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Ruth Etzioni
Professor at Fred Hutchinson Cancer Research Center- Models for Health Outcomes using Data from Population Registries and Surveys
Session 1 - Models for Health Outcomes using Data from Population Registries and Surveys
Session 2 - Statistical models for understanding population cancer trends and informing health policies | Plenary Address
- Roundtable | Data Science, Data Literacy and the Future of Statistics
Ruth Etzioni received her BS in Mathematics and Computer Science from the University of Cape Town in 1984. A chance encounter with a job advertisement on a department bulletin board led her to the field of statistical modeling and an Honors degree in Statistics and Operations Research at UCT. Following a meeting with Stephen E. Fienberg, the invited speaker at the SASA conference in 1985, she moved to the US where she completed to a PhD in Statistics at Carnegie-Mellon University in 1990. She is a full professor at the University of Washington and the Fred Hutch Cancer Center where she holds the Rosalie and Harold Rea Brown endowed chair. Her research focuses on the gaps in evidence that inevitably arise when making health care decisions, whether at the individual or policy level. Much of her work has been in the area of cancer diagnostics and early detection, particularly in breast and prostate cancer where she has leveraged disease trends from population registries to learn about unobservable but policy-driving phenomena including disease natural history and overdiagnosis. She works closely with the surveillance program at the National Cancer Institute, serves on several national cancer screening guidelines panels and was a member of a COVID modeling and policy group that informed the Washington State governor’s responses to the pandemic. She is a fellow of the American Statistical Association and has been the chair of its Health Policy Statistics Section. She has developed a popular graduate-level course on the modeling of health outcomes using large observational databases on which her textbook, “Statistics for health data science: an organic approach,” is based.
Robert Gramacy
Professor at Virginia Polytechnic and State University- A Practical Introduction To Gaussian Process Regression and Bayesian Optimization
Session 1 - A Practical Introduction To Gaussian Process Regression and Bayesian Optimization
Session 2 - Deep Gaussian Process Surrogates for Computer Experiments | Plenary Address
- Roundtable | Data Science, Data Literacy and the Future of Statistics
Prof Robert Gramacy is a Professor of Statistics in the College of Science at Virginia Polytechnic and State University (Virginia Tech/VT) and affiliate faculty in VT's Computational Modeling and Data Analytics program. Previously, Prof Gramacy was an Associate Professor of Econometrics and Statistics at the Booth School of Business, and a fellow of the Computation Institute at The University of Chicago. His research interests include Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, sequential design, and optimization under uncertainty.
Edzer Pebesma (Online)
Professor at University of Münster, Institute for Geoinformatics- Spatial statistical questions and big spatial datasets | Plenary Session
- An Introduction to Spatial Data Science with R
Session 1 - An Introduction to Spatial Data Science with R
Session 2
Edzer Pebesma leads (since 2007) the spatiotemporal modelling lab at the Institute for Geoinformatics of the University of Muenster, Germany. His research interests include spatial statistics, analysis of environmental and remote sensing data, open science and reproducibility, interoperability and open source software development. In the past he was editor of Computers & Geosciences and the Journal of Statistical Software, and associate editor of Spatial Statistics. He is an ordinary member of the R foundation, and is a major contributor to the R-spatial package ecosystem.
Mark Nasila
Chief Data and Analytics Officer at FirstRand Risk- Emerging technologies, globalization and social challenges are redefining the role of intelligent decisioning | Keynote Address
- Roundtable | Data Science, Data Literacy and the Future of Statistics
Dr Mark Nasila is the Chief Data and Analytics Officer of FirstRand Risk, and a Singularity University Faculty member. He is also a steering committee member of the National Institute for Theoretical Physics and Computational Sciences (NITheCS). As an experienced AI and data science expert, he ensures the techniques and methodologies he introduces into FNB are at the forefront of where banking is headed, both locally and internationally. He is the developer and the brain behind Manila, an AI system FNB has harnessed to reimagine its risk management and forensic due diligence processes. Dr Nasila has presented at local and international conferences, such as the: • Business-Tech Digital Banking Conference - SA • Chief Data & Analytics Officer forums in South Africa and the UK • European Simulation & Modelling Conference. He has published and written opinion pieces in Business Day, Mail & Guardian, TechCentral, Daily Maverick, CIO Talk Network, CIO.com, Corinium Intelligence and the European Simulation & Modelling Association. He holds a PhD in Mathematical Statistics from the Nelson Mandela University, and is also an alumni of the SingularityU South Africa Executive programme. He was named one of the Corinium Global Intelligence ‘2020 Global Top 100 Innovators in data and analytics’.
Sheetal Silal
Director of Modelling and Simulation Hub, Africa (MASHA)- Towards evidence-based public health management: the role of Statistics and Modelling in South Africa | Keynote Address
- Roundtable | Data Science, Data Literacy and the Future of Statistics
Prof Sheetal Silal is the Director of the Modelling and Simulation Hub, Africa (MASHA) and associate Professor in the Department of Statistical Sciences at the University of Cape Town (UCT). She is an Honorary Visiting Research Fellow in Tropical Disease Modelling at the Nuffield Department of Medicine at Oxford University. She received a PhD in Mathematical Modelling of Infectious Diseases in 2014 from UCT. Her primary research area is the development and application of mathematical models to malaria, pertussis, syphilis, COVID-19, and other infectious diseases in South Africa, sub-Saharan Africa and globally, with a focus on using mathematical models to predict the dynamics and control of diseases to evaluate the potential impact of control programmes in reducing morbidity and mortality, and supporting policy development. Prof Sheetal Silal is leading the development of COVID-19 transmission models as part of the South African COVID-19 Modelling Consortium. The Modelling Consortium is a group of researchers from academic, non-profit, and government institutions across South Africa where the mandate of the group is to provide, assess and validate model projections to be used for planning purposes by the Government of South Africa.
Ashwell Jenneker
Deputy Director General of StatsSA- Roundtable | Data Science, Data Literacy and the Future of Statistics
- Census 2022 Journey: Updating the nations statistical landscape | Keynote Session 3
Ashwell Jenneker has been the DDG for Statistical Support and Informatics at Statistics South Africa since 2008. Ashwell started his career at Stats SA as a Statistical Training Officer before progressing to Deputy Director of Marketing, Acting Director of Communication for the Census 2001, Executive Manager of Statistical Information Services and Executive Manager of the Data Management and Information Delivery Project (DMID) before his DDG appointment where he is currently responsible for Statistical Operations and Provincial Coordination. Ashwell has a Masters degree in Urban and regional sciences from the Stellenbosch University in South Africa and has a BSc (honours) in mathematics and a higher diploma in education from the University of Western Cape. He is a Fellow of the seventh class of the Africa Leadership Initiative-South Africa.
Renette Blignaut
2021 SAS® Thought Leader and Professor at University of the Western Cape- Roundtable | Data Science, Data Literacy and the Future of Statistics
- Can statisticians ignore data science, or should it be embraced? | Keynote Address | SAS® Thought Leader 2021
Rénette Blignaut manages the UWC Data Science programmes. She as been the HOD or DHOD of the Statistics and Population Studies Department at UWC for 24 of the 30 years in the academic environment. Prior to this she worked in industry for 9 years whilst completing her Honours in Mathematical Statistics (Pretoria), M.Sc. in Mathematical Statistics (UCT) and her PhD (Pretoria) on a part-time basis. Her PhD thesis: “Modelling of claim patterns of members of private medical aid schemes” was completed in 1995. Since then she has been conducting research in various fields namely: data mining, statistical learning, predictive modelling, biostatistics, mobile security, internet access and science education. In 2001, she was promoted to associate professor and in 2015 promoted to full professor. She has published more than 78 accredited articles, 22 technical reports, presented more than 53 international and 50 national conference presentations and 56 workshop presentations. Supervised or co-supervised 29 masters and 6 PhD students.
In 2021, Rénette was awarded the South African Statistical Association's Thought Leader Award for significant contributions in academia, industry, government and elsewhere. She is the second female to have been awarded this award.
Rénette currently serves as Chairperson of the Data Science Academic Committee of the National Graduate Academy for Mathematical and Statistical Sciences (NGA MaSS). She furthermore serves on the Steering Committee and the Advisory Board of the NGA MaSS. She was appointed on the Governing Board of the Centre for Multi-dimensional Data Visualisation at Stellenbosch University (Apr 2022- Mar 2025).
Married to Jacques, an attorney, they have two daughters, one a data scientist completing a PhD in Mechatronic/Biomedical Engineering and the other a medical doctor.
Pravesh Debba
2020 SAS® Thought Leader and Manager for Inclusive Smart Settlements and Regions at CSIR- Roundtable | Data Science, Data Literacy and the Future of Statistics
- Statistical Science: Enriching our lives | Keynote Address | SAS® Thought Leader 2020
Professor Pravesh Debba was born in KwaZulu Natal, South Africa. He obtained a BSc degree with majors in Mathematics and Statistics from the University of KwaZulu-Natal (UKZN) in 1991. He completed an honours degree in Statistics from UKZN in 1992. In 1998, he completed an MSc degree in Biostatistics at Hasselt University in Belgium. He was awarded a full scholarship from the Flemish Ministry of Education during this period. He completed his PhD in Spatial Statistics in 2006 from the International Institute for Geo-Information Science and Earth Observation ITC and Wageningen University in the Netherlands. He was awarded a scholarship from ITC and grants from NRF Thuthuka during 2003–2008. Professor Debba is currently the manager for Inclusive Smart Settlements and Regions within Smart Places at the Council for Scientific and Industrial Research (CSIR). Professor Debba has been the president of the South African Statistical Association (SASA) from 2010–2011 and Chairperson of the Institute for Certificated and Chartered Statisticians of South Africa (ICCSSA) from 2014–2018. He was appointed as the chair of the Body of Trustees of ICCSSA since 2018. Professor Debba has supervised MSc and PhD students. His research achievements include, about 50 national or international presentations at conferences or workshops, three popular articles, and over 50 peer-reviewed publications published at ISI rated journals or conference proceedings. He is also a co-producer of a technology demonstrator in the field of remote sensing. His field of applied research is in the areas of Remote Sensing, GIS, Spatial Statistics, Space-Time Models, Design of Optimal Sampling Schemes. His most recent awards include the 2020 SASA-SAS Thought Leadership Award, 2019 ICCSSA Charter Award, 2018 CSIR CEO Award, 2016 CSIR Management Excellence Award, 2016 and 2014 CSIR Collaboration Award.
Rajat Mukherjee (Bayes Workshop Presenter)
VP Advanced Statistics & Data Science at Alira Health- Bayes Interest Group | Use of informative priors in confirmatory studies, along with a hands-on session in R | Session 1
- Bayes Interest Group | Use of informative priors in confirmatory studies, along with a hands-on session in R | Session 2
- Bayes Interest Group | Use of informative priors in confirmatory studies, along with a hands-on session in R | Session 3
- Bayes Interest Group | ISBA President Address
Rajat has over 25 years of experience in Biostatistics within both pharmaceutical companies, and academic institutions.
Rajat joined Alira Health in April 2022 as VP Advanced Statistics and Data Sciences. In his current role his main responsibilities include definition and implementation of long-term business strategies in collaboration with Alira Health leaders from various practices such as Market Access, RWE, Regulatory and Management consulting and to provide strategic statistical consulting for clinical pipelines and clinical trials. His main areas of expertise include Bayesian and Adaptive trial designs, application of Machine Learning and AI for diagnostics and biomarker discovery and statistical computation to facilitate the incorporation of complex endpoints in clinical trials. Rajat is also keen in developing statistical software to empower statisticians and clinical trialists.
In his previous position Rajat acted as a Senior Research Fellow/Consultant for Cytel, leading innovative clinical trials design activities including trials under the CID (FDA) program. In addition, his responsibilities included consulting in areas of Bayesian adaptive designs, big-data, biomarker discovery and machine learning. He was a part of the executive team for developing consulting business strategies, thought leadership activities (research publication, conferences, etc.), and mentoring fellow consultants.
Rajat holds a PhD degree in Mathematical Statistics from the University of Wisconsin-Madison (USA), a MSc degree in Applied Sciences from Bowling Green State University, Ohio (USA), and a BSc degree in Statistics from the Presidency College, Calcutta (India).
Berthold Lausen
Professor at University of Essex- New Developments in Data Science and Data Science in Africa
Session 1 - New Developments in Data Science and Data Science in Africa
Session 2
Berthold Lausen has 35 years of experience as medical and trial statistician and data scientist. He contributed to the first conference of the International Federation of Classification Societies (IFCS) in 1987 with a cutting-edge proposal of a three-objects variance estimator and parametric bootstrap to evaluate the confidence and stability of unsupervised learning with DNA-DNA hybridisation data (with P. O. Degens). He made influential contributions to develop machine learning and nonparametric methods for medical statistics and data science as for example maximally selected rank statistics, p-value adjusted classification and regression trees, bagging survival trees (with M. Schumacher and others). He is past president of IFCS (2020-22; former president 2018-19, president elect 2016-17), a former president of Data Science Society (GfKl) (2013-19, vice-president 1995-2001, 2004-13) and the founding vice-president of European Association for Data Science (EuADS) 2015-18. Since 1986 he is member of the International Biometric Society (IBS) and Data Science Society (GfKl), since 1998 a fellow of the Royal Statistical Society (RSS) and since 2015 a founding member of the European Association for Data Science (EuADS).
Since 2010 Lausen is Professor in Biometry and Epidemiology at School of Medicine of the University of Erlangen-Nuremberg and 2012-17 full Professor of Statistics and since 2017 of Data Science at the Department of Mathematical Sciences, University of Essex. 2016-21 Head of Department, while the department grow substantially (624 students - up 158% from 242 students in 2017, 37 permanent academic staff - up 118% from 17 permanent academics in 2017). He is on sabbatical (2021-23).
He is principal investigator of data science driven Knowledge Transfer Partnerships (KTP) of Innovate UK with Profusion (funded 2014-22), KTP with Mondaq (funded 2016-2022) and a partnership with Rolls-Royce Motor Cars (funded 2021-25). Contributor to the Business and Local Government Data Research Centre, University of Essex, ESRC (funded 2019-22).
He is an associated editor of Behaviormetrika, and a member of the editorial board of Advances Data Analysis and Classification, Archives of Data Science Series A and of Methods of Information in Medicine.
Dianne Cook (MDAG Workshop Presenter)
Professor at Monash University- MDAG Workshop | Visual methods for multivariate data - a journey beyond 3D | Session 1
- MDAG Workshop | Visual methods for multivariate data - a journey beyond 3D | Session 2
Dianne Cook is Professor of Business Analytics at Monash University in Melbourne, Australia. Her research is in the area of data visualisation, especially the visualisation of high-dimensional data using tours with low-dimensional projections, and projection pursuit. A current focus is on bridging the gap between exploratory graphics and statistical inference. Technology plays an important role in data visualisation for evaluating effectiveness and for public consumption. Di utilises technology such as virtual environments, Amazon’s Mechanical Turk, and eye-tracking in her work, and makes an effort to share her work with open source software. Di is a Fellow of the American Statistical Association, elected member of the International Statistical Institute, past-editor of the Journal of Computational and Graphical Statistics, elected Member of the R Foundation, and current editor of the R Journal. Education is an important part of her contributions, and mentoring graduate research is a significant activity. Several of her students have won the prestigious American Statistical Association John Chambers Software Award, including Hadley Wickham, Yihui Xie, Carson Sievert, and most recently, Monash student Earo Wang
David Hofmeyr (Online MDAG Workshop Presenter)
Senior Lecturer at Stellenbosch UniversityDavid is currently employed as a senior lecturer in the department of statistics and actuarial science at Stellenbosch University, a post which he has held since January 2017. David sits on a number of committees, both internal and external to the university, including for the National Graduate Academy for Data Science. Prior to joining Stellenbosch University, David held a one year post doctoral fellowship within the STOR-i center for doctoral training, at Lancaster University.
David received his PhD from the STOR-i CTD at Lancaster, where his research was on finding optimal projections for cluster analysis. He has a master of research from Lancaster in statistics and operations research, and a master of science from Edinburgh University in operations research. His bachelor's degree had as majors mathematics and mathematical statistics, and his honours is in pure maths (from WITS and UCT respectively).
David continues to work on the problem of finding optimal projections for clustering, and has also extended his scope into (primarily) the areas of model selection, non-parametric smoothing, and the clustering problem in general. However, he has peripheral interest in a large collection of areas relevant to data science, machine learning and methodological statistics.
Sudipto Banerjee (Online Bayes Workshop Presenter)
President at ISBASudipto Banerjee is currently Professor and Chair of the UCLA Department of Biostatistics with joint appointments in the UCLA Department of Statistics and the UCLA Institute of the Environment and Sustainability. He also serves as the 2022 President of the International Society for Bayesian Analysis. He has worked on a number of problems on spatial statistics, developing theory and methods related to Bayesian modeling and inference for geographic data with wide-ranging applications in public and environmental health sciences, ecology, forestry, real estate economics and agronomy. He has published 2 textbooks and an edited handbook. His contributions have been recognized through many honours, including the Abdel El-Shaarawi Award from The International Environmetric Society (TIES), the Mortimer Spiegelman Award from the American Public Health Association and the George W. Snedecor Award from the Committee of Presidents of Statistical Societies (COPSS), elected membership of the International Statistical Institute, elected fellowships in the Institute of Mathematical Statistics (IMS), the American Statistical Association (ASA), the International Society for Bayesian Analysis and the American Association for the Advancement of Science (AAAS), a Distinguished Achievement Medal from the ASA's Section on Statistics and the Environment, and the ASA's Outstanding Statistical Application Award.