Sotabase

Career

· Professor, University of Melbourne2013–
· PhD Student, University of California, Berkeley2004–2010
· Master of Computer Science, University of Melbourne2003–2004
· Bachelor of Engineering (First Class Hons), University of Melbourne1999–2002
· Bachelor of Science, University of Melbourne1999–2002
· Researcher, IBM Research Australia
· Researcher, Microsoft Research Silicon Valley

Publications (141)

Adversarial machine learning
Security and Artificial Intelligence · 2019
1,522
cited
ANTIDOTE: understanding and defending against poisoning of anomaly detectors
ACM/SIGCOMM Internet Measurement Conference · 2009
425
cited
Exploiting Machine Learning to Subvert Your Spam Filter
USENIX Workshop on Large-Scale Exploits and Emergent Threats · 2008
391
cited
A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration
Proceedings of the VLDB Endowment · 2012
352
cited
Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning
Journal of Privacy and Confidentiality · 2009
301
cited
Identifying At-Risk Students in Massive Open Online Courses
AAAI Conference on Artificial Intelligence · 2015
202
cited
Link prediction by de-anonymization: How We Won the Kaggle Social Network Challenge
The 2011 International Joint Conference on Neural Networks · 2011
180
cited
Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation
Transplantation · 2017
134
cited
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors
AAAI Conference on Artificial Intelligence · 2020
131
cited
Security Evaluation of Support Vector Machines in Adversarial Environments
arXiv.org · 2014
127
cited
Misleading Learners: Co-opting Your Spam Filter
2009
124
cited
Query Strategies for Evading Convex-Inducing Classifiers
Journal of machine learning research · 2010
123
cited
Robust and Private Bayesian Inference
International Conference on Algorithmic Learning Theory · 2013
119
cited
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing
International Conference on Machine Learning · 2019
98
cited
Health Data in an Open World
arXiv.org · 2017
92
cited
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning
AAAI Conference on Artificial Intelligence · 2021
90
cited
A Game Theoretical Approach to Defend Against Co-Resident Attacks in Cloud Computing: Preventing Co-Residence Using Semi-Supervised Learning
IEEE Transactions on Information Forensics and Security · 2016
82
cited
Evolving quantum circuits using genetic programming
Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546) · 2001
80
cited
Reinforcement Learning for Autonomous Defence in Software-Defined Networking
Decision and Game Theory for Security · 2018
78
cited
Differential Privacy for Bayesian Inference through Posterior Sampling
Journal of machine learning research · 2017
70
cited
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