Find Academic Supervisors

• Clinical Trials
• Randomized Controlled Trials
• Bayesian Statistics
• +8 more

Dr. Guangyu Tong is an Assistant Professor of Cardiovascular Medicine at the Yale School of Medicine with a secondary appointment as Assistant Professor of Biostatistics at the Yale School of Public Health. He directs the Cardiovascular Medicine Analytics Center (CMAC), providing critical analytic support for Yale's cardiovascular research community. Dr. Tong maintains faculty affiliations with multiple interdisciplinary centers including the Center for Methods of Implementation and Prevention Science (CMIPS), the Data Management and Statistics Core of the Alzheimer's Disease Research Center (ADRC-DMSC), the Center for Interdisciplinary Research on AIDS (CIRA), and the Interdepartmental Foci of Firearm Injury Prevention (FIP). His educational background includes a PhD from Duke University, an MA from Columbia University, and an AB from Peking University. Dr. Tong's research spans three major pillars: methodological innovation in trial design (particularly cluster randomized trials and stepped wedge designs), cardiovascular medicine applications, and firearm injury prevention research. His methodological contributions include advances in sample size estimation, treatment effect heterogeneity analysis, and complex trial designs with unequal cluster sizes. Dr. Tong's publications reveal a strong focus on translating statistical methods into clinical and public health applications. His work bridges Bayesian statistics with causal inference frameworks to address complex real-world problems like treatment effect heterogeneity in pragmatic trials and survivor average causal effects in studies with mortality outcomes. His research has appeared in top journals including Annals of Applied Statistics, Statistics in Medicine, and American Journal of Epidemiology. Faculty Scholar, National Institute on Aging's IMPACT Collaboratory (2023) Statistical Editor of the Journal of the American College of Cardiology (JACC) Associate Editor for BMC Medicine Principal Investigator on multiple NIH-funded trials As a senior statistician for the Great Smoky Mountain Study (GSMS), Dr. Tong examines how childhood exposures influence long-term mental health and firearm-related behaviors, directly informing policy debates around 'red flag' laws and age-based firearm restrictions. His collaborative work spans numerous NIH-funded projects including PULESA-UGANDA, TRANSFORM-HF, TRUE HAVEN, G4H, and iDOVE2.

Shivam GuptaView profile

Associate Professor

• Procurement
• Supplier Management
• Innovation Management
• +1 more

Shivam Gupta is an Associate Professor of Supply Chain Management and Analytics at the University of Nebraska-Lincoln's College of Business. He joined the university in 2018 as an Assistant Professor and was promoted to his current rank in 2024. His office is located in HLH 511K, Lincoln, NE. Education: Ph.D. in Management Science, The University of Texas at Dallas (2011-2016) M.Tech. in Civil Engineering, Indian Institute of Technology Kanpur (2009-2011) B.Tech. in Civil Engineering, Indian Institute of Technology Kanpur (2003-2007) His research expertise spans procurement systems, supplier relationship management, agricultural operations optimization, and incentive mechanism design. He develops analytical models to address challenges in supply chains, focusing on both theoretical frameworks and practical applications in agricultural markets. His work integrates game theory, optimization techniques, and economic analysis to solve complex operational problems. Gupta's publications demonstrate consistent focus on mechanism design and operational challenges, with recent work emphasizing dynamic incentive structures, procurement optimization, and agricultural policy impacts. His articles appear in premier journals including Management Science, Operations Research, and Production and Operations Management. Honors: First Place, INFORMS Public Sector OR Best Paper Competition (2015) Finalist, POMS SCM Student Paper Competition (2016) He teaches undergraduate and graduate courses in business analytics, including SCMA 350: Business Analytics/Information Analysis and SCMA 855: Prescriptive Analytics.

Hedvig Marie Egeland NordengView profile

Professor

• Perinatal Pharmacoepidemiology
• Pharmacotherapy in Pregnancy and Breastfeeding
• Neurodevelopmental Disorders
• +3 more

Hedvig Marie Egeland Nordeng is a Professor at the Department of Pharmacy, University of Oslo and an Adjunct Professor in Clinical Pharmacology at the Faculty of Health Sciences, University of Southern Denmark . She specializes in perinatal pharmacoepidemiology and medication safety during pregnancy , leading interdisciplinary research projects across the Nordic region and globally. PhD in Pharmacoepidemiology (2005), University of Oslo MSc in Pharmacy (1997), University of Oslo Her research focuses on neurodevelopmental outcomes , childhood cancer risks , and pharmacovigilance following prenatal and postnatal drug exposure. She develops machine learning pipelines for real-world data analysis and leads the iAPOGEE and UIORealArt convergence environments. Recent publications span registry-based studies on antidepressants, antiseizure drugs, and COVID-19 vaccine safety in pregnancy. She holds a ERC Starting Grant and has received multiple awards, including the Women's Research Award (2023) and Pharmacist of the Year (2016). Editor of clinical pharmacology textbook for nurses Head of PharmacoSafe Research Group Contributor to Norwegian Drug Formulary guidelines

• Industrial Engineering
• Operations Research
• Optimization
• +5 more

Shunichi Ohmori , a Professor at the Faculty of Science and Engineering , Waseda University , holds a Doctorate in Engineering from the same institution. His academic journey includes continuous affiliation with Waseda University since 2011, currently serving as a faculty member and concurrently as Director of Research Institute at the Institute of Global Production & Logistics (2022-2026). Education: Doctorate (2009-2012), Master's (2007-2009), and Bachelor's (2004-2007) from Waseda University His research focuses on industrial engineering and operations research , with specific interests in optimization , facility planning , logistics , and supply chain management . He has developed innovative frameworks for: Robust supply chain design under disruption risks Multi-echelon inventory optimization 3D facility layout planning with pipeline arrangements Collaborative vehicle routing cost allocation Green product portfolio strategies under uncertainty His publication record demonstrates expertise in stochastic optimization (15+ peer-reviewed papers) and heuristic algorithms (14+ conference proceedings). He has received multiple Best Paper Awards (2012-2016) and contributed to curriculum development through courses like Advanced Facilities Planning , Supply Chain Transformation , and Logistics at both undergraduate and graduate levels.

• Intellectual Disability
• Physical Activity
• Exercise Science
• +5 more

Josep Cabedo Sanromà is a Full Professor in the Department of Physical Activity and Sport Sciences and Sports Management at the Faculty of Psychology, Educational Sciences and Sports Blanquerna, Universitat Ramon Llull. His extensive research career spans intellectual disability, aging, physical activity, water polo performance analysis, and dance therapy for vulnerable populations. As a leading researcher in his field, he directs and participates in multiple significant research projects addressing critical health and sports science questions. Dr. Cabedo Sanromà's primary research interests focus on intellectual disability and exercise science, particularly examining how physical activity impacts aging populations with intellectual disabilities. His work with the IDEA study investigates cardiovascular and vascular modifications due to physical exercise in older adults with intellectual disabilities. He also conducts significant research in water polo performance analysis, examining positional effectiveness in numerical inequality situations. Additionally, his work explores creative dance therapy for Alzheimer's patients and motivational factors in charity sport events. His recent publications reveal a strong interdisciplinary approach combining exercise physiology, gerontology, and psychology. The research demonstrates consistent focus on vulnerable populations (individuals with intellectual disabilities, elderly, Alzheimer's patients) and performance analysis in water polo. His work often employs observational methodology, with significant use of statistical analysis including Chi-square tests. Dr. Cabedo Sanromà leads substantial research funding, most notably the SAFE project (Health, Physical Activity and Sport) funded by AGAUR (2022-2025), with a budget covering three and a half years of research. He collaborates extensively with researchers across multiple disciplines including psychology, medicine, and sports science, demonstrating strong interdisciplinary research capabilities. His work has significant practical applications for improving quality of life through physical activity interventions tailored to specific populations.

• Business Informatics
• Data Science
• Knowledge Engineering
• +6 more

Michael Schrefl is a Full Professor at Johannes Kepler University Linz, affiliated with the Institute of Business Informatics - Data & Knowledge Engineering. He serves as Principal Investigator on multiple research projects including AWARE (2024-2026) and AISA (2020-2022), and is actively involved in European research collaborations as both PI and researcher on funded projects. His research interests span across several key areas in modern data science and business informatics: Business Informatics and Digital Transformation Data Science and Knowledge Engineering Database Systems and Data Mining Semantic Technologies and Information Systems Predictive and Prescriptive Analytics Enterprise Computing and Information Systems Professor Schrefl's recent publication activity shows a strong focus on reliability assessment in predictive analytics, conceptual modeling for business intelligence, and applications of data science in Industry 4.0 contexts. His work bridges theoretical foundations with practical applications in enterprise information systems, particularly examining data quality and reliability in predictive models. As an active member of the academic community, Professor Schrefl serves on program committees for major conferences including BI-WEEK, EDOC, and DATA. He has supervised 129 students throughout his career and contributes to educational technology through projects like eTutor++. His research spans multiple fields of science including Knowledge Engineering, IT Security, Web Engineering, and Distributed Systems. Professor Schrefl maintains strong engagement with both academic and public discourse, having given invited talks on AI topics in 2024 and scheduled media appearances including an Ö1 interview on autonomous weapons systems for 2025, demonstrating his commitment to science communication and societal impact of technological developments.

• Digital Transformation
• Manufacturing Industry
• Intelligent Sensing Technology
• +5 more

Sun Yacheng is a Professor at the School of Economics and Management, Tsinghua University, where he actively contributes to research on digital transformation in the manufacturing sector. His expertise bridges economic theory and practical industrial applications. Professor Sun's research focuses on how intelligent sensing technology can drive digital transformation in manufacturing. His work particularly emphasizes the application of IoT, computer vision, and RFID technologies to create closed-loop systems of 'perception-analysis-decision-execution.' He investigates how high-precision 3D spatial reconstruction, end-to-end customer flow tracking, and multi-source data fusion can provide businesses with comprehensive market understanding and process optimization capabilities. His research shows how AI and machine learning can advance analytics from descriptive to predictive and prescriptive models, enhancing business decision-making. As part of Tsinghua School of Economics and Management's 'Two Sessions Through a Financial Perspective' series, Professor Sun provided expert analysis of the Government Work Report's call to accelerate digital transformation in manufacturing. He highlighted the strategic importance of cultivating service providers who understand both industry processes and digital technologies, with particular attention to the challenges facing small and medium enterprises in digital adoption.

• Physiotherapy
• Rehabilitation
• Telemedicine
• +4 more

Şeyda Ercan Yüceer serves as a Research Assistant at the Department of Physiotherapy and Rehabilitation within the Faculty of Health Sciences at Muğla Sıtkı Koçman University, Turkey, and holds concurrent affiliation with the Institute of Health Sciences at the same institution. Her academic credentials include: Bachelor's degree in Physiotherapy and Rehabilitation from Bolu Abant İzzet Baysal University, Kemal Demir School of Physical Therapy and Rehabilitation (2012-2016) Master's degree (MSc) in Physiotherapy and Rehabilitation from Süleyman Demirel University, Institute of Health Sciences (2017-2020) Ongoing doctoral studies in Physiotherapy and Rehabilitation at Muğla Sıtkı Koçman University, Institute of Health Sciences (2020-present) Her research spans telemedicine applications, AI integration in rehabilitation, geriatric physiotherapy, pelvic functional anatomy, and pandemic-related physical activity impacts. Recent publications demonstrate consistent focus on technology-enhanced rehabilitation methodologies and pandemic health consequences, with increasing emphasis on AI-driven solutions and specialized clinical applications since 2020. Her work bridges traditional physiotherapy with digital innovation, particularly in neurological rehabilitation and geriatric care. Dr. Yüceer has contributed as a researcher to three significant national projects: the 1st National Trakya University Physical Activity Symposium (2020-2021), Supporting Neurological Rehabilitation Through Technology-Based Methods (2019-2021), and the 1st International Balkan Prosthetics and Orthotics Symposium (2019-2020). These projects reflect her commitment to advancing rehabilitation science through technological integration and interdisciplinary collaboration. Her scholarly output extends to book chapters and translations that enhance educational resources in proprioceptive neuromuscular facilitation, geriatric rehabilitation principles, and pelvic anatomy, demonstrating active knowledge translation within the physiotherapy community.

David M LiebovitzView profile

Professor

• Clinical Informatics
• Patient Safety
• Clinical Decision Support
• +7 more

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.

Theresa MadreiterView profile

Lecturer

• Knowledge-based maintenance
• Predictive and prescriptive maintenance
• Knowledge discovery from text
• +5 more

Theresa Madreiter is a Lecturer & Doctoral Student at the Institute of Management Sciences within the Faculty of Mechanical Engineering and Industrial Management at Vienna University of Technology (Technische Universität Wien). Her research focuses on Production and Maintenance Management, where she combines engineering expertise with data science approaches to advance industrial maintenance practices. Her educational background includes: Dipl.-Ing. in Industrial Engineering and Mechanical Engineering from the Faculty of Mechanical Engineering and Industrial Management, Vienna University of Technology BSc. in Industrial Engineering and Mechanical Engineering from the Faculty of Mechanical Engineering and Industrial Management, Vienna University of Technology Madreiter's research interests center on knowledge-intensive approaches to industrial maintenance. She explores how knowledge-based maintenance , predictive and prescriptive maintenance systems , and knowledge discovery from text can transform traditional maintenance practices. Her work leverages semantic technology and Natural Language Processing to extract valuable insights from maintenance documentation, and applies predictive data analysis and machine learning techniques to anticipate equipment failures before they occur. This interdisciplinary approach bridges the gap between industrial engineering and data science, positioning her at the forefront of Maintenance 4.0 research. Her publications demonstrate a strong focus on applying text mining and AI techniques to industrial maintenance challenges. The trend in her work shows increasing sophistication in combining multiple data sources (both structured sensor data and unstructured text documentation) to create comprehensive maintenance solutions. Her research spans both theoretical development of algorithms and practical implementation in manufacturing environments, with a particular emphasis on discrete manufacturing systems. Madreiter's scientific achievements have been recognized with several prestigious awards: Schnieder Prize YOUNG MAKER 2021 from acatech Industrial Management - Thesis Award 2020 from Austrian Association for the Promotion of Business Research and Education Best Paper Award for "Combining process monitoring with text mining for anomaly detection in discrete manufacturing" at the Conference on Learning Factories 2022 As a doctoral student and lecturer, Madreiter is actively involved in academic mentoring and education. Her master's thesis on "Design and Development of a Prototype of a Text Understanding Tool for Maintenance 4.0" has served as the foundation for her current doctoral research and multiple research projects including TU-MARS, True_Usage, DigiMain 4.0, and DigiTS-ME. Beyond her formal academic role, she demonstrates significant commitment to social causes through her work with the Computerclubhouse Vienna (CCV), where she leads technology workshops for children from disadvantaged backgrounds. Madreiter is part of research teams working on the intersection of industrial engineering and data science, particularly focused on how AI and text analytics can transform maintenance practices in manufacturing. Her work connects closely with Industry 4.0 initiatives and represents an important bridge between traditional engineering disciplines and emerging data-driven approaches.

• Machine Learning
• Data Analytics
• Social Media Analysis
• +5 more

Dr. Paraskevas Koukaras is an Academic Scholar at the International Hellenic University (IHU) and a Postdoctoral Research Associate at the Information Technologies Institute (ITI) of the Centre for Research and Technology - Hellas (CERTH), affiliated with the School of Science and Technology at IHU. His educational background includes: IT Engineer from the Department of Informatics, Alexander Technological Educational Institute of Thessaloniki (ATEI) PhD in Interdisciplinary data science methods using machine learning for enhanced knowledge acquisition from the School of Science and Technology, International Hellenic University (IHU) Dr. Koukaras' research spans social media analytics, energy systems, and machine learning. His work focuses on energy load forecasting and optimization, data analytics, information modeling, and graph mining in heterogeneous networks. He applies these techniques to address challenges in public health, financial markets, and building energy efficiency through prescriptive analytics. His recent publications (2020-2023) demonstrate a strong focus on applying machine learning to real-world problems, particularly in social media analysis for public health during the COVID-19 pandemic, energy forecasting, and fake news detection. His work consistently employs multi-model approaches leveraging both traditional and deep learning techniques across healthcare, finance, and energy domains. Dr. Koukaras has participated in major European research projects including eDREAM (H2020), DRIMPAC (H2020), PRECEPT, SmartWins, easySRI, and SMACCs, focusing on demand response technologies and energy ecosystems. He contributes to academic training through teaching courses in data science and computing despite no formal advisees being listed. He operates within interdisciplinary research teams at ITI/CERTH and IHU's School of Science and Technology, collaborating on AI applications for energy efficiency, healthcare support, and social media analytics in residential and industrial contexts.

• Quantitative Methods in Business Analytics
• Markov chains and stochastic modeling
• Machine Learning and Prescriptive analytics in Operations
• +4 more

Georgiou Andreas is a Professor in the Department of Business Administration at the University of Macedonia, directing the Master in Business Administration program and serving as academic staff for the Master in Information Systems and Master in Business Analytics and Data Science programs. He earned his B.Sc. in Mathematics (1984) and Doctorate in Operations Research (1989) from Aristotle University of Thessaloniki. His research spans Quantitative Methods in Business Analytics, stochastic modeling, Machine Learning for Operations, Healthcare Simulation, and Multiple Criteria Optimization including AHP and DEA efficiency evaluation. He applies these techniques to solve complex business problems in operations management, marketing, and healthcare decision-making. Professor Georgiou teaches graduate courses including Operations Research, Decision Analysis and Optimization, Simulation Techniques in Business Analytics, and Quantitative Analysis for Business Decisions across multiple programs. With an extensive publication record of 13 books, 36 journal articles, 50 conference papers, and 41 other scholarly works, he actively mentors students in the graduate programs he directs.

Michael E ThompsonView profile

Associate Professor

• Community-driven problem identification
• Program development and evaluation
• Public health workforce development
• +3 more

Dr. Michael E. Thompson is an Associate Professor at the University of North Carolina at Charlotte's College of Health and Human Services, where he currently serves as Interim Chair of the Department of Health Management and Policy (July 2024-June 2025). With over 20 years of academic leadership, he has directed multiple accredited programs including the CAHME-accredited MHA Program, CEPH-accredited MPH program, and Health Informatics programs. He previously served as Associate Director of the Academy for Population Health Innovation, a unique university-county partnership. His research focuses on three interconnected themes: Community-driven identification of health problems Program development and evaluation methodologies Professional workforce development in public health This work spans opioid prescribing practices, tuberculosis care models, community health assessments, and competency-based curriculum design. Education background: DrPH in Health Services Research & Evaluation, Johns Hopkins Bloomberg School of Public Health (2002) MS in Emergency Health Services Administration, University of Maryland (1988) BA in Biology, Johns Hopkins University (1986) Honors and awards: Staff Recognition Award (Johns Hopkins University, 1995) Elected to Delta Omega honorary society (2002) Phi Beta Delta International Scholars Honor Society (President 2013-2015) Founding member of Beta Phi Chapter of Delta Omega at UNC Charlotte National leadership positions in Delta Omega including President-elect (2023-2024) and President (2025-2026) Dr. Thompson maintains significant global engagement as Adjunct Associate Professor at American University of Armenia and former Visiting Associate Professor at King Saud University. He has led health workforce development initiatives in conflict zones and transitional economies including Pakistan, Lebanon, and Armenia.

• Social Epidemiology
• Health Inequalities
• Child and Family Health
• +2 more

Dr. William Ball is a Chancellor's Fellow in Social Epidemiology at Robert Gordon University's School of Health. As a quantitative researcher and Registered Nurse, he investigates health inequalities through causal inference methods applied to observational health data. His work focuses on child/family mental health and socioeconomic determinants of long-term health outcomes. Research Interests: Dr. Ball's research examines how health inequalities emerge and persist across the life course, with emphasis on mental health service access disparities among children and adolescents. Key themes include social epidemiology, counterfactual causal inference, mental health policy evaluation, and the impact of early-life socioeconomic exposures. Publication Focus: His 12+ publications (2020-2025) demonstrate consistent focus on mental health inequalities, vulnerable populations, and methodological rigor. Recent work analyzes emergency mental health presentations in adolescents, child protection register linkages, and pandemic impacts on clinical care. Publications employ diverse methods including record linkage studies, multi-cohort analyses, and policy evaluations. Professional Engagement: Dr. Ball actively contributes to public health discourse through video briefings and collaborative research networks. He is available for PhD supervision in health inequality topics and maintains an open science approach to research transparency.

• Telecommunications Engineering
• Telematics
• Distributed Systems
• +7 more

María Teresa Ariza Gómez serves as a Full Professor in the Department of Telematics Engineering at the University of Seville, where she has established herself as a leading researcher in telecommunications and educational technology. Her academic career spans over two decades of continuous research contributions and teaching innovation. Professor Ariza Gómez's research interests focus on Telematics Engineering , with specialization in Distributed Systems , CORBA/MMS protocols , and IoT applications . She has pioneered the integration of gamification techniques into engineering education through tools like Kahoot, and developed virtual learning environments that transform programming instruction. Her work bridges theoretical telecommunications concepts with practical industrial applications, particularly in vehicle telematics and service station management systems. Her publication record shows consistent output with recent emphasis on educational technology (2015-2019), including software architecture for health applications and virtual laboratory environments. These works demonstrate her ability to adapt telecommunications expertise to solve problems in diverse domains from healthcare to automotive systems. Professor Ariza Gómez maintains active research through multiple projects including the TIC-154 research group (with continuous funding since 2006) and industry collaborations on Android applications and payment systems for gas stations. Her teaching methodology emphasizes project-based learning , virtual laboratories , and game-based educational resources that enhance student engagement in complex technical subjects. She leads research initiatives that combine telecommunications engineering with practical educational applications, creating innovative teaching tools that have been adopted across engineering disciplines at the University of Seville. Her work on virtualized computing environments has established a flexible, portable model that supports multidisciplinary teaching needs while maintaining technical rigor.