Research Spotlight

Dr. Rohitash Chandra is USyd Research Fellow at the Centre for Translational Data Science and School of Geosciences at the University of Sydney. His research interests are in areas of deep learning, neuro-evolution, Bayesian methods, solid Earth Evolution, reef modelling and mineral exploration. Currently he is developing novel learning algorithms for robust and dynamic decision making given misinformation and uncertainty from the environment. This provides a synergy of deep learning methods with Bayesian inference, and multi-task learning. Furthermore, he is involved in projects that employ machine learning methods and Bayesian inference via parallel tempering for solid Earth evolution, mineral exploration, and reef modelling.

Current Research Projects

Bayesian deep learning for uncertain environments: We develop novel learning algorithms for robust decision making given misinformation and uncertainty from the environment. This provides a synergy of neural networks with modular, multi-task and transfer learning. We employ Bayesian methods to address uncertainty quantification in emerging deep learning methods. Collaborators: Prof. Sally Cripps, Centre for Translational Data Science; Prof. Junbin Gao, USyd Business School.

Solid Earth evolution: The solid Earth evolution project considers Bayesian inference and machine learning for landscape dynamics model (BayesLands). Collaborators: Prof. Dietmar Muller and Dr. Tristan Salles, School of Geosciences; Prof. Sally Cripps, Centre for Translational Data Science.

Reef modelling: We provide uncertainty quantification estimation of free parameters using Bayesian inference for reef modelling (BayesReef). The objectives is to gain insights into the flux of carbon by analysing carbonate platform growth and demise through time, and modelling their evolution using lanscape dynamics and reef modelling Python packages (Badlands and pyRee). Bayesian and machine learning methods will be used in conjunction with landscape and reef models to predict the future evolution of landscape and reef systems around the world and their impact on the carbon cycle.

Collaborators: A/Prof. Jody Webster and Dr. Tristan Salles, School of Geosciences; Prof. Sally Cripps, Centre for Translational Data Science.

Mineral exploration: We provide a synergy of machine learning, geo-physical forward models, and Bayesian inference for the robust location of sites for mineral prospecting and exploration. Collaborators: Prof. Chris Clark, Dr. Hugo Olierook (Curtin University); Prof. Sally Cripps, Centre for Translational Data Science; Prof. Dietmar Muller, School of Geosciences

Paleo-climate: The objective is to develop models that can describe the climate of the past that range for millions of years. Collaborators: Prof. Dietmar Muller, School of Geosciences; Prof. Sally Cripps, Centre for Translational Data Science.

Machine consciousness: Develop computational models of machine consciousness that simulate aspects such as personality, affection, and reasoning.

Open Research Opportunities

Summer of Research Internship Students are given 12 weeks of research allowance to work in a selected field in Statistical machine learning and deep learning. Students will be based at the Centre for Translational Data Science, The University of Sydney. More details here:

Honours Research Projects

  1. “Climate precipitation in geological timeframe”, Co-supervised with Prof. Dietmar Muller, School of Geosciences
  2. “Uncertainty quantification for solid Earth models (Badlands), “ Co-supervised with Prof. Dietmar Muller, School of Geosciences

Ph.D Open Projects

  1. “Dynamic Earth models, landscape dynamics and basin evolution”, Co-supervised with Prof. Dietmar Muller, School of Geosciences More details here:
  2. “Spatio-temporal geodata mining”,Co-supervised with Prof. Dietmar Muller, School of Geosciences More details here:
  3. “Bayesian deep learning for incomplete information, “ Co-supervised with Prof. Sally Cripps, School of Mathematics and Statistics Mode details here:
  4. “Machine learning for Reef Modelling and Optimisation, “ Co-supervised with Prof. Jody Webster, School of Geosciences More information:

Active Research Students

  1. Ehsan Farahbakhsh, “Machine learning methods for mineral prospecting”, Ph.D, Tehran Polytechnic, Tehran (External Supervisor)

  2. Gary Wong, “Novel methods for neuro-evolution”, University of the South Pacific, Suva, Fiji, MSc. Computer Sc. (External Supervisor)

  3. Ratneel Deo, “Bayesian inference and machine learning methods for modelling great barrier reef”, preparing for Ph.D.

Past Research Students and Thesis

  1. Shelvin Chand, “Multi-Objective Cooperative Neuro-Evolution for Chaotic Time Series Prediction”, Master of Science in Computing Science, University of the South Pacific, Suva, Fiji, August 2014 Download thesis from USP Library (Awarded PhD Scholarship at UNSW Australia, 2015)
  2. Shonal Chaudhary, “Mobile Based Face Recognition for Visually Impaired Persons”, Master of Science in Computing Science, University of the South Pacific, Suva, Fiji, August 2015 Download thesis from USP Library
  3. Kavitesh Bali, “Competitive Island Cooperative Coevolution for Real Parameter Global Optimization”, Master of Science in Computing Science, University of the South Pacific, Suva, Fiji, September 2015 Download thesis from USP Library (Awarded PhD Scholarship at Nanyang Technological University - Singapore, 2016) (Awarded Gold Medal for Best MSc Thesis at USP)
  4. Ravneil Nand, “Competitive Island Cooperative Neuro-Evolution for Time Series Prediction”, Master of Science in Computing Science, University of the South Pacific, Suva, Fiji, January 2016 Download thesis from USP Library
  5. Shamina Hussein, “ “, Master of Science in Computing Science, University of the South Pacific, Suva, Fiji, 2015 Download thesis from USP Library (Thesis to be uploaded later)
  6. Swaran Ravindra, “ “,Master of Science in Information Systems, University of the South Pacific, Suva, Fiji, 2015 Download thesis from USP Library (Thesis to be uploaded later)
  7. Ratneel Deo, “ “, Master of Science in Computing Science, University of the South Pacific, Suva, Fiji, December 2017 Download thesis from USP Library (Thesis to be uploaded later)

Open Research Projects

Open Research Projects (Email to check which ones are open for collaboration)

Contact Information

rohitash.chandra (at) sydney.edu.au or c.rohitash (at) gmail.com

University of Sydney: Research Supervisor Connect