My group is interested in investigating the processes of evolution and biology using computational methods. We apply machine learning methods (HMMs, Bayesian statistics, particle filters, deep learning) to large data sets to study for example human demographic history or non-coding functional elements in the genome.
With a B.Sc. in Mathematics and Applied Mathematics from the University of Shantou, China (2003), a M.Sc. in Data Analysis, Network and Nonlinear Dynamical System from the University of York, UK (2004), and a Ph.D. in Statistics from the University of Leeds, UK (2008), Dr. Luo has gained extensive knowledge& experience in applied mathematics and statistics, computer simulations & forecasting, dynamic system and high-dimensional data analysis, to study disease dispersal and mitigation on a multinational scale. He has worked several years as biostatistician at The Food and Environmental Research Agency (UK) before beginning research in Florida (2011) as collaborated research scholar in NCSU and visiting scientist USDA. He played a key role in a wide range of multidisciplinary projects including, but not limited to, risk-based survey of HLB/ACP in FL, CA, TX and AZ, Plum Pox Virus (PPV) survey in NY and CA, Census travel modelling, agent-based disease simulation, GIS disease mapping and Aerial image processing.
The Vsevolod Makeev Head of Department of Computational Systems Biology, Vavilov Institute of General Genetics, Russian Academy of Sciences; Professor at Moscow Institute (University) of Physics and Technology, Deputy Chair of Bioinformatics; Past Head of the Laboratory of Bioinformatics, State Research Centre of Genetics and Selection of Industrial Microorganisms.
After 11 years working at the University of Washington and the Fred Hutchinson Cancer Research Center, Dr. Mâsse moved back to Canada in August of 2010 and took a faculty appointment at the Université de Montreal as well as joining the Research Center at CHU-Ste-Justine. Overall, he has contributed to 85+ research grants since graduating in biostatistics from UNC-Chapel Hill in 1993. In addition to studies focused on HIV/AIDS, he has been involved in clinical trials and studies on children delinquent behavior; perinatal research; head and neck cancer chemoprevention; breast cancer; psychosocial and work environment studies on cardiovascular diseases, urinary infection, delirium in cancer palliative care, and pain management in early termination of pregnancy.
Dr. Mâsse has conducted multi-country large international trials in USA, Brazil, Canada, China, India, Russia, and in many countries of Africa. Since 2000, he has contributed to the research agenda of several large NIH networks by providing methodological support for the development of study protocols as well as providing the infrastructure to support the conduct of these studies. In 2006, Dr. Mâsse received a grant of over $US 25 millions from the NIH as the Principal Investigator responsible for establishing the Statistical Data Management Center for providing support to all international Phase I-II-III trials and observational studies conducted within the Microbicide Trials Network.
David Meyre completed a PhD in quantitative plant genetics in France. Since 2001, he has been working on the elucidation of the genetic bases of obesity and type 2 diabetes. In 2004, he published the first family-based genome-wide scans for childhood and severe adult obesity. He completed the two first successful positional cloning efforts for childhood and severe adult obesity, which identified the positional candidate genes ENPP1 and PCSK1. In 2007, he contributed to the identification of the major susceptibility gene for polygenic obesity FTO. In 2009, he published the first genome-wide association study of extreme obesity in the French population and identified four novel susceptibility-loci. In 2010, he conducted the first genome-wide association meta-analysis for early-onset extreme obesity in German and French populations. In 2012, he identified the third more common form of monogenic obesity (PCSK1 partial deficiency) and demonstrated an important role of the lipid sensor GPR120 in human obesity. He also discovered the first molecular link between obesity and major depression. In 2013, he discovered a novel gene (SIM1) responsible for a syndromic Mendelian form of childhood obesity. In 2016, he discovered that physical activity can blunt the effect of the obesity predisposing gene FTO in diverse ethnic groups. He also demonstrated that genes can predict the outcomes of different types of bariatric surgery.
Associate Professor of Economics at the H. Wayne Huizenga School of Business and Entrepreneurship at Nova Southeastern University.
Dr. Nguyen is a Principal Fellow and Lab Head of the Garvan Institute of Medical Research (Australia). He also holds joint appointments as Professor, St Vincent's Clinical School, University of New South Wales (UNSW Sydney); Professor of Predictive Medicine at the University of Technology Sydney (UTS); and conjoint Professor of Epidemiology and Biostatistics at the School of Medicine, University of Notre Dame Australia.
Corey Nislow's laboratory develops and uses cutting edge tools to address this central question: how can we understand the biological commonalities in all of the life sciences; from embryonic development, to the spread of infectious diseases to better ways to treat cancer. Each of these disciplines can be explained in the context of competition, interaction and evolution. His lab studies the interface between genes and the environment using parallel genome-wide screens, high throughput cell-based assays and next generation sequencing. Most recently, he and his scientific partner, Dr. Guri Giaever, are exploring how laboratory experiments can co-opt evolutionary processes to understand drug action. He enjoys teaching all aspects of biotechnology, genomics and drug discovery. He got his PhD from the University of Colorado, worked at several Biotechnology companies and was at Stanford and University of Toronto before joining UBC in 2013. He has published 161 papers and run 19 marathons.
I am a member of the Agents, Interaction and Complexity group, part of the Faculty of Physical and Applied Sciences at the University of Southampton, UK. I have a long-standing interest in using agent-based models to look at the evolution of social behaviour; I'm particularly interested in communication and social learning.
Zoran Obradovic is L.H. Carnell Professor of Data Analytics at Temple University, Professor in the Department of Computer and Information Sciences with a secondary appointment in Statistics, and is the Director of the Center for Data Analytics and Biomedical Informatics. He is an Academician at the Academia Europaea (link is external) (the Academy of Europe) and a Foreign Academician at the Serbian Academy of Sciences and Arts (link is external). He is the executive editor at the journal on Statistical Analysis and Data Mining, which is the official publication of the American Statistical Association and is an editorial board member at eleven journals. He was the chair at the SIAM Activity Group on Data Mining and Analytics for 2014 and 2015 years, was co-chair for 2013 and 2014 SIAM International Conference on Data Mining and was the program or track chair at many data mining and biomedical informatics conferences. His work is published in more than 300 articles and is cited more than 15,000 times (H-index 48).
I am a Professor in Biostatistics and Clinical Research Methodology in the Department of Clinical Medicine at the Miguel Hernández University (Spain).
My research is focused on biostatistics, clinical research methodology, cardiovascular diseases and pediatrics.
I am a behavior change professional on the cross-section between behavior change science (psychology), methodology and statistics and technology (ICT).
Main interests include: behavior change, statistics, methodology, online research methodology and intervention development.