Contact

Skills

  • Expert: R, HTML/CSS, LaTeX
  • Intermediate: Git/GitHub, Python, Bash, JS
  • Languages: English (fluent) and Japanese (conversational)

Interests

  • Research: experimental design, mixed models, data visualisation, bioinformatics, statistical genetics, selective breeding
  • Non-Research: drawing (but not good at it), reading (manga, manhwa and non-fiction books)

This resume was made with the R package pagedown.

Last updated on 2021-03-31.

Emi Tanaka

Work Experience

Lecturer
Monash University,
Department of Econometrics and Business Statistics
2020/01 - current
Lecturer
The University of Sydney,
School of Mathematics and Statistics
2017/01 - 2019/12
Research fellow
University of Wollongong,
School of Mathematics and Applied Statistics
2014/01 - 2017/01

Education

PhD, Statistics
Statistical Methods for Improving Motif Evaluation

Supervisor: Dr. Uri Keich
School of Mathematics and Statistics
The University of Sydney, Sydney, Australia, 2015

Bachelor of Science (Advanced Mathematics), Honours I
Major in Mathematics and Statistics

The University of Sydney, Sydney, Australia, 2010

Publications

  1. Morota, G, Cheng, H, Cook, D, & Tanaka, E (2021) ASAS-NANP SYMPOSIUM: Prospects for interactive and dynamic graphics in the era of data-rich animal science. Journal of animal science, 99(2). Citations: 1.
  2. Tanaka, E (2020) Simple outlier detection for a multi-environmental field trial. Biometrics, 76(4), 1374-1382. Citations: 4.
  3. Tanaka, E & Hui, F (2019) Symbolic formulae for linear mixed models. Statistics and data science, 3-21
  4. Hui, F, Tanaka, E, & Warton, D (2018) Order selection and sparsity in latent variable models via the ordered factor LASSO. Biometrics, 74(4), 1311-1319. Citations: 6.
  5. Norman, A, Taylor, J, Tanaka, E, Telfer, P, Edwards, J, Martinant, J, & Kuchel, H (2017) Increased genomic prediction accuracy in wheat breeding using a large australian panel. Theoretical and applied genetics, 130(12), 2543-2555. Citations: 16.
  6. Tanaka, E, Ral, J, Li, S, Gaire, R, Cavanagh, C, Cullis, B, & Whan, A (2017) Increased accuracy of starch granule type quantification using mixture distributions. Plant methods, 13, 107. Citations: 5.
  7. Tanaka, E (2014) Statistical methods for improving motif evaluation. PhD Thesis
  8. Tanaka, E, Bailey, T, & Keich, U (2014) Improving MEME via a two-tiered significance analysis. Bioinformatics, 30(14), 1965-1973. Citations: 17.
  9. Liachko, I, Tanaka, E, Cox, K, Chung, S, Yang, L, Seher, A, Hallas, L, Cha, E, Kang, G, Pace, H, Barrow, J, Inada, M, Tye, B, & Keich, U (2011) Novel features of ARS selection in budding yeast lachancea kluyveri. BMC genomics, 12, 633. Citations: 22.
  10. Tanaka, E, Bailey, T, Grant, C, Noble, W, & Keich, U (2011) Improved similarity scores for comparing motifs. Bioinformatics, 27(12), 1603-1609. Citations: 49.

Citation counts are sourced from Google Scholar at 2021-03-31.

Software

Talks

List of talks (and links to the slides if available) are at https://emitanaka.org/talks.html.
Below show the last 10 talks.

Visual Inference
FukuokaR
2021-03-27
The Grammar of Experimental Design
TokyoR
2021-01-23
Advent of “Grammar”: Bridging Statistics and Data Science for the Design of Experiments
Statistical Society of Australia
2020-11-27
Rethinking the framework to specify the design of experiments
Department of Agriculture and Fisheries, Queensland
2020-11-11
What every young statistician should know: Developing your identity, networking and marketing
Statistical Society of Australia Western Australian Branch
2020-09-30
Advent of “Grammar”: Bridging Statistics and Data Science for the Design of Experiments
Monash Bioinformatics Seminar
2020-07-15
Beyond Beamer: Modern and Dynamic Presentations with R Markdown
Statististical Society of Australia Canberra & NSW Branch
2020-06-23
Software design, selection and estimation for latent variable models
WOMBAT
2019-11-28
Symbolic model formulae for linear mixed models illustrated with the analysis of agricultural data
Department of Mathematics and Statistics, Macquarie University
2019-10-15
Symbolic model formulae for linear mixed models illustrated with the analysis of agricultural data
Research School of Finance, Actuarial Studies and Statistics, Australian National University
2019-09-16

Workshops

Data Wrangling with R
2020/12
Hosted by Statistical Society of Australia NSW Branch.
Data Visualisation with R
2020/11
Co-presented with Di Cook.
Hosted by Statistical Society of Australia VIC Branch.
Tidyverse and R Markdown Workshop
2019/12
Hosted by International Biometrics Society Australasia Region.
R Package & R Markdown Workshop
2019/11
Co-presented with ‪Damjan Vukcevic.
Hosted by Statistical Society of Australia VIC Branch.
Statistical Methods for Omics Assisted Breeding
2018/11
Co-presented with Gota Morota, Diego Jarquin, Malachy Campbell, Jessica Tressou, Hiroyoshi Iwata.
Hosted by Univeristy of Tokyo.

Service

President
Statistical Society of Australia, Victoria Branch
2021/03-ongoing
Vice President
Statistical Society of Australia, Victoria Branch
2023/03-2024/03
Assistant Secretary
Statistical Society of Australia, NSW Branch
2017/03-2018/03
Secretary
Statistical Society of Australia, NSW Branch
2018/03-2020/03
Social Media Coordinator
International Biometrics Society, Australaisan Region
2018/01-ongoing
Member
useR! 2021, Program Committee
2021/03-2021/03

Professional memberships

  • Statistical Society of Australia
  • International Biometrics Society

Awards & Distinctions

ARC Centre of Excellence
Associate Investigator
ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS)
2020
ARC Industrial Transformation Training Centre
Chief Investigator
Data Analytics for Resources and Environments (DARE)
2019
$3,973,202
R Consortium Grant
Lead Investigator
Symbolic Formulae for Linear Mixed Models
2019
$6,000
Sydney Institute of Agriculture Research Project Grant
Chief Investigator
Land surface models of carbon and water do not work in agricultural landscapes where it actually matters they work
2018
$90,000

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