Dr. Almudevar is Assistant Professor in the Department of Biostatistics and Computational Biology at the University of Rochester. He earned his Ph.D. from the Department of Statistics at the University of Toronto in 1994. His published research represents a wide range of fields, including approximate control theory and iterative systems; mathematical statistics; psychometrics; and clinical home monitoring applications. His main interest is in graphical modeling of biological systems. He has published extensively in the area of pedigree inference in wild populations, and is currently conducting research in the modeling of gene regulatory pathways and networks.
Dr. Lutz Edler received his academic education and training in mathematics and physics from 1964 to 1970 at the Albert-Ludwigs University in Freiburg, and from 1971 to 1978 in statistics and probability at the Johannes-Gutenberg University in Mainz, Germany, where he received his Ph.D. for his thesis work on branching processes. Since 1979 he has been with the Department of Biostatistics of the German Cancer Research Center in Heidelberg, of which he has been head since 1991. Dr. Edler’s scientific fields are in mathematical modelling and data analysis in carcinogenesis and risk assessment; methods for the design and analysis of clinical trials; and methods of computational statistics for pharmacokinetics and, more recently, pharmacogenomics. He has been visiting scientist at the National Institute of Environmental Health Sciences (NIEHS) in the Research Triangle Park, NC, USA, and at the Institute of Statistical Mathematics (ISM) in Tokyo, Japan.
During his more than 25 years work at the German Cancer Research Center he published approximately 240 journal articles, 80 book chapters and gave approximately 160 invited talks. He edited, together with colleagues, the book "Quantitative Methods for Cancer and Human Health Risk Assessment" and edited/coedited "Special Issues in Statistics in Medicine and in Computational Statistics and Data Analysis (CSDA)". Dr. Edler is member of all major statistical societies, is an elected member of the International Statistical Institute (ISI), was President of the International Association for Statistical Computing IASC) and now heads the ISI-Committee for Risk Analysis. He also acts as an expert on scientific advisory panels of the German Bundesinstitut für Risikobewertung (BfR); the US Environmental Protection Agency (EPA); the Japanese ISM; and the European Food Safety Agency. He is responsible biostatistician in the Central European Society of Anticancer Reseach (CESAR) and member of the Ethics Committee of the University of Heidelberg and the "Off Label Use in Oncology" expert group of the BfArM.
Dr. Alexander Gordon received his PhD in Mathematics from the Moscow Institute of Electronic Machine Building (Moscow, Russia; now the Moscow State Institute of Electronics and Mathematics) in 1988. Much of his mathematical research has been in the field of functional analysis on its borderline with mathematical physics and probability theory (almost periodic and random operators). Over the last few years, Dr. Gordon has been involved in studies in Biostatistics (multiple testing procedures and their application to microarray experiments)--first at the University of Rochester Medical Center and currently at the University of North Carolina at Charlotte, where he is an Assistant Professor in the Department of Mathematics and Statistics.
Yuriy Gusev, Ph.D., is an Assistant Professor of Bioinformatics at the University of Oklahoma Health Science Center, and an Adjunct Assistant Professor at the Breast Health Institute. He is also a faculty member of the University of Oklahoma Cancer Institute where he is involved with the Cancer Biology Program; Translational Research Program with animal tumor models; and the Southwest Program for Pancreatic Cancer. Dr. Gusev obtained his M.S. degree in Applied Mathematics with a concentration in Mathematical Biology at St. Petersburg State University, Russia and his Ph.D. in Applied Mathematics and Biology from the Central Research Institute of Roentgenology & Radiology, St. Petersburg, Russia under the supervision of Dr. Andrej Yakovlev. Dr. Gusev was a post-doctoral fellow at the Waksman Institute at Rutgers University in the cancer genetics laboratory of Dr. David Axelrod, and later held a junior faculty position at the Johns Hopkins School of Medicine. At Johns Hopkins, he conducted multi-disciplinary projects on mathematical modeling and computer simulation of the basic mechanisms of carcinogenesis, and identification of novel biomarkers for the molecular diagnostics of breast, pancreas, prostate and liver malignancies. His current research interests are centered on analysis and integration of high throughput data obtained with genomics and proteomics technologies as well as global profiling of microRNAs in human cancers and inflammation using bioinformatics and systems biology methodologies.
Interview with Yuriy Gusev: http://www.scienceboard.net/community/spotlights.150.html
Departmental Webpage: http://w3.ouhsc.edu/surgery/Faculty/Yuriy_Gusev.asp
Leonid Hanin is Professor of Mathematics at Idaho State University. He received his Ph.D. in Functional Analysis from the Steklov Mathematical Institute (St. Petersburg, Russia) in 1985. Since then he worked at various universities in Russia, Israel and the US. The main focus of his research as it evolved over the last 20 years is on rigorous development and analysis of mathematical models of various biomedical processes. In particular, he worked in stochastic modeling in cell biology, radiation biology, cancer epidemiology, radiation cancer treatment, molecular biology, and biochemistry. His other scientific interests include probability, stochastic processes, and mathematical methods in heat transfer.
Dr. Hyrien is an Assistant Professor of Biostatistics and Computational Biology at the University of Rochester. He received his Ph.D. in statistics from the University of Rennes I, France, in 2001. Before joining the University of Rochester, he worked at the Huntsman Cancer Institute, University of Utah. Dr. Hyrien’s research is motivated by the quantitative analysis of complex cellular systems. His primary research interests include stochastic processes (e.g., age-dependent branching processes), mixture models, as well as composite and pseudo-likelihood inference.
Peter Jagers is a professor of Mathematical Statistics at the Chalmers University of Technology, Gothenburg Sweden. He is also the First Vice President of the Royal Swedish Academy of Science.
His research interests have centered around stochastic population dynamics, in particular branching processes. On the theoretical side, Dr. Jagers introduced general branching processes with abstract type spaces and wrote about the structure, growth, and stabilization of supercritical populations. Recently he has investigated the time and path to extinction (PNAS 2007), and studied population size dependence and other forms of interaction in population dynamics. A number of papers deal with the consequently arising linear phase in polymerase chain reactions (PCR).
Dr. Jagers’ interest in cell proliferation goes back to the 70's, when he first met young Andrei Yakovlev at a Moscow meeting on cell biology. This is reflected in his 1975 book "Branching Processes with Biological Applications". More recently he published "Branching Processes: Variation, Growth, and Extinction of Populations" (with P. Haccou and V. Vatutin), published by Oxford University Press in 2005.
Nicholas Jewell is Professor of Biostatistics and Statistics at the University of California, Berkeley. He has held various academic and administrative positions at Berkeley since his arrival in 1981, most notably serving as Vice Provost from 1994 to 2000. He was trained at the University of Edinburgh where he received an Honours degree in Applied Mathematics in 1973 and a Ph.D. in Mathematics in 1976. Immediately following his graduate program, he was appointed to a Harkness Fellowship from 1976-1978 which he held at the University of California, Berkeley and at Stanford University. From 1979-1981 he was an Assistant Professor of Statistics at Princeton University. He has also held academic appointments at the University of Edinburgh and at Oxford University.
Dr. Jewell is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science (AAAS). He is the 2005 winner of the Snedecor Award from COPSS, and won the Distinguished Teaching Award from UC Berkeley's School of Public Health in 2004. In 2000, he was awarded the Director's Award from the Federal Emergency Management Agency for "extraordinary leadership and vision in implementing strategies that enhance the disaster resistance of the University of California, Berkeley, and universities throughout America"; in addition the 2005 Alfred E. Alquist Award was given to UC Berkeley's SAFER program that he launched and led for many years. In 2007, he was a Fellow at the Rockefeller Foundation Bellagio Center in Italy.
Dr. Jewell worked originally in functional analysis before turning to Biostatistics. He has made major contributions to statistical techniques for the analysis of epidemiological data, longitudinal data analysis, and survival analysis--particularly current status data. In applications, he has worked on HIV and AIDS data since the beginning of the epidemic in 1981, and more recently on other infectious diseases, and in environmental epidemiology and vision science, publishing more than 120 research articles. Dr. Jewell has had more than 20 Ph.D. students at Berkeley and has been an Associate Editor of Biometrika, The Journal of the American Statistical Association, The Annals of Statistics, The International Statistical Review, The American Statistician, and Statistical Science. In addition, he was a founding Editor of Lifetime Data Analysis. At bepress, he launched two journals, Statistical Applications in Genetics and Molecular Biology and The International Journal of Biostatistics, for which he is still Senior Editor. He is the author of the monograph, Statistics for Epidemiology, published by CRC Press. He is a past President of the WNAR region of the Biometric Society, Treasurer of IMS, and member of the National Research Council's Committees on National Statistics and on Applied and Theoretical Statistics.
Marianthi Markatou is a Professor of Biostatistics, Columbia University, New York. She holds a B.Sc. in Mathematics from the University of Patras, Greece ; an MA in Statistics from the University of Rochester; and a PhD in Statistics from the Pennsylvania State University. Her research interests include problems in model selection and statistical distances, high dimensional data analysis methods, biomedical text data mining, methods for the analysis of microarray and proteomics data, pharmacovigilance and issues in biomarker development. Her publications include articles in the Journal of the American Statistical Association (JASA), Journal of Biomedical Informatics (JBI), Annals of Statistics, Journal of the American Medical Informatics Association (JAMIA), Bioinformatics, Review of Economic Studies, and many others. She is an elected Fellow of the American Statistical Association, an elected member of the International Statistical Institute and a Fellow of the Institute of Social and Economic Research and Policy at Columbia University. From 2001-2003 she held the position of Program Director in Statistics, National Science Foundation. Moreover, she is on the editorial board of JASA (Theory & Methods), Sankhya (Series B), and Biology Direct—Section on Mathematical Biology. In 2009, Dr. Markatou is on leave from Columbia University and with the Center of Biologics Evaluation and Research (CBER), FDA as a scientific advisor to the center.
Dr. Aniko Szabo is Associate Professor and Director of the Biostatistical Consulting Service at the Division of Biostatistics, Department of Population Health of the Medical College of Wisconsin in Milwaukee, WI. She received a Ph.D. in Applied Statistics from the University of Memphis, Memphis, TN in 1998, and continued with post-doctoral training at the University of Utah, Salt Lake City, UT under the guidance of Dr. Andrei Yakovlev during 1999.
Dr. Szabo's research interests are in statistical modeling of biomedical data. She has worked on developing tree models of oncogenesis, nonparametric models of clustered discrete data, and population level models of the effect of screening on prostate cancer incidence.
Alex Tsodikov is Professor of Biostatistics at the University of Michigan, Ann Arbor. He received his Ph.D. in Applied Mathematics in 1991 from St. Petersburg State Technical University, Russia and has worked at Universities in France, Germany, Sweden, Utah and California. Dr. Tsodikov's research interests are in various areas of biostatistics and biomathematics, including failure time and survival analysis models, cure models, EM algorithms and their generalizations, semiparametric inference, models of cancer, optimal control, inference algorithms based on self-consistency, categorical data analysis. Applications have mainly evolved around cancer research.
Recent methodological interest has centered on the idea of fake mixture or frailty models and its generalization as a tool to derive computationally efficient inference procedures for a wide variety of statistical models. Much of this methodology was initially developed for so-called semiparametric cure models and mechanistic models of cancer. These methods are applied to build a comprehensive model of the dynamics of the national incidence and mortality trends in prostate cancer in the presence of variable utilization of screening.
Dr. Elart von Collani is Professor of Stochastics, Faculty of Economy, University of Würzburg and Managing Director of Stochastikon GmbH (www.stochastikon.com), Würzburg.
Dr. von Collani studied Mathematics, Physics and Japanology at Würzburg University and received a Diplom-degree in Mathematics in 1972, the degree Dr. rer. nat. (Mathematics) in 1978, and the degree Dr. rer. nat habil. (Applied Mathematics) in 1983.
He is author of about 200 publications and had visiting positions in various universities and research institutions in Europe, Asia and America. His research covers many areas of statistics, stochastic processes and the philosophy of science. In particular, he developed a novel approach to model uncertainty about future developments that aims at replacing the conventionally assumed deterministic approach in science. The approach incorporates explicitly the two sources of uncertainty namely ignorance and randomness and has been successfully applied to problems in medicine, material sciences, industry and economy.
Nikolay M. Yanev
Bulgarian Academy of Sciences
Institute of Mathematics and Informatics
Dr. Nikolay M. Ianev is Professor and Chair of the Department of Probability and Statistics, Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia. He obtained an M.S. diploma in Mathematics from Sofia University in 1969, Ph.D. in Probability and Statistics from Moscow State University in 1975 and also a second Ph.D. in Mathematical Sciences (Sofia, 1985). Dr. Ianev has about 120 publications (among them 7 books). A large part of these publications are in the field of branching stochastic processes – regulation, regeneration, random migration, limit theorems, statistical inference, to name a few. He was involved with Dr. Andrei Yakovlev in biological and medical applications of branching processes (more than 20 collaborative papers and one book). As a result of this collaboration, new problems for branching processes theory also appeared.
Departmental Webpage: http://www.math.bas.bg/