Professor at Texas Tech University Health Sciences Center, United States
Dr. Hafiz M. R. Khan is a Full Professor of Biostatistics at Texas Tech University Health Sciences Center, with an extensive academic and research background. He holds a Ph.D. in Statistics from the University of Western Ontario and has postdoctoral training in Bioinformatics. His career spans multiple institutions, including Florida International University and the University of Medicine & Dentistry of New Jersey. Dr. Khan has held leadership roles such as Associate Chair and Director of Outcome Measures, contributing significantly to academic committees and research initiatives. He has published extensively in peer-reviewed journals, focusing on biostatistics, public health, and cognitive impairment research. His strengths for the Best Researcher Award include a strong publication record, leadership in academia, and interdisciplinary collaboration. Areas for improvement may include further engagement in international research projects. Overall, his contributions to biostatistics and public health research make him a strong candidate for the Best Researcher Award.
Professional ProfileĀ
Education
Dr. Hafiz M. R. Khan has a strong educational background in statistics and biostatistics. He earned his Ph.D. in Statistics from the University of Western Ontario, Canada, where he specialized in statistical methodologies and their applications in health sciences. To further enhance his expertise, he completed postdoctoral training in Bioinformatics, gaining advanced knowledge in computational biology and data analysis. His academic journey also includes a Masterās and Bachelorās degree in Statistics, which provided him with a solid foundation in quantitative analysis and research methods. Throughout his education, Dr. Khan focused on interdisciplinary applications of statistics, particularly in public health, epidemiology, and biomedical sciences. His strong academic credentials have enabled him to contribute significantly to research, teaching, and mentoring students in biostatistics and public health. His education has played a pivotal role in shaping his career, allowing him to bridge the gap between statistical theory and real-world health applications.
Professional Experience
Dr. Hafiz M. R. Khan has an extensive professional background in statistics, biostatistics, and public health research. He has held various academic and research positions, contributing significantly to statistical methodologies in biomedical and epidemiological studies. As a professor and researcher, he has taught biostatistics, data analysis, and public health courses at reputable institutions, mentoring numerous students and professionals. His expertise extends to consulting for healthcare organizations and research institutions, where he applies statistical models to solve complex health-related problems. Dr. Khan has also collaborated on interdisciplinary projects involving bioinformatics, machine learning, and predictive analytics in healthcare. His professional journey includes publishing high-impact research papers, serving as a peer reviewer for scientific journals, and participating in international conferences. His work has been instrumental in advancing statistical applications in medicine and public health, bridging the gap between theoretical research and practical implementation in real-world health challenges.
Research Interest
Dr. Hafiz M. R. Khan’s research interests lie at the intersection of biostatistics, epidemiology, and public health, with a strong focus on statistical modeling, predictive analytics, and machine learning applications in healthcare. He is particularly interested in developing advanced statistical methodologies to analyze complex biomedical data, improve disease prediction models, and enhance public health decision-making. His work explores the integration of statistical techniques with bioinformatics to study genetic influences on diseases and health outcomes. Additionally, he investigates the application of artificial intelligence in medical research, aiming to optimize diagnostic accuracy and treatment effectiveness. Dr. Khan is also passionate about global health issues, including infectious disease surveillance, health disparities, and aging populations. Through interdisciplinary collaborations, he strives to bridge the gap between statistical theory and real-world healthcare applications, contributing to innovative solutions that enhance patient care, policy-making, and public health interventions worldwide.
Award and Honor
Dr. Hafiz M. R. Khan has received numerous awards and honors in recognition of his outstanding contributions to biostatistics, public health, and epidemiology. He has been honored with prestigious research grants and fellowships from esteemed institutions, highlighting his excellence in statistical modeling and healthcare analytics. His groundbreaking work has earned him accolades such as the Best Researcher Award and Excellence in Public Health Research recognition. Dr. Khan has been invited as a keynote speaker at international conferences and has received distinguished scholar awards for his impactful publications. His dedication to academic excellence has also been acknowledged through teaching awards, mentoring recognitions, and leadership roles in professional organizations. Additionally, he has been recognized for his contributions to global health initiatives, demonstrating his commitment to improving healthcare outcomes. These awards and honors underscore his influence in the field and his continuous efforts to advance research, education, and policy in health sciences.
Research Skill
Dr. Hafiz M. R. Khan possesses exceptional research skills in biostatistics, public health, and epidemiology, enabling him to conduct advanced statistical analyses and develop innovative models for healthcare studies. His expertise includes data analysis, predictive modeling, machine learning applications in health research, and designing population-based studies. He has a strong command of statistical software such as R, SPSS, SAS, and STATA, which he utilizes to interpret complex datasets effectively. Dr. Khan excels in systematic reviews, meta-analysis, and quantitative research methodologies, ensuring rigorous scientific inquiry and evidence-based conclusions. His ability to synthesize large datasets and extract meaningful insights has contributed significantly to policy recommendations and healthcare improvements. Additionally, his collaborative approach to interdisciplinary research allows him to work seamlessly with experts from diverse fields. His critical thinking, problem-solving abilities, and meticulous research design skills make him a valuable contributor to advancing public health, epidemiology, and statistical sciences.
Conclusion
Dr. Hafiz M. R. Khan is a highly qualified candidate for the Best Researcher Award due to his extensive contributions to academia, research, and public health. His leadership roles, mentoring, and commitment to advancing Biostatistics make him a strong contender. However, enhancing visibility of research impact, citations, international collaborations, and applied innovations could further strengthen his application.
Publications Top Noted
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Title: Metabolic syndrome in aboriginal Canadians: prevalence and genetic associations
Authors: RL Pollex, AJG Hanley, B Zinman, SB Harris, HMR Khan, RA Hegele
Year: 2006
Citations: 145
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Title: Differences between carotid wall morphological phenotypes measured by ultrasound in one, two and three dimensions
Authors: K Al-Shali, AA House, AJG Hanley, HMR Khan, SB Harris, …
Year: 2005
Citations: 142
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Title: Genetic Variation in PPARG Encoding Peroxisome Proliferator-Activated Receptor Ī³ Associated With Carotid Atherosclerosis
Authors: KZ Al-Shali, AA House, AJG Hanley, HMR Khan, SB Harris, B Zinman, …
Year: 2004
Citations: 123
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Title: GuillaināBarrĆ© syndrome after Gardasil vaccination: data from vaccine adverse event reporting system 2006ā2009
Authors: N Souayah, PA Michas-Martin, A Nasar, N Krivitskaya, HA Yacoub, …
Year: 2011
Citations: 120
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Title: Type 2 diabetes and its correlates among adults in Bangladesh: a population-based study
Authors: MAB Chowdhury, MJ Uddin, HMR Khan, MR Haque
Year: 2015
Citations: 110
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Title: Physical therapistsā attitudes, knowledge, and practice approaches regarding people who are obese
Authors: S Sack, DR Radler, KK Mairella, R Touger-Decker, H Khan
Year: 2009
Citations: 78
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Title: Trends in outcomes and hospitalization costs for traumatic brain injury in adult patients in the United States
Authors: K Farhad, HMR Khan, AB Ji, HA Yacoub, AI Qureshi, N Souayah
Year: 2013
Citations: 56
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Title: Predictive inference from a two-parameter Rayleigh life model given a doubly censored sample
Authors: HMR Khan, SB Provost, A Singh
Year: 2010
Citations: 49
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Title: Optimizing RNA extraction yield from whole blood for microarray gene expression analysis
Authors: J Wang, JF Robinson, HMR Khan, DE Carter, J McKinney, BA Miskie, …
Year: 2004
Citations: 48
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Title: Secondhand smoke exposure reduction intervention in Chinese households of young children: a randomized controlled trial
Authors: AS Abdullah, F Hua, H Khan, X Xia, Q Bing, K Tarang, JP Winickoff
Year: 2015
Citations: 45
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Title: Statistical machine learning approaches to liver disease prediction
Authors: F Mostafa, E Hasan, M Williamson, H Khan
Year: 2021
Citations: 40
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Title: The safety profile of home infusion of intravenous immunoglobulin in patients with neuroimmunologic disorders
Authors: N Souayah, A Hasan, HMR Khan, HA Yacoub, M Jafri
Year: 2011
Citations: 34
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Title: Tumor-infiltrating lymphocytes (TILs) as a biomarker of abscopal effect of cryoablation in breast cancer: A pilot study
Authors: SY Khan, MW Melkus, F Rasha, M Castro, V Chu, L Brandi, H Khan, …
Year: 2022
Citations: 31
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Title: Vulnerability prioritization, root cause analysis, and mitigation of secure data analytic framework implemented with MongoDB on Singularity Linux containers
Authors: AM Dissanayaka, S Mengel, L Gittner, H Khan
Year: 2020
Citations: 31
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Title: Colorectal cancer screening use among insured adults: Is out-of-pocket cost a barrier to routine screening?
Authors: A Perisetti, H Khan, NE George, R Yendala, A Rafiq, S Blakely, …
Year: 2018
Citations: 31
