Health Informatics in the Classroom: An Empirical Study to Investigate Higher Education's Response to Healthcare Transformation. - Noushin Ashrafi; Jean-Pierre Kuilboer; Chaitanya Joshi; Iris Ran; Priyanka Pande (J. Inf. Syst. Educ., 2014)

Inferring User Actions from Provenance Logs. - Xin Li; Chaitanya Joshi; Alan Yu Shyang Tan; Ryan Kok Leong Ko (TrustCom/BigDataSE/ISPA (1), 2015)

Prior Robustness for Bayesian Implementation of the Fault Tree Analysis. - Chaitanya Joshi; Fabrizio Ruggeri 001; Simon P. Wilson 001 (IEEE Trans. Reliab., 2018)

On approximating the shape of one dimensional functions. - Chaitanya Joshi; Paul T. Brown; Stephen Joe (CoRR, 2019)

Adversarial Risk Analysis for First-Price Sealed-Bid Auctions. - Muhammad Ejaz; Chaitanya Joshi; Stephen Joe (CoRR, 2019)

Insider threat modeling: An adversarial risk analysis approach. - Chaitanya Joshi; David Ríos Insua; Jesus Rios (CoRR, 2019)

Human-in-the-loop AI in government: a case study. - Lanthao Benedikt; Chaitanya Joshi; Louisa Nolan; Ruben Henstra-Hill; Luke Shaw; Sharon Hook (IUI, 2020)

A novel method of marginalisation using low discrepancy sequences for integrated nested Laplace approximations. - Paul T. Brown; Chaitanya Joshi; Stephen Joe; Håvard Rue (Comput. Stat. Data Anal., 2021)

Adversarial Risk Analysis for Auctions Using Mirror Equilibrium and Bayes Nash Equilibrium. - Muhammad Ejaz; Stephen Joe; Chaitanya Joshi (Decis. Anal., 2021)

Considerations for Developing Predictive Spatial Models of Crime and New Methods for Measuring Their Accuracy. - Chaitanya Joshi; Sophie Curtis-Ham; Clayton D'Ath; Deane Searle (ISPRS Int. J. Geo Inf., 2021)

Insider Threat Modeling: An Adversarial Risk Analysis Approach. - Chaitanya Joshi; Jesús M. Ríos Aliaga; David Ríos Insua (IEEE Trans. Inf. Forensics Secur., 2021)

Methods for Eliciting Informative Prior Distributions: A Critical Review. - Julia R. Falconer; Eibe Frank; Devon L. L. Polaschek; Chaitanya Joshi (Decis. Anal., 2022)

Target Detection in Hyperspectral Imagery Using Atmospheric-Spectral Modeling and Deep Learning. - Sudhanshu Shekhar Jha; Chaitanya Joshi; Rama Rao Nidamanuri (IEEE Geosci. Remote. Sens. Lett., 2022)

On a class of prior distributions that accounts for uncertainty in the data. - Chaitanya Joshi; Fabrizio Ruggeri 001 (Int. J. Approx. Reason., 2023)

Eliciting Informative Priors by Modeling Expert Decision Making. - Julia R. Falconer; Eibe Frank; Devon L. L. Polaschek; Chaitanya Joshi (Decis. Anal., 2024)

A 10T SRAM architecture with 40 % enhanced throughput for IMC applications benchmarked with CIFAR-10 dataset. - Ravi S. Siddanath; Mohit Gupta; Chaitanya Joshi; Manish Goswami; Kavindra Kandpal (Integr., 2024)

Spatial distribution of poultry farms using point pattern modelling: A method to address livestock environmental impacts and disease transmission risks. - Marie-Cécile Dupas; Francesco Pinotti; Chaitanya Joshi; Madhvi Joshi; Weerapong Thanapongtharm; Madhur S. Dhingra; Damer Blake; Fiona Tomley; Marius Gilbert; Guillaume Fournié (PLoS Comput. Biol., 2024)

Contrasting the optimal resource allocation to cybersecurity controls and cyber insurance using prospect theory versus expected utility theory. - Chaitanya Joshi; Sergeja Slapnicar; Jinming Yang; Ryan K. L. Ko (Comput. Secur., 2025)

Utilising Deep Learning to Elicit Expert Uncertainty. - Julia R. Falconer; Eibe Frank; Devon L. L. Polaschek; Chaitanya Joshi (CoRR, 2025)

A programmable environment for shape optimization and shapeshifting problems. - Chaitanya Joshi; Daniel Hellstein; Cole Wennerholm; Eoghan Downey; Emmett Hamilton; Samuel Hocking; Anca S. Andrei; James H. Adler; Timothy J. Atherton (Nat. Comput. Sci., 2025)