Anthony Ebert

Dr Anthony Ebert

Italiano

Experience

2019-Present

Postdoctoral researcher; Università della Svizzera italiana, Swiss Federal Institute of Aquatic Science and Technology, and Harvard T.H. Chan School of Public Health

Statistical Inference on Large-Scale Mechanistic Network Models

2019

Teaching assistant; Università della Svizzera italiana

Statistics

2018
Casual lecturer, Mathematics and Statistics for Medical Science; Queensland University of Technology
2016-2017
Sessional academic tutor, Quantitative Methods in Science; Queensland University of Technology
2017
Mentor, Predictive Analytics: Gaining Insights from Big Data (Online course); Queensland University of Technology
2016
Teaching assistant, Big Data: Statistical Inference and Machine Learning (Online course); Queensland University of Technology
2012
Engineer; Atom Consulting
2010-2011
Course tutor, Products and Value Chains; University of Sydney
2007-2009
Year in Industry Internship Holder; ANSTO Minerals

Education

2016-2020

PhD, Statistics Queensland University of Technology

​Dynamic Queueing Networks: Simulation, Estimation and Prediction​

2015

Honours, Statistics; University of Western Australia

Predicting Bearing Failure using Joint Models with Longitudinal and Time-to-event Data

2013-2014
Bachelor of Science, Statistics; Australian National University
2010-2013

MPhil, Chemical Engineering; University of Sydney

Synthesis, Preparation and Assembly of Carbon Nanotube-Based Electrode Materials

2005-2009
Bachelor of Engineering, Chemical Engineering: University of Sydney

Pre-prints and publications

Ebert, A.​, Wu, P., Mengersen, K., & Ruggeri, F. (2017). Computationally Efficient Simulation of Queues: The R Package queuecomputer. ​arXiv:1703.02151. (Accepted to the Journal of Statistical Software)

Ebert, A., Dutta, R., Mengersen, K., Mira, A., Ruggeri, F., & Wu, P. (2019). Likelihood-free parameter estimation for dynamic queueing networks: case study of passenger flow in an international airport terminal. arXiv:1804.02526 (To revise and resubmit to the Journal of the Royal Statistical Society, Series C)

Liu, J., ​Ebert, A.​, Variava, M. F., Dehghani, F., & Harris, A. T. (2010). Surface modification and Pt functionalisation of multi-walled carbon nanotubes in methanol expanded with supercritical CO​2​. Chemical Engineering Journal​, 165(3), 974-979.

Statistical skills

approximate Bayesian computation, statistical network models, Bayesian hierarchical modelling, statistical distance, kernel methods, functional data analysis, curve registration, agent-based models, discrete event simulation, longitudinal data, mixed effects models, spline methods

Technical skills

Programming: ​R (5 years exp), Python, C++, Matlab, SQLite + Relational algebra (Stanford Online)

Operating Systems:​ Linux, OSX, Windows, High performance computing (PBS Pro)

Document preparation:​ LaTeX, Rmarkdown, Microsoft Office

Probabilistic programming: ​JAGS, STAN, OpenBUGS

R packages authored:queuecomputer (on CRAN), EasyMMD, protoABC

Referees

Professor Kerrie Mengersen
ARC Centre of Excellence in Mathematical and Statistical Frontiers (ACEMS), Queensland University of Technology, Brisbane, Australia
k.mengersen@qut.edu.au

Professor Fabrizio Ruggeri
Italian National Research Council in Milano, Italy & ACEMS, Queensland University of Technology, Brisbane, Australia
fabrizio@mi.imati.cnr.it

Dr Paul Wu
ARC Centre of Excellence in Mathematical and Statistical Frontiers (ACEMS), Queensland University of Technology, Brisbane, Australia
p.wu@qut.edu.au