Youping Deng, Ph.D., is currently the Director of Bioinformatics and Biostatistics, Associate Professor, Department of Internal Medicine and Biochemistry, Rush University Medical Center in Chicago. Dr. Deng received his Ph.D. from Peking Union Medical College. He used to be Associate Director of Bioinformatics, Mississippi Functional Genomics Network as well as adjunct Associate Professor in the Department of Computer Sciences of Georgia State University. From 2004 to 2008, he was a tenure track assistant professor at the University of Southern Mississippi. He has published more than 170 papers in peer-reviewed journals and is serving as editorial board members of 5 international
Youping Deng, Ph.D., is currently the Director of Bioinformatics and Biostatistics, Associate Professor, Department of Internal Medicine and Biochemistry, Rush University Medical Center in Chicago. Dr. Deng received his Ph.D. from Peking Union Medical College. He used to be Associate Director of Bioinformatics, Mississippi Functional Genomics Network as well as adjunct Associate Professor in the Department of Computer Sciences of Georgia State University. From 2004 to 2008, he was a tenure track assistant professor at the University of Southern Mississippi. He has published more than 170 papers in peer-reviewed journals and is serving as editorial board members of 5 international journals. My research interest is bioinformatics, biostatistics, computational biology, biomedical informatics, and genomics.
Dr. Hsu-Hao Yang received the B.S. degree in industrial management from National Cheng-Kung University, Tainan City, Taiwan, in 1983, and the M.S. and Ph.D. degrees in industrial engineering from The University of Iowa, Iowa City, U.S.A., in 1991 and 1994, respectively. He was a visiting scholar at the Department of Mechanical and Industrial Engineering, The University of Iowa, in 2010. He is currently a Professor at the Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung City, Taiwan. Professor Yang published and reviewed papers in referred journals, and has been a member of several editorial boards. His current
Dr. Hsu-Hao Yang received the B.S. degree in industrial management from National Cheng-Kung University, Tainan City, Taiwan, in 1983, and the M.S. and Ph.D. degrees in industrial engineering from The University of Iowa, Iowa City, U.S.A., in 1991 and 1994, respectively. He was a visiting scholar at the Department of Mechanical and Industrial Engineering, The University of Iowa, in 2010. He is currently a Professor at the Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung City, Taiwan. Professor Yang published and reviewed papers in referred journals, and has been a member of several editorial boards. His current research interests focus on the applications of data mining techniques to wind energy.
Dr. Hardin has authored or co-authored over 80 papers in various journals. He is the author or co-author of over 150 abstracts presented at national meetings and has given over 75 invited lectures or talks. He is the author of several book chapters dealing with database design and decision support systems. Dr. Hardin often serves as a consultant to healthcare organizations in the areas of data mining, sampling, and program integrity. Additionally, he is an instructor and consultant for the SAS Institute in the areas of data mining and time series analysis. He is Adjunct Professor of Biostatistics and Adjunct
Dr. Hardin has authored or co-authored over 80 papers in various journals. He is the author or co-author of over 150 abstracts presented at national meetings and has given over 75 invited lectures or talks. He is the author of several book chapters dealing with database design and decision support systems. Dr. Hardin often serves as a consultant to healthcare organizations in the areas of data mining, sampling, and program integrity. Additionally, he is an instructor and consultant for the SAS Institute in the areas of data mining and time series analysis. He is Adjunct Professor of Biostatistics and Adjunct Professor of Health Informatics at the University of Alabama at Birmingham. He has served as Scholar in Residence in the Center for Information Management, Department of Information Systems and Operations Management, Loyola University, Chicago, and Visiting Professor in the Department of Management and Information Sciences and Statistics at Trinity College, Dublin, Ireland. He is a member of numerous professional associations including the American Statistical Association, the Biometric Society, and the Institute of Mathematical Statistics. He was also named a Fellow of the American Statistical Association. His specialty areas include Data mining and knowledge discovery, data visualization, data warehousing, machine learning, statistical classification models, data management and collection methodologies, research design, informatics, the applications of statistical methodologies in the study of aging, and biostatistics.
Dr. B. M. Golam Kibria is a Professor in the Department of Mathematics and Statistics at Florida International University (FIU). He also taught at The University of British Columbia & The University of Western Ontario, Canada and Jahangirnagar University, Bangladesh. Dr. Kibria has diverse research interests, mainly, Applied Statistics, Distribution Theory, Quality Control, Linear Model, Ridge Regression, Statistical Inference and Simulation Study. Since 1993, he has more than 200 full research articles either published or accepted for publication in different internationally well-reputed statistical journals and co-authored two books. Dr. Kibria has supervised as a major (or co-major) professor of two
Dr. B. M. Golam Kibria is a Professor in the Department of Mathematics and Statistics at Florida International University (FIU). He also taught at The University of British Columbia & The University of Western Ontario, Canada and Jahangirnagar University, Bangladesh. Dr. Kibria has diverse research interests, mainly, Applied Statistics, Distribution Theory, Quality Control, Linear Model, Ridge Regression, Statistical Inference and Simulation Study. Since 1993, he has more than 200 full research articles either published or accepted for publication in different internationally well-reputed statistical journals and co-authored two books. Dr. Kibria has supervised as a major (or co-major) professor of two Ph.D. and 19 masters students and as a major professor of 20 undergraduate students at FIU. He has served more than 40 Ph.D. and M.Sc thesis committees at FIU and abroad (Australia, Canada, India, Pakistan, South Africa and Sweden). He is the recipient of several awards: Certificate of Excellence in Reviewing Award-2018, awarded by the Journal of Advances in Mathematics and Computer Sciences. FIU Top Scholar Award 2016, FIU College of Arts, Science and Education Research Award 2016 & 2019, Canadian Commonwealth Scholarship at Carleton and University of Western Ontario (UWO), Graduate Research Fellowship at UWO and Asadul Kabir Gold Medal from Jahangirnagar University among others. Dr. Kibria is the Editor-in-Chief of the Journal of Probability and Statistical Science and member of editorial board of about 25 international statistical journals, including Communications in Statistics – A, B & C. He is the elected Fellow of Royal Statistical Society.
Dr. Jon Ver Halen is an Associate Professor with the Texas A&M School of Medicine, Department of Surgery. He is also Associate Program Director of the Plastic Surgery Residency, and Program Director of the Microvascular Surgery Fellowship. His professional organisations include Plastic Surgery Research Council, American Society for Reconstructive Microsurgery, American Society for Reconstructive Transplantation, Memphis Robotic Surgical Society, American Society of Plastic Surgeons, etc.
Dr. Jon Ver Halen is an Associate Professor with the Texas A&M School of Medicine, Department of Surgery. He is also Associate Program Director of the Plastic Surgery Residency, and Program Director of the Microvascular Surgery Fellowship. His professional organisations include Plastic Surgery Research Council, American Society for Reconstructive Microsurgery, American Society for Reconstructive Transplantation, Memphis Robotic Surgical Society, American Society of Plastic Surgeons, etc.
Dr. Mehmet Kocak is an Associate Professor of Biostatistics in the Department of Preventive Medicine. He earned his M.Sc. degree in applied statistics from Michigan State University and a Ph.D. of statistics from University of Memphis. He has been a study biostatistician for numerous Phase-I and Phase-II clinical trials conducted by St. Jude Children's Research Hospital from 2002-2011 and by Pediatric Brain Tumor Consortium (PBTC) from 2002-present, and for clinical and observational studies conducted by University of Tennessee Health Science Center (UTHSC) since 2011. His responsibilities as the biostatistician for many clinical trials have included, but have been not limited
Dr. Mehmet Kocak is an Associate Professor of Biostatistics in the Department of Preventive Medicine. He earned his M.Sc. degree in applied statistics from Michigan State University and a Ph.D. of statistics from University of Memphis. He has been a study biostatistician for numerous Phase-I and Phase-II clinical trials conducted by St. Jude Children's Research Hospital from 2002-2011 and by Pediatric Brain Tumor Consortium (PBTC) from 2002-present, and for clinical and observational studies conducted by University of Tennessee Health Science Center (UTHSC) since 2011. His responsibilities as the biostatistician for many clinical trials have included, but have been not limited to, statistical design of the trial, conducting and monitoring of the trial, periodic reporting of study progress in semi-annual meetings, analyzing, reporting and publication of the trial data. As a biostatistician, he has also conducted numerous retrospective data analyses as well as analyses on clinical and observational studies conducted by PBTC, Children's Oncology Group (COG), and UTHSC. As part of his responsibilities within UTHSC, he acts as the coordinating biostatistician for the CANDLE (Conditions Affecting Neurocognitive Development and Learning in Early Childhood) study as well as its ancillary study 'Pregnancy folate status & early childhood respiratory & atopic disease outcomes' by providing direct mentorship and supervisions to data analysts and other statisticians. He also provides statistical support for the US AirForce studies, specifically to the FitBlue (Dissemination of the Look Ahead Weight Management Treatment in the Military) study. His area of research have been time-course gene expression data analysis, meta-analysis of p-values, Phase-I clinical trial design, Survival analysis, and categorical data analysis. He is an expert on SAS programming language as well as SAS/Graph.
Dr. Haixin Wang's primary research interests are in the field of bioinformatics, computation biology, algorithm analysis, and signal processing. Specifically, he is interested in the statistics data processing in system biology, especially the noisy time-series microarray data. His research has profound biomedical application. He developed the noisy non-linear gene regulatory network models using advanced statistics signal processing, and analyzed statistical-based microarray data and delivery systems for functional genomics information to visualize the expression data. He also published fourteen papers in prestigious peer-reviewed top-rated journal and conference, such as IEEE Transactions on Signal Processing, and IET System Biology, and one
Dr. Haixin Wang's primary research interests are in the field of bioinformatics, computation biology, algorithm analysis, and signal processing. Specifically, he is interested in the statistics data processing in system biology, especially the noisy time-series microarray data. His research has profound biomedical application. He developed the noisy non-linear gene regulatory network models using advanced statistics signal processing, and analyzed statistical-based microarray data and delivery systems for functional genomics information to visualize the expression data. He also published fourteen papers in prestigious peer-reviewed top-rated journal and conference, such as IEEE Transactions on Signal Processing, and IET System Biology, and one book chapter by Wiley with the book title 'Applied Statistics for Network Biology: Methods in System Biology'. He presented his research work at numerous prestigious scientific gatherings in the United States, China, and Canada, for example, IEEE Symposia on Computation and Intelligence in Bioinforamtics and Computation Biology. As a researcher in Bioinformatics, he also serves in the professional organizations. He served as the paper reviewer for many national and international conferences, and journals, for example, IEEE Transaction, and IET System Biology. He was identified as the TOP Performing Reviewer on Computers and Electrical Engineering in 2010 and 2014, Elsevier Editorial System. He was also committee member in the national and international conferences.
Dr. Lou received his Ph.D. from Zhejiang University, China, in 1997. And then he was recruited as an Assistant Professor at Zhejiang University. He came to the U.S. for pursuing postdoctoral training in the Department of Statistics, the University of Florida, in 2002. He was a Research Associate and an Assistant Professor at the University of Virginia. He joined UAB as an Associate Professor in 2009. Dr. Lou's research interests include Biostatistics, Bioinformatics, Genetic Epidemiology, Statistical Genetics, and Population Genetics. His research primarily concentrates on developing and applying powerful innovative analysis methods to solve
Dr. Lou received his Ph.D. from Zhejiang University, China, in 1997. And then he was recruited as an Assistant Professor at Zhejiang University. He came to the U.S. for pursuing postdoctoral training in the Department of Statistics, the University of Florida, in 2002. He was a Research Associate and an Assistant Professor at the University of Virginia. He joined UAB as an Associate Professor in 2009. Dr. Lou's research interests include Biostatistics, Bioinformatics, Genetic Epidemiology, Statistical Genetics, and Population Genetics. His research primarily concentrates on developing and applying powerful innovative analysis methods to solve real-world biological problems such as gene-gene and gene-environment interactions, low statistical power, and allelic heterogeneity in genetic data analysis. His research Interests are Biostatistics, Bioinformatics, Genetic Epidemiology, Statistical Genetics, and Population Genetics.
Yasutaka Chiba is an Associate Professor of Clinical Research Center at Kindai University Hospital in Japan. He is a biostatistician. His area of interest is clinical research methodology. Specifically, he is working on application of causal inference methodology to clinical studies. His research interest is Application of causal inference methodology to clinical studies.
Yasutaka Chiba is an Associate Professor of Clinical Research Center at Kindai University Hospital in Japan. He is a biostatistician. His area of interest is clinical research methodology. Specifically, he is working on application of causal inference methodology to clinical studies. His research interest is Application of causal inference methodology to clinical studies.
Mr. Zhuopei Hu has been a biostatistician in the University of Arkansas for Medical Sciences (UAMS) since 2014. Mr. Hu graduated from the University of Arkansas with a M.S degree in Statistics. After working as a data analyst in General Dynamics Health Solution, Mr. Hu joined the research institution, UAMS, as a biostatistician due to the strong passion on novel research in the biostatistics and biomedical field. He collaborated with medical researchers in Departments of pediatrics on various filed, such as emergency medicine, pulmonary, obesity, etc. He currently works on several clinical trial studies that were funded by NIH. Besides
Mr. Zhuopei Hu has been a biostatistician in the University of Arkansas for Medical Sciences (UAMS) since 2014. Mr. Hu graduated from the University of Arkansas with a M.S degree in Statistics. After working as a data analyst in General Dynamics Health Solution, Mr. Hu joined the research institution, UAMS, as a biostatistician due to the strong passion on novel research in the biostatistics and biomedical field. He collaborated with medical researchers in Departments of pediatrics on various filed, such as emergency medicine, pulmonary, obesity, etc. He currently works on several clinical trial studies that were funded by NIH. Besides the collaborations on biomedical field, he also does researches on new statistical methodology development. Mr. Hu served as the Vice President for Central Arkansas Statistics Association from the year 2016 to 2017, and the President in the following year to host statistical travel course and seminars. Mr. Hu’s current research interest are clinical trials design and execution, computational statistics, statistical graphics, generalized linear models.
Mr. Hanjie Shen is a Senior Statistician working at Fred Hutchinson Cancer Research Center. He obtained Master’s degrees in Statistics and Biostatistics from University of California San Diego. His expertise lies in advanced statistical models, high dimensional data analysis, machine learning algorithms in cancer clinical trials and cancer research. His research interests includes Cancer Research, Clinical Trials, Physical Activity, High Dimensional Data Analysis and Machine Learning Algorithms.
Mr. Hanjie Shen is a Senior Statistician working at Fred Hutchinson Cancer Research Center. He obtained Master’s degrees in Statistics and Biostatistics from University of California San Diego. His expertise lies in advanced statistical models, high dimensional data analysis, machine learning algorithms in cancer clinical trials and cancer research. His research interests includes Cancer Research, Clinical Trials, Physical Activity, High Dimensional Data Analysis and Machine Learning Algorithms.
All articles are fully peer reviewed, free to access and can be downloaded from our ClinMed archive.
Clinical Medical Image Library: 93.51
International Journal of Critical Care and Emergency Medicine: 92.83
International Journal of Sports and Exercise Medicine: 91.84
International Journal of Womens Health and Wellness: 91.79
Journal of Musculoskeletal Disorders and Treatment: 91.73
Journal of Geriatric Medicine and Gerontology: 91.55
Journal of Infectious Diseases and Epidemiology: 91.55
Clinical Medical Reviews and Case Reports: 91.40
International Archives of Nursing and Health Care: 90.87
International Journal of Ophthalmology and Clinical Research: 90.80
International Archives of Urology and Complications: 90.73
Journal of Clinical Nephrology and Renal Care: 90.33
Journal of Family Medicine and Disease Prevention: 89.99
Journal of Clinical Gastroenterology and Treatment: 89.54
Journal of Dermatology Research and Therapy: 89.34
International Journal of Clinical Cardiology: 89.24
International Journal of Radiology and Imaging Technology: 88.88
Obstetrics and Gynaecology Cases - Reviews: 88.42
International Journal of Blood Research and Disorders: 88.22
International Journal of Diabetes and Clinical Research: 87.97