By Associate Professor Rohitash Chandra

Conference Presentations

Chandra R; Azam D; Dietmar Müller R, 2019, 'Probabilistic modelling of sedimentary basin evolution using Bayeslands', http://dx.doi.org/10.1080/22020586.2019.12073181

Alac R; Zahirovic S; Salles T; Muller D; Cripps S; Ramos F; Chandra R, 2018, 'Surface Process Models of The Lake Eyre Basin Using Badlands Software', http://dx.doi.org/10.1071/aseg2018abp011

Software / Code

Farahbakhsh E; Hezarkhani A; Eslamkish T; Bahroudi A; Chandra R, 2020, 3DWofE: An open-source software package for three-dimensional weights of evidence modeling[Formula presented], Published: 01 November 2020, Software / Code, http://dx.doi.org/10.1016/j.simpa.2020.100039

Media

Venkataraman V; Chandra R, 2022, Artificial Intelligence meets Bhagavad Gita and the Upanishads, India, https://www.csp.indica.in/artificial-intelligence-meets-bhagavad-gita-and-the-upanishads/

Chandra R; Lande J; Yu C; Kaurav Y, 2022, Global COVID-19 Twitter dataset, Kaggle, http://dx.doi.org/10.34740/kaggle/ds/2397387

Chandra R, 2022, AI, philosophy and religion: what machine learning can tell us about the Bhagavad Gita, https://theconversation.com/ai-philosophy-and-religion-what-machine-learning-can-tell-us-about-the-bhagavad-gita-182517

Chandra R, 2021, Travelling through deep time to find copper for a clean energy future, https://www.stuff.co.nz/environment/climate-news/300357891/travelling-through-deep-time-to-find-copper-for-a-clean-energy-future

Preprints

Chandra R; Choi J; Sonawane J, 2026, Detoxify: A framework for abusive text transformation using LLMs, http://dx.doi.org/10.48550/arxiv.2507.10177

Chandra R; Li J; Dong Y; Zhuang H; Wu D, 2026, Deep learning framework for video-based violence and abuse detection in movies, http://dx.doi.org/10.21203/rs.3.rs-10061173/v1

Selvaraj AK; Panat T; Chandra R, 2026, Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies, http://dx.doi.org/10.48550/arxiv.2502.06866

Liu S; Johnson F; Chandra R, 2026, Remote sensing data imputation using deep learning for multispectral imagery, https://arxiv.org/abs/2605.24003v2

Ibenegbu A; de Micheaux PL; Chandra R, 2026, tBayes-MICE: A Bayesian Approach to Multiple Imputation for Time Series Data, http://dx.doi.org/10.48550/arxiv.2603.27142

Zhang Y; Beard R; Hawkins J; Chandra R, 2026, Automated evaluation of LLMs for effective machine translation of Mandarin Chinese to English, https://arxiv.org/abs/2603.09998v1

Choi J; Chandra R, 2026, Abusive music and song transformation using GenAI and LLMs, http://dx.doi.org/10.48550/arxiv.2601.15348

Chandra R; Chen H; Zhang Y; Chen J; Wu Y, 2026, An evaluation of LLMs for political bias in Western media: Israel-Hamas and Ukraine-Russia wars, https://arxiv.org/abs/2601.06132v1

Chandra R, 2026, <p>How to Write a Scientific Paper: Data Science and AI</p>, http://dx.doi.org/10.2139/ssrn.6493866

Badhe S; Bhat L; Kandaswamy S; Chandra R, 2026, Impact of a Structured Bhagavad Gita Pedagogy Intervention on Dispositional Mindfulness, http://dx.doi.org/10.2139/ssrn.6472118

Kulkarni O; Chandra R, 2025, DynBERG: Dynamic BERT-based Graph neural network for financial fraud detection, https://arxiv.org/abs/2511.00047v1

Forouzandeh S; Krivitsky PN; Chandra R, 2025, A comprehensive survey of modern recommendation systems: methods, personalisation and scalable deployment, http://dx.doi.org/10.36227/techrxiv.176054814.40957359/v1

Hawkins J; Pramar A; Beard R; Chandra R, 2025, Machine Learning for Detection and Analysis of Novel LLM Jailbreaks, http://dx.doi.org/10.48550/arxiv.2510.01644

Chandra R; Suresh Y; Sinha DR; Jindal S, 2025, Language models for longitudinal analysis of abusive content in Billboard Music Charts, http://dx.doi.org/10.48550/arxiv.2510.06266

Kapoor A; Chandra R, 2025, QDeepGR4J: Quantile-based ensemble of deep learning and GR4J hybrid rainfall-runoff models for extreme flow prediction with uncertainty quantification, http://dx.doi.org/10.48550/arxiv.2510.05453

Chandra R; Ren G; Group-H , 2025, Longitudinal Abuse and Sentiment Analysis of Hollywood Movie Dialogues using Language Models, http://dx.doi.org/10.48550/arxiv.2501.13948

Hua J; Ahluwalia R; Chandra R, 2025, Extreme value forecasting using relevance-based data augmentation with deep learning models, https://arxiv.org/abs/2510.02407v1

Gurjar Y; Wan R; Farahbakhsh E; Chandra R, 2025, Landcover classification and change detection using remote sensing and machine learning: a case study of Western Fiji, http://dx.doi.org/10.48550/arxiv.2509.13388

Ma Y; Yu Z; Chandra R, 2025, Deep learning framework for crater detection and identification on the Moon and Mars, http://dx.doi.org/10.48550/arxiv.2508.03920

Chandra R; Chaudhari A; Rayavarapu Y, 2025, An evaluation of LLMs and Google Translate for translation of selected Indian languages via sentiment and semantic analyses, http://dx.doi.org/10.48550/arxiv.2503.21393

Wu J; Chandra R, 2025, Machine learning-based correlation analysis of decadal cyclone intensity with sea surface temperature: data and tutorial, http://dx.doi.org/10.48550/arxiv.2506.09254

Sutar V; Singh A; Chandra R, 2025, Spatiotemporal deep learning models for detection of rapid intensification in cyclones, https://arxiv.org/abs/2506.08397v1

Sands B; Wang Y; Xu C; Zhou Y; Wei L; Chandra R, 2025, An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3, https://arxiv.org/abs/2506.00312v1

Wang R; Wang R; Shen Y; Wu C; Zhou Q; Chandra R, 2025, Evaluation of LLMs for mathematical problem solving, https://arxiv.org/abs/2506.00309v3

Chandra R; Zhu B; Fang Q; Shinjikashvili E, 2025, Large language models for newspaper sentiment analysis during COVID-19: The Guardian, http://dx.doi.org/10.48550/arxiv.2405.13056

Forouzandeh S; Krivitsky PN; Chandra R, 2025, Multiview graph dual-attention deep learning and contrastive learning for multi-criteria recommender systems, http://dx.doi.org/10.48550/arxiv.2502.19271

Farahbakhsh E; Goel D; Pimparkar D; Muller RD; Chandra R, 2025, Convolutional neural networks for mineral prospecting through alteration mapping with remote sensing data, http://dx.doi.org/10.48550/arxiv.2502.18533

Ibenegbu A; Schaeffer A; de Micheaux PL; Chandra R, 2025, A Machine Learning Framework for Handling Unreliable Absence Label and Class Imbalance for Marine Stinger Beaching Prediction, http://dx.doi.org/10.48550/arxiv.2501.11293

Deo R; Sisson S; Webster JM; Chandra R, 2025, Compact Bayesian Neural Networks via pruned MCMC sampling, http://dx.doi.org/10.48550/arxiv.2501.06962

Singh A; Chandra R, 2025, HP-BERT: A framework for longitudinal study of Hinduphobia on social media via language models, https://arxiv.org/abs/2501.05482v2

Tavakoli M; Chandra R; Tian F; Bravo C, 2024, Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams, http://dx.doi.org/10.48550/arxiv.2304.10740

Cheung J; Rangarajan S; Maddocks A; Chen X; Chandra R, 2024, Quantile deep learning models for multi-step ahead time series prediction, http://dx.doi.org/10.48550/arxiv.2411.15674

Wang T; Beard R; Hawkins J; Chandra R, 2024, Recursive deep learning framework for forecasting the decadal world economic outlook, http://dx.doi.org/10.48550/arxiv.2301.10874

Kulkarni O; Chandra R, 2024, Bayes-CATSI: A variational Bayesian deep learning framework for medical time series data imputation, https://arxiv.org/abs/2410.01847v2

Nagar S; Farahbakhsh E; Awange J; Chandra R, 2024, Remote sensing framework for geological mapping via stacked autoencoders and clustering, http://dx.doi.org/10.48550/arxiv.2404.02180

Wang X; Beard R; Chandra R, 2024, Evaluation of Google Translate for Mandarin Chinese translation using sentiment and semantic analysis, http://dx.doi.org/10.48550/arxiv.2409.04964

Wang C; Chandra R, 2024, A longitudinal sentiment analysis of Sinophobia during COVID-19 using large language models, https://arxiv.org/abs/2408.16942v1

Chandra R; Simmons J, 2024, Bayesian neural networks via MCMC: a Python-based tutorial, http://dx.doi.org/10.48550/arxiv.2304.02595

Chandra R; Kapoor A; Khedkar S; Ng J; Vervoort RW, 2024, Ensemble quantile-based deep learning framework for streamflow and flood prediction in Australian catchments, https://arxiv.org/abs/2407.15882v2

Wu J; Zhang X; Huang F; Zhou H; Chandra R, 2024, Review of deep learning models for crypto price prediction: implementation and evaluation, https://arxiv.org/abs/2405.11431v2

Vora M; Blau T; Kachhwal V; Solo AMG; Chandra R, 2024, Large language model for Bible sentiment analysis: Sermon on the Mount, http://dx.doi.org/10.48550/arxiv.2401.00689

Haggerty H; Chandra R, 2024, Self-supervised learning for skin cancer diagnosis with limited training data, https://arxiv.org/abs/2401.00692v3

Chandra R, 2024, Science and Hinduism Share the Vision of a Quest for Truth, http://dx.doi.org/10.2139/ssrn.4685559

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