Select Publications

Journals

  • Diana Cárdenas, Finnian Lattimore, Daniel Steinberg, and Katherine J Reynolds. Youth well-being predicts later academic success. Scientific reports, 12(1):1–13, 2022. [ PDF ] [ Code ]
  • James S. Camac, Richard Condit, Richard G. FitzJohn, Lachlan McCalman, Daniel Steinberg, Mark Westoby, S Joseph Wright, and Daniel S. Falster. Partitioning mortality into growth-dependent and growth-independent hazards across 203 tropical tree species. Proceedings of the National Academy of Sciences, 115(49):12459–12464, 2018. [ PDF ]
  • N. Butterworth, D. Steinberg, R. D. Müller, S. Williams, A. S. Merdith, and S. Hardy. Tectonic environments of south american porphyry copper magmatism through time revealed by spatiotemporal data mining. Tectonics, 35(12):2847–2862, 2016. [ PDF ]
  • Stefan B. Williams, Oscar Pizarro, Daniel M. Steinberg, Ariell Friedman, and Mitch Bryson. Reflections on a decade of autonomous underwater vehicles operations for marine survey at the australian centre for field robotics. Annual Reviews in Control, 42:158–165, 2016.
  • Daniel M. Steinberg, Oscar Pizarro, and Stefan B. Williams. Hierarchical bayesian models for unsupervised scene understanding. Journal of Computer Vision and Image Understanding (CVIU), 131:128–144, Feb. 2015. [ PDF ] [ Code ]
  • Tom Bridge, Anna Scott, and Daniel M. Steinberg. Abundance and diversity of anemonefishes and their host sea anemones at two mesophotic sites on the great barrier reef, australia. Coral Reefs, 31:1057–1062, 2012. [ PDF ]
  • Jan Seiler, Ariell L. Friedman, Daniel M. Steinberg, Neville Barrett, Alan Williams, and Neil J. Holbrook. Image-based continental shelf habitat mapping using novel automated data extraction techniques. Continental Shelf Research, 45:87–97, 2012. [ PDF ]
  • Stefan B. Williams, O. R. Pizarro, M. V. Jakuba, C. R. Johnson, N. S. Barrett, R. C. Babcock, G. A. Kendrick, P. D. Steinberg, A. J. Heyward, P. J. Doherty, I. Mahon, M. Johnson-Roberson, D. M. Steinberg, and A. Friedman. Monitoring of benthic reference sites: using an autonomous underwater vehicle. Robotics Automation Magazine, IEEE, 19(1):73–84, 2012. [ PDF ]
  • Christopher N. Roman, Gabrielle Inglis, J. Ian Vaughn, Stefan B. Williams, Oscar Pizarro, Ariell L. Friedman, and Daniel M. Steinberg. Development of high-resolution underwater mapping techniques. Oceanography, 24(1):42–45, 2011. [ PDF ]
  • Daniel M. Steinberg, Asher Bender, Friedman, Ariell L, Michael V. Jakuba, Oscar Pizarro, and Stefan B. Williams. Analysis of propulsion methods for long-range auvs. Marine Technology Society Journal, 44(2):46–55, 2010. [ PDF ]

Conference Papers

  • Daniel Steinberg, Alistair Reid, and Simon O'Callaghan. Fairness measures for regression via probabilistic classification. In Ethics of Data Science Conference (EDSC). Sydney, Australia, 2020. [ PDF ]
  • John Wilford, Karol Czarnota, Sudipta Basak, L Lachlan Mccalman, Daniel Steinberg, Niket Chhajed, and Rakib Hassan. Machine-learning-converting geoscience data into predictive geochemical and 3d surface models. In AGU Fall Meeting Abstracts, volume 2018, T31E–0370. 2018. [ PDF ]
  • Edwin V. Bonilla, Daniel M. Steinberg, and Alistair Reid. Extended and unscented random kitchen sinks. In International Conference on Machine Learning (ICML). New York, NY, 2016. [ PDF ] [ Poster ]
  • Daniel M. Steinberg and Edwin V. Bonilla. Extended and unscented gaussian processes. In Advances in Neural Information Processing Systems (NIPS). Montreal, Canada, 2014. Awarded a spotlight presentation. [ PDF ] [ Poster ] [ Code ]
  • Daniel M. Steinberg, Oscar Pizarro, and Stefan B. Williams. Synergistic clustering of image and segment descriptors for unsupervised scene understanding. In International Conference on Computer Vision (ICCV). Darling Harbour, Sydney, 2013. IEEE. [ PDF ] [ Poster ] [ Code ]
  • Ariell L. Friedman, Daniel M. Steinberg, Oscar Pizarro, and Stefan B. Williams. Active learning using a variational dirichlet process model for pre-clustering and classification of underwater stereo imagery. In IEEE/RSJ Intelligent Robots and Systems., 1533–1539. San Francisco, 2011. IEEE. [ PDF ]
  • Michael V. Jakuba, Daniel M. Steinberg, James C. Kinsey, Dana R. Yoerger, and Richard Camilli. Toward automatic classification of chemical sensor data from autonomous underwater vehicles. In IEEE/RSJ Intelligent Robots and Systems., number 1, 4722–4727. San Francisco, 2011. [ PDF ]
  • Daniel M. Steinberg, Ariell L. Friedman, Oscar Pizarro, and Stefan B. Williams. A bayesian nonparametric approach to clustering data from underwater robotic surveys. In International Symposium on Robotics Research. Flagstaff, AZ, 2011. [ PDF ] [ Code ]
  • Daniel M. Steinberg, Oscar Pizarro, Michael V. Jakuba, and Stefan B. Williams. Dirichlet process mixture models for autonomous habitat classification. In Proceedings of OCEANS. Sydney, 2010. IEEE Oceanic Engineering Society. [ PDF ]
  • Daniel M. Steinberg, Stefan B. Williams, Oscar Pizarro, and Michael V. Jakuba. Towards autonomous habitat classification using gaussian mixture models. In Proceedings of Intelligent Robotics and Systems (IROS). Taipei, 2010. IEEE/RSJ. [ PDF ]
  • Daniel M. Steinberg, Asher Bender, and Ariell L. Friedman. Toward selection of a propulsion method for a long range benthic imaging auv. In International Symposium on Unmanned Untethered Submersible Technology (UUST). University of New Hampshire, 2009. [ PDF ]
  • Asher Bender, Daniel M. Steinberg, Ariell L. Friedman, and Stefan B. Williams. Analysis of an autonomous underwater glider. In Australasian Conference on Robotics and Automation (ACRA). Australian National University, Canberra, 2008. [ PDF ]

Chapters

  • Hugh Durrant-Whyte, Lachlan McCalman, Simon O'Callaghan, Alistair Reid, and Daniel Steinberg. The impact of computerisation and automation on future employment. In Australia's Future Workforce?, chapter 1.4. Committee for Economic Development of Australia (CEDA), June 2015. [ PDF ]

Workshops etc.

  • Daniel M. Steinberg, Oscar Pizarro, and Stefan B. Williams. Synergistic clustering of image and segment descriptors for unsupervised scene understanding. Scene Understanding Workshop (SUNw) at CVPR, 2014. (invited submission). [ PDF ] [ Poster ] [ Code ]

PhD Thesis

  • Daniel M. Steinberg. An Unsupervised Approach to Modelling Visual Data. PhD thesis, Australian Centre for Field Robotics, The University of Sydney, 2013. [ PDF ] [ Code ]

Curriculum Vitae