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Dianne Cook
Professor of Statistics at Monash University
Professional Background
Dianne Cook is a distinguished researcher and educator in the field of statistics and data visualization, known for her innovative approaches in exploratory data analysis, multivariate methods, data mining, and statistical computing. With a career marked by contributions to significant software projects, including XGobi, GGobi, and various R packages, her work has greatly influenced how data is visualized and interpreted across different scientific and commercial domains. Cook has held the esteemed position of Professor of Business Analytics at Monash University, where she applied her expertise to enhance the understanding of complex data sets.
Cook's research interests are vast and varied, encompassing the visualization of data in virtual environments and the development of sophisticated methods that bridge the gap between statistical inference and exploratory graphics. Her dedication to advancing the field is reflected in her involvement in projects that utilize cutting-edge technology, such as Amazon's Mechanical Turk and eye-tracking equipment, to conduct experiments that refine the understanding of visual data representation.
Throughout her career, Dianne has participated in a plethora of projects, ranging from studies on the ecological interactions of butterfly populations in Yellowstone to statistical analyses of drug studies and the impact of climate change on various ecosystems. This diverse portfolio showcases her versatility and commitment to applying statistical methods for solving real-world problems.
Education and Achievements
Dianne Cook's educational journey laid a solid foundation for her illustrious career in statistics and data visualization. She earned her Doctor of Philosophy (PhD) in Statistics from Rutgers University, one of the top statistical departments in the nation. Before that, she completed her Bachelor of Science and Diploma of Education in Mathematics and Statistics from the University of New England in Australia, where she honed her skills in analytical thinking and quantitative methods.
The blend of her rigorous academic training and her passion for teaching has allowed Dianne to engage and inspire students in the realm of business analytics. Her work not only contributes to the academic community but also provides valuable insights for industry professionals seeking to leverage data analytics in their decision-making processes.
Noteworthy Contributions
Dianne Cook has made remarkable contributions to the field of data visualization through her innovative methodologies and collaborative projects. Some of her most notable work includes:
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Software Development:
- Co-developing XGobi and GGobi, two prominent interactive data visualization tools that allow users to explore complex data sets dynamically. These tools have been utilized across various disciplines, enhancing the understanding of multivariate data.
- Contributing to several R packages that extend the capabilities of statistical analysis and visualization in accessible ways for researchers and practitioners.
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Method Development:
- Creating pioneering methods such as tours, projection pursuit, and manual controls that empower users to interact with and interpret their data visually. Her efforts in developing a grammar of graphics tailored for biological data have also been instrumental in advancing the representation of complex biological phenomena.
- Developing pipelines for interactive graphics that facilitate user engagement and promote deeper insights into the data.
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Research Applications:
- Dianne has applied her expertise to an array of research projects, which include:
- Backhoes and their operational analytics
- Investigative studies into drug efficacy and public health trends
- Research on mud crab growth concerning environmentalchanges
- Analyses of gene expression data relevant to critical biological questions
- Evaluating climate change impacts through data analytics and visualization
- Studying butterfly population dynamics in Yellowstone National Park and their relevance to ecological conservation efforts
- Utilizing stimulus funds spending data to assess economic impacts
- Contributing to NRC rankings of graduate programs using statistical methodologies
- Analyzing technological trends during boom and bust cycles
- Engaging with election polling data to understand voting behavior
- Investigating soybean breeding and common crop population structures in agricultural research
- Exploring insect gall to plant host interactions to contribute to ecological studies
- Conducting statistical studies on soccer and tennis analytics demonstrating profound connections between statistical insights and sports performance.
- Dianne has applied her expertise to an array of research projects, which include:
Dianne’s extensive portfolio not only reflects her deep knowledge of statistical design and data visualization but also underscores her commitment to solv
Highlights
The Section on Statistical Computing and Data Visualisation of the Statistical Society of Australia is excited to offer a series of tutorials on Mar 26:
🚀 Calling all data enthusiasts! Join "Introduction to Machine Learning with tidymodels" led by Max Kuhn. Elevate your modelling skills with hands-on tidymodels in R. Prerequisites: solid R knowledge and familiarity with data wrangling and visualization. Let's level up together! #MachineLearning #tidymodels #DataScience SOLD OUT!
🌍 Unlock the power of spatial uncertainty visualization with Petra Kuhnert! Join us to learn about Vizumap and incorporate uncertainties into spatial predictions. Prerequisites: R proficiency and modelling background. Let's map out a clearer future! #SpatialUncertainty #Vizumap #ResearchScience
🌌 Dive into the world of high-dimensional data visualization with Di Cook! Learn to recognize patterns, identify clusters, and reduce dimensionality effectively using R. Prerequisites: R proficiency and multivariate statistical methods. Ready to visualize the future? #DataVisualization #HighDimensionalData #RStats
Details and registration at https://lnkd.in/ggtvETM9
The Monash Business Analytics Team is organising a workshop on December 7. The topic of the workshop is "Communicating with Data", and the invited speaker sessions are divided into three theme areas: environment, health and sports. Amanda Cox from USAFacts, and previously the New York Times, is the keynote speaker. Amanda’s web site, https://lnkd.in/gM--XVXQ, has a lot of examples of her work. Casey Briggs, from the ABC, and Liam Mannix, from the Age, are speaking in the health session.
Details of the workshop, and first day tutorials, can be found by visiting the "Find out more and register here” link at https://lnkd.in/g9s7q-Bq.
There are 8 virtual tutorials on Dec 6:
9:00-12:00 Morning tutorials AM-1 Effective Data Visualisation with R, Dr Emi Tanaka AM-2 Collaborative projects with git and GitHub, Dr Patricia Menéndez AM-3 Optimisation in Python and its application in carbon portfolio, Dr Jess Leung AM-4 Wrangling spatio-temporal data in R, H. Sherry Zhang (and Prof Di Cook) 1:00-4:00 Afternoon tutorials PM-1 Interactive web applications with Shiny for R, Mitchell O'Hara-Wild PM-2 Exploratory time series analysis using R, Prof Rob Hyndman PM-3 Bayesian Inference and regression using R and Stan, Dr Lauren Kennedy PM-4 Spatio-temporal visualisation for natural disasters, Dr Kate Saunders
The cost for everything is really low, with the goal being to simply cover the costs of running the event. The number of participants is limited to 60 for the workshop and 20 for each tutorial, so if you are interested please register early. Please feel free to share this information.
