Przemysław Biecek graduated in Software Engineering and Mathematical Statistics at Wrocław University of Technology. He is currently working as professor at Warsaw University of Technology and as assistant professor at University of Warsaw. His research interests are focused on statistical learning from big datasets, especially with applications in oncology, bio-statistics and computational medicine. He has published over 50 articles in journals including JSS, IJMP, PloS one, PMB and JCB. In addition, he is an active developer of many R packages and wrote three monographs related to Data processing, Data visualization and Statistical modeling.
Prof. Tomasz Burzykowski
Professor of Biostatistics and Bioinformatics, Hasselt University and Vice-President of Research at the International Drug Development Institute (IDDI) in Louvain-la-Neuve, BELGIUM
Tomasz Burzykowski is Professor of Biostatistics and Bioinformatics at Hasselt University (Belgium) and Vice-President of Research at the International Drug Development Institute (IDDI) in Louvain-la-Neuve(Belgium). He received the M.Sc. degree in applied mathematics (1990) from Warsaw University, and the M.Sc. (1991) and Ph.D. (2001) degrees in biostatistics from Hasselt University. He is Visiting Professor at the Medical University of Bialystok (Poland) and has held guest professorships at the Karolinska Institute (Sweden) and the Technical University of Warsaw (Poland). He serves as Associate Editor of Pharmaceutical Statistics. Prof. Burzykowski published methodological work on survival analysis, meta-analyses of clinical trials, validation of surrogate endpoints, analysis of gene expression data, and modeling of peptide-centric mass spectrometry data. He is also a co-author of numerous papers applying statistical methods to clinical data in different disease areas (oncology, Alzheimer's disease, ophthalmology, cardiovascular diseases). More information.
Prof. Magdalena Chechlinska, PhD is a Head of Department of Immunology at the Maria Skłodowska-Curie Memorial Cancer Centre and Institute of Oncology in Warsaw, Poland (COI). She received M.Sci. degree in biology from Warsaw University, and PhD and Dr Habil. degrees in medical biology from the COI. She has published on cancer microenvironment, cytokines, microRNAs, with a special emphasis on biomarkers. In 2011, she was awarded the The Jedrzej Sniadecki Memorial Award, the most prestigious prize of the Medical Department of the Polish Academy of Sciences, for a series of papers on cancer biomarkers. She serves on the Editorial Boards of BMC Cancer and of Contemporary Oncology. She is a member of several Polish and International professional societies. Currently, she is a member of the Scientific Boards of the COI and of the Children’s Memorial Health Institute in Warsaw. She has conceived and implemented the idea to develop a comprehensive IT platform for cancer research, the ONKOSYS.
Mariusz Dzieciątko is a Business Solution Manager at SAS Poland Technology and Big Data Competency Center and lecturer at the Warsaw School of Economics. He graduated from the Faculty of Electrical Engineering at the Warsaw University of Technology, where he was later awarded a PhD degree in computer science. He has more than 20 years of experience with information technology. His main interests include Text Mining and optimization methods. He has extensive experience in the area of information retrieval, information extraction, sentiment analysis, text classification and clustering, predictive modeling and data visualization, gained during the implementation of many projects. Personally he is an advocate of homeschooling and president of the Association of Education in the Family.
Andrzej Gałecki is a Research Professor in the Division of Geriatric Medicine, Department of Internal Medicine, and Institute of Gerontology at the University of Michigan Medical School, and in the Department of Biostatistics at the University of Michigan School of Public Health. He earned his M.Sc. in applied mathematics (1977) from the Technical University of Warsaw, Poland, and an M.D. (1981) from the Medical University of Warsaw. In 1985 he earned a Ph.D. in epidemiology from the Institute of Mother and Child Care in Warsaw (Poland). He is a member of the Editorial Board of the Open Journal of Applied Sciences. Since 1990, Dr. Gałecki has collaborated with researchers in gerontology and geriatrics. His research interests lie in the development and application of statistical methods for analyzing correlated and over- dispersed data. He developed the SAS macro NLMEM for nonlinear mixed-effects models, specified as a solution to ordinary differential equations. He also proposed a general class of variance-covariance structures for the analysis of multiple continuous dependent variables measured over time. This methodology is considered to be one of the first approaches to joint models for longitudinal data. In 2015 he was named Fellow of the American Statistical Association.
Prof. Jeanine J. Houwing-Duistermaat
Professor of Data Analytics and Statistics, Department of Statistics, University of Leeds, UK, Professor of Statistical Genetics, Department of Medical Statistics and Bioinformatics, Leiden University Medical Centre, THE NETHERLANDS
Jeanine Houwing-Duistermaat is Professor of Data Analytics and Statistics at the department of Mathematics, University of Leeds. She received a PhD in Medical Statistics from University of Leiden, The Netherlands (1997). In 2005 she received a prestigious personal grant to start her own group in statistical genetics at the Leiden University Medical Center. In 2010 she was appointed as full professor and in 2015 she decided to move to the UK. She is coordinator of the FP7 funded consortium MIMOmics, which aims to develop methods for integrated analysis of multiple omics datasets. She was leader of the LUMC-Research ICT committee which wrote a strategic report on big data and data analytics opportunities and investments for the board of the hospital. From 2013 to 2015, she was co-editor of Biometrics, the journal of the International Biometric Society. Currently she is president of the Dutch Region of the International Biometric Society. She has more than 200 publications in statistical and medical journals. H-index of 50 (google scholar), of 37 (web of science).
Jack Shostak, Associate Director of Statistics, manages a group of statistical programmers at the Duke Clinical Research Institute. He manages the business aspects of the statistical programming workforce and interacts with the Information Technology, Informatics, and Data Management Groups to develop and facilitate methodology for efficient data organization and flow in the organization. His group works on industry funded studies, regulatory submission work, and the statistical programming for academic publications. Jack Shostak is a SAS user since 1985, and he is the author of SAS Programming in the Pharmaceutical Industry, and coauthor of Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, as well as Implementing CDISC Using SAS: An End-to-End Guide. Shostak has published papers for the Pharmaceutical SAS Users Group (PharmaSUG) and the NorthEast SAS Users Group (NESUG), and he contributed a chapter, "Reporting and SAS Tool Selection," in the book Reporting from the Field. He is active in the Clinical Data Interchange Standards Consortium (CDISC) community, contributing and assisting with the leadership of the Analysis Data Model (ADaM). He serves as an ADaM trainer for CDISC, and teaches classes for the pharmaceutical industry as well as the FDA. Shostak received an MBA from James Madison University and a BS in statistics from Virginia Polytechnic Institute and State University. More information.
Associate Professor in the discipline Biocybernetics and Biomedical Engineering; employee of the Department of Biomedical Engineering Silesian University of Technology. It specializes in the processing of multimedia data, in particular for computer-aided diagnosis and therapy. Highlighted among other things, the title of Very Important Polish Innovator by the Foundation for Poland Now.
Prof. Maciej Wiznerowicz
Professor of Medicine, Poznan University of Medical Sciences, Principal Investigator, Greater Poland Cancer Centre, President and co-founder, International Institute for Molecular Oncology in Poznan, POLAND
Dr Wiznerowicz received his M.D. (1997) and Ph.D. (1998) degrees from the Poznan University of Medical Sciences. Next, he pursued his career at the University of Geneva (2000-2004) and École Politechnique Fédérale de Lausanne (EPFL) in Switzerland (2004-2006), followed by Merck Research Laboratories in Boston, USA (2006-2009). In 2010, Dr Wiznerowicz was awarded with prestigious Welcome grant from the Foundation for Polish Science to 2009 and came back to native Poland with the goal to study molecular mechanisms in stem cells and cancer in collaboration with the MD Anderson Cancer Center. In the same year, he has included GPCC into The Cancer Genome Atlas (TCGA) Program, collaborative effort between National Cancer Institute, the National Human Genome Research Institute and leading oncology hospitals in the world. The major goal of this project is comprehensive molecular analysis of human tumours in order to identify novel molecular mechanisms involved in carcinogenesis and potential new targets for drug discovery. In 2015, together with leading oncologists in Poland, Dr Wiznerowicz founded the International Institute for Molecular Oncology, non-profit research organization for translational cancer research (iimo.pl). The mission of IIMO is to carry out scientific and industrial studies in oncology using the state-of-the-art ICT solutions and computational science to develop and implement innovative methods for prevention, diagnosis and treatment of cancer. The Institute has already received a contract from NCI/NIH to integrate of cancer genomics with the proteomic analyses of various tumour types within the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Dr Wiznerowicz works on the TCGA PanCancer Atlas analyses and leads an international team of computational biologists, statisticians, and clinicians, focused on comprehensive analyses of selected cancer features across over 30 tumour types using TCGA molecular data from various genomic and proteomic platforms.