career
My career trajectory.
Basics
| Name | Edwin V. Bonilla |
| Label | Machine Learning Research Scientist |
| edwin.bonilla@data61.csiro.au | |
| Url | https://ebonilla.github.io |
| Summary | Machine learning scientist driven by challenging problems in probabilistic modelling, causal discovery and inference, and the optimal design of experiments. |
Work
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2023.07 - Present Senior Principal Research Scientist and Science Leader
CSIRO's Data61
Lead a team of 8–10 researchers in developing new methods for foundational machine learning.
- New algorithms for causal discovery
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2018.08 - 2023.06 Principal Research Scientist
CSIRO's Data61
Led research on Bayesian inference, deep learning and decision making.
- New algorithms for network graph analytics and optimal design of experiments
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2014.11 - 2018.08 Senior Lecturer
UNSW
Research on scalable probabilistic inference.
- Developed scalable inference methods for Gaussian process models with state-of-the-art performance
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2010.01 - 2014.10 Researcher/Senior Researcher
NICTA
Research on non-parametric Bayesian methods.
- Data fusion methods for the characterisation of geothermal energy targets
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2007.11 - 2009.12 Research Associate
The University of Edinburgh
Research on compiler optimization with machine learning
- Delivered a machine learning model for the world’s first open-source machine-learning compiler
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2003.06 - 2003.09 Software Engineer
Casa Editorial El Tiempo
Software development and support across all businesses
- Developed software applications for managing the cash flow of the company
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2001.10 - 2003.02 Software Developer
Inpesa Ltd, Ecopetrol ICP
Machine learning techniques for the characterisation of oil fields
- Development and integration of the tool Oil Field Intelligence (OFI)
Education
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2004.10 - 2008.12 Edinburgh, UK
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2003.10 - 2004.09 Edinburgh, UK
MSc with Distinction
The University of Edinburgh
Predicting good compiler transformations using machine learning
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1996.01 - 2001.01 Bucaramanga, Colombia
Awards
- 2023
Best Student Research Paper Award
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
- 2019
Outstanding Contribution
NeurIPS' Graph Representational Learning Workshop
Variational Graph Convolutional Networks
- 2019
Test-of-time paper award
International Symposium on Code Generation and Optimization (CGO)
Automatic Feature Generation for Machine Learning Based Optimizing Compilation
- 2017
Test-of-time paper award
International Symposium on Code Generation and Optimization (CGO)
Rapidly Selecting Good Compiler Optimizations using Performance Counters