Dr Emi Tanaka

Dr. Emi Tanaka is an applied, academic statistician at the Australian National University with a passion for data science and open source software. Her primary interest is to develop impactful methods and tools that can be readily used by practitioners. She interfaces across multiple disciplines to bridge statistical concepts and findings to a broad range of individuals. To this end, she has developed numerous open-source tools, primarily as R-packages, and resources aimed at making statistical methods accessible to a diverse audience. 

Emi demonstrates a proactive approach to community development and education through her involvement in the branches of the Statistical Society of Australia (SSA) and other committees. She delivers numerous statistical workshops including in data visualisation, data wrangling, reproducible practices, statistical modelling and statistical consulting. Her contributions are recognised with the SSA Distinguished Presenter's Award, SSA President’s Award for Leadership in Statistics, and being featured in the list of 60 prominent Australian statisticians in the Significance magazine.

Emi is a big advocate of open science and an avid research software engineer. She is highly proficient in the R language, used to code in Python and Bash, practices computational reproducibility using R Markdown (now Quarto) and Git, and dabbles in UI, UX and front-end web development (HTML/CSS/JS). Most of her code is available on her GitHub profile.

She is currently the Chief Editor of the R Journal and leads the ANU Analytics for the Australian Grains Industry project. At ANU, she has run a number of R and statistical workshops (available here) and lectures STAT1003 (Statistical Techniques).

Her applications have primarily focused on bioinformatics and plant sciences (particularly plant breeding), but she has a wide interest in data-driven processes. She likes to ponder about the human aspects of the process and adopts a holistic view to solve problems.

• Personal webpage: https://emitanaka.org/
• GitHub: https://github.com/emitanaka/
• CV: https://emitanaka.org/cv.html

• Experimental design,
• Mixed models (also known as multi-level models, panel data models or hierarchical models),
• Data visualisation and visual inference,
• Applications in bioinformatics and selective breeding (particularly plant breeding),
• Emerging analytics (e.g. machine/deep learning, computer vision and large language models),
• Statistical software development, particularly in R, and
• Statistical workflow/practice (encompassing reproducibility, design, infrastructure and communication).