Shalmali Joshi

1.7k total citations
18 papers, 428 citations indexed

About

Shalmali Joshi is a scholar working on Health Informatics, Artificial Intelligence and General Health Professions. According to data from OpenAlex, Shalmali Joshi has authored 18 papers receiving a total of 428 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Health Informatics, 8 papers in Artificial Intelligence and 7 papers in General Health Professions. Recurrent topics in Shalmali Joshi's work include Artificial Intelligence in Healthcare and Education (10 papers), Machine Learning in Healthcare (6 papers) and Healthcare cost, quality, practices (6 papers). Shalmali Joshi is often cited by papers focused on Artificial Intelligence in Healthcare and Education (10 papers), Machine Learning in Healthcare (6 papers) and Healthcare cost, quality, practices (6 papers). Shalmali Joshi collaborates with scholars based in Canada, United States and Australia. Shalmali Joshi's co-authors include Mjaye Mazwi, Melissa D. McCradden, James A. Anderson, Marzyeh Ghassemi, Irene Y. Chen, Anna Goldenberg, Randi Zlotnik Shaul, Natalie Dullerud, Danny Eytan and Sana Tonekaboni and has published in prestigious journals such as Nature Medicine, Machine Learning and Journal of the American Medical Informatics Association.

In The Last Decade

Shalmali Joshi

17 papers receiving 419 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Shalmali Joshi Canada	9	196	157	83	73	60	18	428
Piyush Mathur United States	8	254 1.3×	129 0.8×	78 0.9×	77 1.1×	60 1.0×	32	533
Stephanie Teeple United States	5	228 1.2×	135 0.9×	108 1.3×	81 1.1×	62 1.0×	9	524
Liam G. McCoy United States	10	256 1.3×	142 0.9×	107 1.3×	81 1.1×	45 0.8×	25	464
David Lyell Australia	8	196 1.0×	108 0.7×	63 0.8×	63 0.9×	39 0.7×	21	444
Dana Moukheiber United States	8	174 0.9×	138 0.9×	94 1.1×	47 0.6×	31 0.5×	15	432
Jenny Krutzinna Norway	8	125 0.6×	126 0.8×	59 0.7×	60 0.8×	33 0.6×	22	461
Lama Moukheiber United States	8	288 1.5×	139 0.9×	125 1.5×	102 1.4×	62 1.0×	12	599
Fred Hersch Australia	10	132 0.7×	143 0.9×	158 1.9×	81 1.1×	108 1.8×	16	562
Suyog Shetty India	2	283 1.4×	116 0.7×	121 1.5×	74 1.0×	36 0.6×	6	482
Michaela Hardt United States	4	270 1.4×	253 1.6×	103 1.2×	95 1.3×	103 1.7×	5	659

Countries citing papers authored by Shalmali Joshi

Since Specialization

Citations

This map shows the geographic impact of Shalmali Joshi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shalmali Joshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shalmali Joshi more than expected).

Fields of papers citing papers by Shalmali Joshi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shalmali Joshi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shalmali Joshi. The network helps show where Shalmali Joshi may publish in the future.

Co-authorship network of co-authors of Shalmali Joshi

This figure shows the co-authorship network connecting the top 25 collaborators of Shalmali Joshi. A scholar is included among the top collaborators of Shalmali Joshi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shalmali Joshi. Shalmali Joshi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

McCradden, Melissa D., et al.. (2025). What makes a ‘good’ decision with artificial intelligence? A grounded theory study in paediatric care. BMJ evidence-based medicine. 30(3). 183–193. 1 indexed citations

Joshi, Shalmali, Junzhe Zhang, & Elias Bareinboim. (2024). Towards Safe Policy Learning under Partial Identifiability: A Causal Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 38(12). 13004–13012. 1 indexed citations

McCradden, Melissa D., Shalmali Joshi, Kagiso Ndlovu, et al.. (2023). What's fair is… fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning. 1505–1519. 11 indexed citations

McCradden, Melissa D., Shalmali Joshi, James A. Anderson, & Alex John London. (2023). A normative framework for artificial intelligence as a sociotechnical system in healthcare. Patterns. 4(11). 100864–100864. 8 indexed citations

Joshi, Shalmali, et al.. (2023). Making machine learning matter to clinicians: model actionability in medical decision-making. npj Digital Medicine. 6(1). 7–7. 30 indexed citations

Zhang, Haoran, Natalie Dullerud, Laleh Seyyed-Kalantari, et al.. (2021). An empirical framework for domain generalization in clinical settings. 279–290. 20 indexed citations

Dullerud, Natalie, et al.. (2021). Can You Fake It Until You Make It?. 149–160. 23 indexed citations

Chen, Irene Y., Emma Pierson, Sherri Rose, et al.. (2020). Ethical Machine Learning in Health. arXiv (Cornell University). 5 indexed citations

Tonekaboni, Sana, Shalmali Joshi, Kieran R. Campbell, David Duvenaud, & Anna Goldenberg. (2020). What went wrong and when? Instance-wise feature importance for time-series black-box models. Neural Information Processing Systems. 33. 799–809. 14 indexed citations

10.

McCradden, Melissa D., Shalmali Joshi, Mjaye Mazwi, & James A. Anderson. (2020). Ethical limitations of algorithmic fairness solutions in health care machine learning. The Lancet Digital Health. 2(5). e221–e223. 137 indexed citations

11.

Chen, Irene Y., Shalmali Joshi, & Marzyeh Ghassemi. (2020). Treating health disparities with artificial intelligence. Nature Medicine. 26(1). 16–17. 90 indexed citations

12.

McCradden, Melissa D., Mjaye Mazwi, Shalmali Joshi, & James A. Anderson. (2020). When Your Only Tool Is A Hammer. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 109–109. 8 indexed citations

13.

McCradden, Melissa D., Shalmali Joshi, James A. Anderson, et al.. (2020). Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. Journal of the American Medical Informatics Association. 27(12). 2024–2027. 65 indexed citations

14.

Tonekaboni, Sana, Shalmali Joshi, Melissa D. McCradden, & Anna Goldenberg. (2019). What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.. 359–380. 9 indexed citations

15.

Tonekaboni, Sana, Shalmali Joshi, David Duvenaud, & Anna Goldenberg. (2019). Explaining Time Series by Counterfactuals. 3 indexed citations

16.

Joshi, Shalmali, Joydeep Ghosh, Mark D. Reid, & Oluwasanmi Koyejo. (2016). Rényi divergence minimization based co-regularized multiview clustering. Machine Learning. 104(2-3). 411–439. 1 indexed citations

17.

Joshi, Shalmali, Suriya Gunasekar, David Sontag, & Joydeep Ghosh. (2016). Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. 17–41. 2 indexed citations

18.

Joshi, Shalmali, Oluwasanmi Koyejo, & Joydeep Ghosh. (2015). Constrained Inference for Multi-View Clustering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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