Service and Leadership

Service Roles:

  • General Co-Chair and Program Committee Chair (Application Track) for Australasian Data Science and Machine Learning Conference - AusDM (2024).

  • Program Committee Member for European Conference on Artificial Intelligence - ECAI (2024).

  • Program Committee Chair (Research Track) for Australasian Data Science and Machine Learning Conference - AusDM (2023).

  • Assistant Deputy Head of School (Research), School of Computer Science, The University of Auckland (2023 - current).

  • Reviewer for Transactions on Machine Learning Research Journal - TMLR (2023 - current).

  • General Board Member of the Artificial Intelligence Researchers Association of New Zealand - AIRA (2023 - current).

  • Special Session Chair for Australasian Data Mining Conference - AusDM (2022).

  • Publicity Chair for IEEE International Conference on Data Mining - ICDM (2021).

  • Senior Program Committee Member for International Joint Conference on Artificial Intelligence - IJCAI Conference (2021).

  • Program Committee Member for International Conference on Machine Learning - ICML Conference (2021 - current).

  • Program Committee Member for European Conference on Machine Learning - ECML/PKDD Conference (2021 - current).

  • Program Committee Member for Neural Information Processing Systems - NeurIPS Conference (2020 - current).

  • Program Committee Member for International Conference on Learning Representations - ICLR Conference (2020 - current).

  • Program Committee Member for International Joint Conference on Artificial Intelligence - IJCAI Conference (2019 - current).

  • Program Committee Member for Australasian Conference on Data Mining AusDM (2018).

  • Program Committee Member for AAAI Conference on Artificial Intelligence(2017 - current).

  • Reviewer for Statistical Analysis and Data Mining Journal (2016).

  • Reporter for Machine Learning and Data Mining - MLDM Conference (2015).

Selected Contributed Talks:

  • School of Mathematical Sciences, University of Southampton (2024). Continual Supervised Learning for Increasingly Intelligent Machine Learning Systems.

  • Australasian Data Science and Machine Learning Conference (2023). Opening Remarks.

  • Conference on Lifelong Learning Agents - CoLLAs (2022). A Theory for Knowledge Transfer in Continual Learning. Onlinfe Conference.

  • Advanced Machine Learning with Deep Neural Networks (2022). Developers Institute, New Zealand.

  • International Conference on Artificial Neural Networks - ICANN (2021). A Generalised Controller Design using Continual Learning. Online Conference/Online Conference.

  • International Joint Conference on Artificial Intelligence - IJCAI Journal Track (2021). Towards Knowledgeable Supervised Lifelong Learning Systems. Online Conference.

  • StrongAI Lab, The University of Auckland (2021). A Max-Margin Continual Learner. Auckland, New Zealand.

  • ICML Workshop on Continual Learning (2020). Beyond Catastrophic Forgetting in Continual Learning: An Attempt with SVM. Online Conference.

  • Big Data World Meeting Bogota (2020). Human-Algorithm Collaboration: Examples and Related Challenges. Online Conference.

  • Institute for Social Sciences Research, University of Queensland (2020). Ethical Data Science for Social Impact - Data Science and Deployment Challenges while Supporting Decision Making in Human Services. Online Workshop.

  • Women in Data Science (WiDS) Auckland (2020). High Stakes Data Science for Social Good: the data scientist’s experience of implementing the Allegheny Family Screening Tool. Auckland, New Zealand.

  • Institute for Social Sciences Research, University of Queensland (2019). Predictive Analytics for Social Good: Essential Elements and Data Science Challenges. Brisbane, Australia.

  • International Joint Conference in Neural Networks - IJCNN (2019). Selective Hypothesis Transfer for Lifelong Learning. Budapest, Hungary.

  • Ministry of Social Development and Family, Chile (2019). Technical Workshop Alerta Ninez. Santiago, Chile.

  • Crime Lab NY (2019). Designing and Deploying Algorithmic Decision Support Tools in Child Welfare. New York, US.

  • Eindhoven University of Technology - TU/e (2019). Algorithmic Fairness: Practical and Long-Term Challenges. Eindhoven, Netherlands.

  • AAAI 2019 Student Abstract Program (2019). An SVM-based Framework for Long-Term Learning Systems. Honolulu, Hawaii.

  • Tenth Citizen Security Week, Interamerican Development Bank (2018). Implementation of a predictive model for supporting decision making in child welfare. Santiago, Chile.

  • Big Data World Meeting (2018). Implementation of a predictive model for supporting decision making in child welfare. Bogota, Colombia.

  • New Jersey Data Science MeetUp (2018). Can an algorithm tell when kids are in danger? Newark, New Jersey, USA.

  • International Joint Conference on Artificial Intelligence - IJCAI (2017). AccGenSVM: Selectively Transferring from Previous Hypotheses. Melbourne, Australia.

  • International Joint Conference on Artificial Intelligence - IJCAI (2017). A Framework for Long-Term Learning Systems. Melbourne, Australia.

  • WOMBAT Conference - Melbourne Data Science Week (2017). Implementation of a predictive model to support child maltreatment hotline screening decisions. Melbourne, Australia.