Diana Benavides Prado

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Research Fellow

Phone: +64 9 921 9999 – ext: 5097

Email: diana.benavides.prado@aut.ac.nz

Qualifications:

  • 2019 - PhD in Computer Science, The University of Auckland, New Zealand (October)
  • 2012 – Master of Engineering in Systems Engineering and Computing Sciences, Universidad de Los Andes, Colombia
  • 2010 – Bachelor of Engineering in Systems Engineering, Fundacion Universitaria San Martin, Colombia

Memberships and Affiliations:

Biography:

Diana completed her Bachelor of Systems Engineering in 2010, and Master’s in Systems Engineering and Computing Sciences in 2012, both in her native country, Colombia. From 2010 to 2016 she worked as a researcher in science and technology for a variety of Colombian government institutions in sectors such as finance, healthcare, justice and geosciences. Diana moved to New Zealand in 2016. Since then she has been working as a Research Fellow in Data Science for the Centre of Social Data Analytics, AUT. Her experience spans a variety of projects in data science and related areas, as well as teaching and tutoring in algorithms, programming and machine learning. Her research areas are transfer learning, lifelong learning, continual learning and human-algorithm interaction. She holds a PhD in Computer Science from the School of Computer Science at The University of Auckland, New Zealand.

Teaching Areas:

  • Artificial Intelligence
  • Computer Science Fundamentals
  • Data Mining and Machine Learning
  • IT in Organisations
  • Algorithms and Object-Oriented Programming
  • Transactional Systems and Databases

Research Areas:

  • Machine Learning Fundamentals, Transfer Learning, Lifelong Learning, Continual Learning, Classification Techniques, SVM
  • Data Science Applications

Research Summary:

Diana’s research interests span transfer learning, lifelong machine learning, continual learning and human-algorithm interaction. She is recently interested in the study of machine learning algorithms for supporting sequential and long-term  fairness in societal problems.

Current Research Projects:

  • A Framework for Long-Term Learning Systems, The University Auckland, New Zealand
  • Allegheny Family Screening Tool, Centre for Social Data Analytics, AUT
  • Decision Support Aid Tool for Douglas County, Centre for Social Data Analytics, AUT
  • Homelessness Predictive Model for Allegheny County, Centre for Social Data Analytics, AUT
  • Long-Term Fairness in Machine Learning, Centre for Social Data Analytics, AUT

Publications:

  1. Benavides-Prado, D. (2019). A Framework for Long-term Learning Systems. PhD Thesis. To appear in The University of Auckland Theses at https://researchspace.auckland.ac.nz/.
  2. Benavides-Prado, D., Koh, Y. S., & Riddle, P. (2019). Towards Knowledgeable Supervised Lifelong Learning Systems. To appear in Journal of Artificial Intelligence Research (JAIR) at https://www.jair.org/index.php/jair/search/search.
  3. Benavides-Prado, D. (2019). An SVM-Based Framework for Long-Term Learning Systems. In Proceedings of the AAAI Conference on Artificial Intelligence, 33, pp. 9915 – 9916.
  4. Benavides-Prado, D., Koh, Y. S., & Riddle, P. (2019). HRSVM: Selective Hypothesis Refinement with Retention using SVM. In review.
  5. Benavides-Prado, D., Koh, Y. S., & Riddle, P. Selective Hypothesis Transfer for Lifelong Learning (2019). To appear in IJCNN 2019 Conference Proceedings.
  6. Benavides-Prado, D., Koh, Y. S., & Riddle, P. (2018). Measuring Cumulative Gain of Knowledgeable Lifelong Learners. In NeurIPS Workshop on Continual Learning.
  7. Chouldechova, A., Benavides-Prado, D., Fialko, O. & Vaithianathan, R. (2018). A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. In Conference on Fairness, Accountability and Transparency, pp. 134-148.
  8. Benavides-Prado, D., Koh, Y. S. & Riddle, P. (2017). AccGenSVM: Selectively Transferring from Previous Hypotheses. In IJCAI Proceedings, pp. 1440-1446.Benavides-Prado, D. (2017). A Framework for Long-Term Learning Systems. In IJCAI Proceedings, pp. 5167-5168.
  9. Marin, O.C., Castro, I.F.C., Fajardo, F.R., Cifuentes, O.J.A., Prado, D.K.B. & Diaz, M.R. (2016). Impacto del proyecto Arquitectura Empresarial en la gestion de informacion geocientifica en el Servicio Geologico Colombiano: caso de estudio. In Universidad de Los Andes, Centro CIFI-Informatica.Prado, D.B. (2015). MOGACAR: A Method for Filtering Interesting Classification Association Rules. In MLDM Conference Proceedings, pp. 172-183.
  10. Prado, D.K.B. and Villamil-Giraldo, M.P. (2013). KDBuss Framework: Knowledge Discovery with Association Rules in the Business Context. In MLDM Poster Proceedings, pp. 59-72.
  11. Prado, D.K.B. (2012). KDBuss Framework: Knowledge Discovery with Association Rules in the Business Context. Masters dissertation, Universidad de Los Andes.
  12. Prado, D.K.B. (2010). Descriptive and predictive modelling of customer behaviour for Sarmiento Montes Ltda. Undergraduate dissertation, Fundacion Universitaria San Martin.

Awards:

  • 2019 – Computer Science Graduate Student Travel (CSGST) Award, The University of Auckland
  • 2018 – Best Technical and Interdisciplinary Paper, Conference on Fairness, Accountability and Transparency – FAT*
  • 2017 – Computer Science Paper Award, The University of Auckland
  • 2017 – Computer Science Graduate Student Travel (CSGST) Award, The University of Auckland
  • 2017 – Colfuturo Scholarship for Postgraduate Studies
  • 2010 – Best Bachelor of Engineering in Systems Engineering, Fundacion Universitaria San Martin (2010)
  • Best Student of Engineering in Systems Engineering, Fundacion Universitaria San Martin (2006, 2007, 2008, 2009)