Grove’s The Practice of Nursing Research . Education: BSN from the University of Central Oklahoma (1977), Master’s and Ph.D. from UTA (1989–1993). She has pioneered nurse-led interventions in hypertension, HIV/AIDS, and maternal health in Uganda, Rwanda, and Tanzania. Her leadership emphasizes innovation in education and maintaining OC’s mission-driven values. She also advocates for healthcare workforce development and healthy work environments in acute care settings. Awards include her American Academy of Nursing Fellowship and recognition for her textbook contributions. She has supervised numerous research initiatives and serves in her church community. Her work bridges academic rigor with practical, community-focused healthcare solutions.

Rita Borgoمشاهده پروفایل

استاد

• Data Visualization
• Computer Science
• Human-Computer Interaction
• +۴ مورد دیگر

Dr Rita Borgo is a Professor in Data Visualization and Head of the Human Centred Computing Group at King's College London's Department of Informatics. She holds a leadership role within the Faculty of Natural, Mathematical & Engineering Sciences and is affiliated with the Centre for Urban Science and Progress (CUSP) London. Her research focuses on interdisciplinary visualization challenges, including human-computer interaction, AI trust calibration, and epidemiological modeling. Education details are not explicitly stated in the provided text. Her work spans over 58 publications, emphasizing visualization techniques for large datasets, trust in AI systems, and urban science applications. Key projects include RAMPVIS (visual analytics for pandemic response) and Trusted Autonomous Systems Hub (AI ethics and human-machine partnerships). Research interests include data visualization, human factors, generative AI, and policy simulation. Recent articles explore trust calibration in AI, time-series visualization, and ethical clinical decision support systems. She has led grants totaling £multi-million, including EPSRC-funded initiatives. Collaborations with organizations like ContactEngine Limited highlight her industry engagement. Labs/Teams: Leads the Human Centred Computing Group and contributes to CUSP's urban data initiatives. Supervised student work includes a notable BSc thesis by Munkhtulga Battogtokh. Current projects address visualization in nuclear policy, social media mental health correlations, and trustworthy autonomous systems.

Hui Luanمشاهده پروفایل

استادیار

• Spatial Epidemiology
• Bayesian Spatiotemporal Statistics
• Geographical Information Science (GIS)
• +۴ مورد دیگر

Hui Luan is an Assistant Professor in the Department of Public Health at the Peter O’Donnell Jr. School of Public Health, UT Southwestern Medical Center. He joined UT Southwestern in 2024 after serving as an Associate Professor (tenured) at the University of Oregon (2018–2024). His research focuses on spatial epidemiology, Bayesian spatiotemporal statistics, and GIS applications to address health disparities and environmental determinants of disease. Education: Ph.D. in Planning, University of Waterloo, 2017 M.S. in Cartography and GIS, Wuhan University, 2011 B.S. in GIS, Wuhan University, 2009 Research Interests: Dr. Luan investigates spatial and temporal variations in health outcomes, particularly HIV incidence, and the role of social, physical, and built environments. He develops Bayesian models and spatial analytics to inform geographically tailored interventions. Current projects include optimizing PrEP accessibility, analyzing food environment equity, and leveraging spatial data science for public health policy. Key Achievements: Lead investigator of an NIH-funded R01 project on reducing HIV incidence via spatial data science Editorial board member of Spatial and Spatiotemporal Epidemiology Recipient of the Vu Fellowship (2021–22) Teaching: Teaches courses on GIS in Public Health, Spatial Analysis, and Big Data applications in geography. Recent courses include GIS and Public Health and Spatial and Spatiotemporal Analysis at the University of Oregon. Labs/Teams: Leads the Spatial Data Science Lab focused on advancing Bayesian methods for health data analysis and promoting GIS applications in public health practice.

• Meta-Research
• Obesity Disparities
• Systematic Reviews
• +۶ مورد دیگر

Dr. Kathryn Kaiser is an Assistant Professor in the Department of Health Behavior at the University of Alabama at Birmingham (UAB) School of Public Health. She holds concurrent appointments in multiple research centers including the Center for Clinical and Translational Science and the Nutrition Obesity Research Center (NORC). Her research focuses on meta-research methodologies, race/sex disparities in obesity, systematic reviews of nutrition interventions, and advancing FAIR data principles for scientific communication. Education: B.S. Microbiology (Texas A&M), B.S. Medical Technology (University of Texas Health Science Center), Ph.D. in Health Psychology (University of North Texas Health Science Center). Postdoctoral training in Vascular Biology/Hypertension at UAB. Extensive background in medical diagnostics instrumentation and laboratory science prior to academia. Research Interests: Systematic review methodologies, FAIR data standards, obesity disparities with a focus on neuroendocrine mechanisms, and translational research in bariatric surgery outcomes. Specializes in methodological rigor for clinical trials and evidence synthesis. Grants: NIH-funded projects on FAIR principles implementation, dairy intake research, obesity energetics, and lifespan studies. Recent grants include $2.1M for metadata education programs and $1.8M for knowledge mapping initiatives. Awards: Recognized as 2015 Top Reviewer for American Journal of Preventive Medicine. Serves as Associate Editor for Frontiers in Nutrition. Active member of Cochrane Collaboration and multiple professional societies. Teaching: Graduate courses in Health Program Evaluation, Psychophysiology, and Systematic Review Design. Supervises doctoral students in health behavior research through 30+ dissertation committees since 2011. Labs/Teams: Key contributor to UAB's Nutrition Obesity Research Center (NORC) and Center for Outcomes and Effectiveness Research (COERE). Collaborates with international metadata initiatives like Metadata 2020 and science dialogue mapping projects.

Yingying Chenمشاهده پروفایل

استاد

• Smart Healthcare
• Internet of Things (IoT)
• Cyber Security
• +۷ مورد دیگر

Yingying (Jennifer) Chen is a Distinguished Professor and Department Chair in the Department of Electrical and Computer Engineering at Rutgers University, affiliated with the Wireless Information Network Laboratory (WINLAB) and the DAISY Lab. She holds a PhD in Computer Science from Rutgers University (2007). Her research focuses on Smart Healthcare, IoT, Cyber Security, Machine Learning, and AR/VR Security, with over 300 publications and multiple patents. Key roles include Associate Director of WINLAB, Fellow of ACM, IEEE, and AAIA, and recipient of the NSF CAREER Award (2010), Henry Morton Teaching Award (2017), and ACM Distinguished Scientist distinction. Awards also include the 2024 ACM Fellow and NAI Fellow (2022). Her work emphasizes interdisciplinary applications, such as AR/VR privacy attacks, adversarial machine learning defenses, and edge computing. Notable grants include NSF projects on AI on edge devices, NextG-enabled manufacturing, and healthcare system design. She advises Ph.D. students and collaborates with industry on testbeds like the Community-based Edge Sensing Testbed (NSF CCRI). Current research explores AI-driven sensing, privacy in immersive technologies, and robust multi-model analytics. Publications span top venues like ACM MobiCom, IEEE INFOCOM, and IEEE S&P. Labs include DAISY Lab (data analysis & security) and collaborations with WINLAB for wireless innovation. She serves on editorial boards of IEEE/ACM Transactions and organizes conferences like ACM MobiCom and IEEE ICDCS.

Enkelejda Mihoمشاهده پروفایل

استاد

• Digital Life Sciences
• Medical Informatics
• Artificial Intelligence in Healthcare
• +۴ مورد دیگر

Prof. Enkelejda Miho is a Professor of Digital Life Sciences at the School of Life Sciences, FHNW, leading the aiHealthLab. Her work bridges computer science/AI with life sciences, focusing on drug discovery, personalized medicine, and immunology. She holds roles as Team Leader at aiHealthLab and Group Leader at the Swiss Bioinformatics Institute. Research Interests : She applies machine learning to analyze immune repertoires, antibody engineering, and autoimmunity diagnostics. Her lab develops computational tools like the RWD-Cockpit for real-world data analysis and synthetic antibody-antigen models (Absolut!) to advance biotherapeutics. Her work on dengue immunity and monoclonal gammopathies highlights translational applications. Key Projects : The aiHealthLab focuses on AI-driven diagnostics and therapeutics. Her contributions include AI frameworks for antibody specificity prediction, age-related immune repertoire changes, and large-scale network analysis of antibody repertoires. Labs/Teams : Leads aiHealthLab and collaborates with the Swiss Bioinformatics Institute, integrating computational and experimental immunology.