Emi Tanaka

@emitanaka.org

2706 Followers 259 Following

Statistical Data Artist & Scientist at Australian National University 🇳🇿 Interested in mixed models, experimental design, plant breeding 🌱, bioinfo 🧬, data vis 📊, statistical practice, ML/AI 👩🏻‍💻 Dabbles in UI, UX, front-end & #rstats 📦 dev emitanaka.org

Wifi
AAGI symposium
Change to css
the UI design principles and the two UI approaches
Conference signs
exceedance plot ggplot(nc) + geom_sf(aes(fill = duo_exceed(value, sd)))
Patrick presenting about generalised linear models
No Statistics, No Deal Statistics are more than numbers; statistics are society’s mirror. Without reliable statistics, democracy falters, markets waver, and citizens lose the means to hold power to account. Reliable figures on growth, jobs, inflation, health, environment and education allow people to judge for themselves, based on impartial evidence rather than political spin. When statistics vanish, speculation fills the gap — and trust disappears. Statistics underpin international scientific cooperation in fields ranging from vaccine innovation to climate research and sustainable development by providing accessible and shared sources of evidence. When their integrity is undermined, mistrust can spread across borders. An attack on statistics and science in one country can quickly become a political export, replicated elsewhere by actors with similar objectives.
Hex stickers on laptop
Presenting to the UTokyo Lab of Biometry and Bioinformatics
The Vice-Chancellor’s Awards for Programs that Enhance Learning
Two upcoming talks: Growing success with statistics in plant breeding Forum “Math for Industry” 2025-08-19 Leveraging large language models in a composable system to design and simulate plant experiments EUCARPIA Biometrics in Plant Breeding 2025-09-17
Huddling for group photo 📷
A photo of Yidi in front of his office
The stage of the town hall
The number of ANU researchers by college
Zoom invoice
Fonti sitting in her new office
Analytics for the Australian Grains Industry (AAGI) aims at harnessing analytics to drive the sector’s profitability and global competitiveness. AAGI has a national network with partnerships across multiple organisations. Australian National University (ANU) is one of those partners. ANU-AAGI aims to consolidate analytical expertise to solve agricultural problems across ANU. Any ANU staff/student interested in contributing can join this effort. Email emi.tanaka@anu.edu.au if you would like to join. For more information see here: https://anu-aagi.github.io/.
An animation of the Australian election results in choropleth map to hex map
Two sausage sizzles
A Bachelor of Agricultural Science, Mathematics, Data Science, Computer Science or in a field relevant to the position (e.g. bioinformatics, statistics) from a recognised tertiary institution or equivalent academic qualifications.
Shop front for Rojiura curry samurai
an app to find the best line of fit to bivariate data
an interactive app to demonstrate central limit theorem
A gif showing an interactive simulation of binomial experiments compared to its theoretical distribution and properties
Perth weather - heat alert
ANU-AAGI team featuring investigators: Eric Stone, Emi Tanaka, Alan Welsh and Francis Hui
a graph showing how the number of articles and people working are increasing
working shiny app
the slide with three speakers
Water bottle
App not working
The plot of funding amount for each FOR for ARC discovery project starting in 2025
code that calls the tool calling in LLM via elmer
Originator of experiment
The title slide for my talk "Building computational frameworks for enchanced practice of statistics"
Slide title page that says Architecture of large language models
A slide that says "Let's discuss" and How do LLMs complement or hinder statistical thinking? What role should LLMs play in decision-making processes and research? How will LLMs impact the training and development of future statisticians and data scientists? What are the use cases of LLM for you (if any)?
A landing page for the CRAN R package edibble with the DOI highlighted.
Why are open source statistical programming languages the best? Because they R
Backcasting
the abstract of the edibble paper