Assist. Prof. Dr. Guanbo Wang | Biostatistics | Best Researcher Award

Assistant professor at The Dartmouth Institute, United States

Dr. Guanbo Wang is an Assistant Professor at The Dartmouth Institute for Health Policy and Clinical Practice and the Department of Biomedical Data Science, Dartmouth College. He specializes in biostatistics, causal inference, and machine learning, with a commitment to advancing statistical methodologies for improving public health. His work focuses on data integration, trial design, and personalized medicine using multi-source data such as randomized clinical trials and electronic health records. Dr. Wang holds a Ph.D. and M.Sc. in Biostatistics from McGill University, with research stints at Harvard University. He has collaborated with leading institutions like Harvard T.H. Chan School of Public Health, Biogen, and Roche, contributing to diverse therapeutic areas including cancer, cardiovascular diseases, and pediatric health. His academic contributions are evidenced by his prolific publication record and roles in high-impact research projects. Dr. Wang is also an active mentor, reviewer, and member of professional societies in statistics and epidemiology. 📊

professional profile

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Education

Dr. Guanbo Wang earned his Ph.D. in Biostatistics (2017–2022) and M.Sc. in Biostatistics (2015–2017) from McGill University, under esteemed mentors such as Robert Platt, Mireille Schnitzer, and Andrea Benedetti. His doctoral and master’s work emphasized causal inference, high-dimensional data, and clinical applications. He also completed a visiting scholar stint at Harvard University’s Department of Population Medicine in 2019, guided by Rui Wang. Currently, he is completing a Postdoctoral Fellowship (2022–2025) in Epidemiology at CAUSALab, Harvard T.H. Chan School of Public Health, mentored by Issa Dahabreh. His academic training integrates theoretical statistics with real-world medical challenges, contributing to a solid foundation in methodological development and applied health sciences. With additional statistical training from China, Dr. Wang’s global academic background uniquely equips him to tackle multifaceted health data challenges. 📘📈

Work Experience

Dr. Wang’s professional journey spans academia, industry, and collaborative health research. Since 2023, he has served as a research collaborator at Harvard’s CBAR on pediatric HIV/AIDS studies. Previously, he interned at Genentech/Roche, where he augmented early-phase oncology trials using external data. He consulted for Biogen on machine learning in neurology and supported various clinical research projects at McGill-affiliated hospitals. Earlier roles include internships with firms such as KPMG, AXA Insurance, and the National Bureau of Statistics of China, where he developed analytics and business strategies. Dr. Wang has also taught graduate courses and mentored students at McGill and Harvard. These experiences reflect his ability to bridge complex statistical theory with practical solutions in both research and corporate settings. 🏥📊

Awards and Honors

Dr. Wang has earned widespread recognition through prestigious awards and fellowships reflecting his scholarly excellence. He is a co-investigator on the $31M PCORI-funded RAPTOR-CIED project, supporting cardiac device care optimization. He was awarded the FRQS Doctorate Fellowship (2019–2022), valued at CAD 70,000, for his work on machine learning in anticoagulant effectiveness. Additional honors include the Research Institute of MUHC Fellowship (CAD 9,125), Harvard Pilgrim Fellowship (USD 4,000), and the CRM StatLab Award. Dr. Wang has also received the McGill Graduate Excellence Award (CAD 40,227), the McGill GREAT Award, and travel grants from the Statistical Society of Canada. His competitive success in acquiring NIH and CIHR funding as a trainee and collaborator further reflects his leadership in health data science. These distinctions underscore his impact on high-stakes research, statistical innovation, and mentorship within interdisciplinary academic and clinical communities. 🏆📑

Research Focus

Dr. Wang’s research lies at the intersection of causal inference, machine learning, and health policy. He focuses on developing robust statistical methods for data integration—particularly combining randomized controlled trials with real-world data sources to generate generalizable and actionable evidence. In personalized medicine, his work aims to evaluate treatment heterogeneity by leveraging multi-source longitudinal datasets and time-to-event outcomes. He also develops advanced methods for complex clinical trial designs, including adaptive, early-phase, and cluster-randomized trials. Another research stream explores how to incorporate prior clinical knowledge into high-dimensional prediction models to improve interpretability and clinical relevance. Methodologically, Dr. Wang draws on non/semi-parametric statistics, optimization, survival analysis, and computational methods. His work addresses diseases across pediatrics, oncology, cardiology, infectious diseases, and mental health. With a mission to inform precision health decisions, Dr. Wang’s research supports a deeper understanding of treatment effects across diverse populations and care settings. 🧬🧠📉

Conclusion

Dr. Guanbo Wang is an exceptional candidate for the Research for Best Researcher Award. His profile demonstrates a rare blend of theoretical innovation, real-world applicability, and academic leadership. His interdisciplinary and collaborative approach, especially in causal inference for healthcare, aligns perfectly with the award’s objectives to recognize researchers who push the boundaries of impactful, rigorous science.

Publications to Noted

Title: Causal inference with multiple concurrent medications: A comparison of methods and an application in multidrug-resistant tuberculosis
Authors: AA Siddique, ME Schnitzer, A Bahamyirou, G Wang, TH Holtz, GB Migliori, …
Citations: 31
Year: 2019

Title: Estimating treatment importance in multidrug-resistant tuberculosis using Targeted Learning: An observational individual patient data network meta-analysis
Authors: G Wang, ME Schnitzer, D Menzies, P Viiklepp, TH Holtz, A Benedetti
Citations: 18
Year: 2020

Title: Using Effect Scores to Characterize Heterogeneity of Treatment Effects
Authors: G Wang, PJ Heagerty, IJ Dahabreh
Citations: 17
Year: 2024

Title: Modeling treatment effect modification in multidrug-resistant tuberculosis in an individual patient data meta-analysis
Authors: Y Liu, ME Schnitzer, G Wang, E Kennedy, P Viiklepp, MH Vargas, …
Citations: 11
Year: 2022

Title: Evaluating hybrid controls methodology in early-phase oncology trials: a simulation study based on the MORPHEUS-UC trial
Authors: G Wang, MP Costello, H Pang, J Zhu, HJ Helms, I Reyes-Rivera, RW Platt, …
Citations: 9
Year: 2023

Title: Predictive factors of detectable viral load in HIV-infected patients
Authors: A Bouchard, F Bourdeau, J Roger, VT Taillefer, NL Sheehan, M Schnitzer, G Wang, …
Citations: 9
Year: 2022

Title: Robust integration of external control data in randomized trials
Authors: G Wang, R Karlsson, JH Krijthe, IJ Dahabreh
Citations: 6
Year: 2024

Title: Penalized G-estimation for effect modifier selection in the structural nested mean models for repeated outcomes
Authors: A Jaman, G Wang, A Ertefaie, M Bally, R Lévesque, R Platt, M Schnitzer
Citations: 6
Year: 2024

Title: Combining an experimental study with external data: study designs and identification strategies
Authors: L Ung, G Wang, S Haneuse, M Hernán, I Dahabreh
Citations: 4
Year: 2024

Ms. Ghaliah Alfurayh | Health informatic | Best Research Article Award

Health Informatics Analyst at King Faisal Specialist Hospital & Research Centre (KFSHRC), Saudi Arabia

Ghaliah H. Alfurayh is a dedicated Health Informatics Analyst at King Faisal Specialist Hospital & Research Centre (KFSHRC), Riyadh. With over a decade of experience in digital health systems, she has contributed significantly to optimizing patient engagement and health data management. Holding a Master’s degree in Health Informatics, Ghaliah’s work bridges the gap between clinical practice and digital innovation. Her research explores the dynamics of patient portal usage, aiming to enhance communication, access, and overall healthcare outcomes. Known for her analytical acumen and collaborative spirit, she has been instrumental in various health informatics initiatives and research collaborations, including work with the King Saud bin Abdulaziz University for Health Sciences (KSAUHS). As a passionate advocate for eHealth integration, she envisions transforming Saudi Arabia’s healthcare system through technological empowerment, innovation, and evidence-based practice. Her ongoing contributions continue to support smarter, safer, and more responsive healthcare environments.

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ORCID

Education

Ghaliah H. Alfurayh holds a Master’s degree in Health Informatics, which forms the cornerstone of her professional career. Her academic foundation is strongly rooted in understanding how digital systems can elevate patient care, decision-making, and healthcare administration. Her graduate research, focused on the utilization of patient portals, reflected her keen interest in exploring how digital tools empower patients to actively manage their health and communication with providers. Her educational journey has included extensive training in medical data systems, information architecture, health policy informatics, and clinical decision support tools. Throughout her studies, she demonstrated exceptional dedication to integrating healthcare delivery with modern information systems. Ghaliah’s commitment to continued learning is evident in her engagement with current technologies, publications, and industry collaborations. Her education has prepared her to serve as a bridge between healthcare professionals and data-driven decision-making tools, with a consistent focus on patient-centered care.

work Experience

Ghaliah currently serves as a Health Informatics Analyst (HITA) at the prestigious King Faisal Specialist Hospital & Research Centre, Riyadh. With over 10 years of field experience, she has applied her expertise in digital healthcare systems to improve clinical workflows, data integration, and patient engagement platforms. Her work involves evaluating and optimizing the performance of patient portals and other electronic health record (EHR) systems, while ensuring compliance with health informatics standards and regulatory frameworks. She has collaborated on institutional research and consultancy projects aimed at improving healthcare services and implementing eHealth innovations. Ghaliah’s contributions span system implementation, data analytics, clinical decision support, and user experience optimization. Her hands-on involvement in training medical staff in digital systems also adds a vital human dimension to her role. Her professional journey reflects a seamless integration of technological fluency with a strong understanding of the healthcare environment, making her a valuable asset in the Saudi digital health ecosystem.

Research Focus

Ghaliah’s research interests are deeply rooted in Health Informatics, with a special emphasis on digital patient engagement platforms such as patient portals. Her master’s thesis explored how patients interact with these portals to manage their health, access medical records, schedule appointments, and communicate with care providers. This research is reflective of her broader aim to enhance patient autonomy, optimize healthcare communication, and promote technology-enabled healthcare systems. She is particularly interested in how data visualization, patient feedback systems, and real-time access to health information can improve patient satisfaction and clinical outcomes. Ghaliah also explores emerging trends in eHealth systems, interoperability standards, and healthcare data governance. Her work aligns with national digital transformation initiatives and aims to create more patient-centric, efficient, and data-driven care models. Collaborating with KFSHRC and KSAUHS, she continues to conduct impactful studies that contribute to the ongoing evolution of Saudi Arabia’s healthcare system.

Conclusion

Ghaliah H. Alfurayh is a strong candidate for the Best Research Article Award, particularly for early-career professionals or those in applied research categories. Her article addresses a critical area in healthcare modernization—patient engagement through digital platforms. While her academic portfolio is still growing, the quality and relevance of her current research, combined with her practical experience, clearly support her nomination. To further strengthen future applications, expanding publication volume, academic leadership roles, and cross-border research engagements is recommended.

Publications to Noted

“Feasibility of Using Patient Portal to Enhance Patient Engagement and Patient-Generated Data in Tertiary Hospital”

Authors: Ghaliah H. Alfurayh*, Abdullah T. Alanazi, Hanin S. Aldalham
Year of Publication: 2025
Journal: Healthcare
Volume and Issue: Volume 13, Issue 5
Article Number: 518

Guanbo Wang | Biostatistics | Best Researcher Award

Assist. Prof. Dr. Guanbo Wang | Biostatistics | Best Researcher Award

professional profile

Education

Work Experience

Awards and Honors

Research Focus

Conclusion

Publications to Noted

Ghaliah Alfurayh | Health informatic | Best Research Article Award

Ms. Ghaliah Alfurayh | Health informatic | Best Research Article Award

professional profile

Education

work Experience

Research Focus

Conclusion

Publications to Noted

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