Rohitash Chandra
Associate Professor
Sydney, New South Wales, Australia
Summary
👤
Senior🎓
Top SchoolRohitash Chandra is an AI scientist and Associate Professor at UNSW with 11 years of experience bridging academic research and applied machine learning. His work spans Bayesian deep learning, ensemble methods, LLMs and uncertainty quantification, applied across domains from social media and religion to climate science, marine reefs and mineral exploration. He has led interdisciplinary projects and labs (Transitional AI Research Group) and held visiting and research roles internationally, including Cornell and NTU, reflecting a strong global research network. Rohitash combines teaching of advanced data science courses with leadership roles in non-profits (Software Foundation Fiji, Pingla Institute) that promote FOSS and tech for social good. Notably, his research programs emphasize robust decision-making under uncertainty, marrying neural methods with Bayesian inference for real-world environmental and geoscience problems. He maintains an active research presence online (rohitash-chandra.github.io) and a track record of translating AI methods into cross-disciplinary impact.
12 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD Artificial Intelligence, Doctor of Philosophy - PhD Artificial Intelligence at Victoria University of WellingtonMaster of Science Artificial Intelligence, Master of Science Artificial Intelligence at University of Fiji
Hindi, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (39)
mcmc10
bayesian10
autoencoder9
data-mining9
julia8
feedforward8
machine-learning8
parallel8
neural-network8
generative-adversarial-network7
python7
recurrent-neural-networks6
fundamentals6
data-augmentation5
deep-learning5
Programming languages (6)
Github contributions (5)
rohitash-chandra/CooperativeCoevolution
Aug 2014 - Dec 2016
Contributions:4 commits, 1 push in 2 years 4 months
EarthByte/paleoclimate-reconstruction
May 2018 - Dec 2020
Paleo-Climate Precipitation Reconstruction using Bayesian Machine Learning
Contributions:53 commits, 50 pushes, 1 branch in 2 years 7 months
bayesianmachine-learning
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