Priyam Das

533 total citations
14 papers, 101 citations indexed

About

Priyam Das is a scholar working on Statistics and Probability, Molecular Biology and Ocean Engineering. According to data from OpenAlex, Priyam Das has authored 14 papers receiving a total of 101 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistics and Probability, 3 papers in Molecular Biology and 3 papers in Ocean Engineering. Recurrent topics in Priyam Das's work include Statistical Methods and Inference (5 papers), Water resources management and optimization (3 papers) and Advanced Statistical Methods and Models (3 papers). Priyam Das is often cited by papers focused on Statistical Methods and Inference (5 papers), Water resources management and optimization (3 papers) and Advanced Statistical Methods and Models (3 papers). Priyam Das collaborates with scholars based in United States, India and United Kingdom. Priyam Das's co-authors include Subhashis Ghosal, A. Sankarasubramanian, Seung Beom Seo, Christine B. Peterson, Debraj Das, Bibhas Chakraborty, Michael E. Weinblatt, Derek J. Hausenloy, Kim‐Anh Do and Jonathan S. Coblyn and has published in prestigious journals such as Bioinformatics, Water Resources Research and Biometrics.

In The Last Decade

Priyam Das

10 papers receiving 91 citations

Peers

Countries citing papers authored by Priyam Das

Since Specialization

Citations

This map shows the geographic impact of Priyam Das'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 Priyam Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Priyam Das more than expected).

Fields of papers citing papers by Priyam Das

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Priyam Das. 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 Priyam Das. The network helps show where Priyam Das may publish in the future.

Co-authorship network of co-authors of Priyam Das

This figure shows the co-authorship network connecting the top 25 collaborators of Priyam Das. A scholar is included among the top collaborators of Priyam Das 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 Priyam Das. Priyam Das is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

#	Work	Indexed citations
1	Paclitaxel-induced neuroinflammation after systemic administration in male and female mice 2025 ·Journal of Pain ·Martial Caillaud, (unknown), (unknown), (unknown), Wisam Toma, Michael D. Burton, Nolan A. Wages, Priyam Das, M. Imad Damaj	0
2	PEBBLE: A second order correct bootstrap method in logistic regression 2025 ·Bernoulli ·Debraj Das, Priyam Das	1
3	Clustering Sequence Data with Mixture Markov Chains with Covariates Using Multiple Simplex Constrained Optimization Routine (MSiCOR) 2023 ·Journal of Computational and Graphical Statistics ·Priyam Das, (unknown), (unknown), Jue Hou, (unknown), Nicole Kim, Zongqi Xia, Tianxi Cai	0
4	Utilizing biologic disease-modifying anti-rheumatic treatment sequences to subphenotype rheumatoid arthritis 2023 ·Arthritis Research & Therapy ·Priyam Das, Dana Weisenfeld, (unknown), (unknown), (unknown), Jonathan S. Coblyn, Michael E. Weinblatt, Nancy A. Shadick, Tianxi Cai, Katherine P. Liao	4
5	Bayesian Hierarchical Quantile Regression with Application to Characterizing the Immune Architecture of Lung Cancer 2022 ·Biometrics ·Priyam Das, Christine B. Peterson, Yang Ni, Alexandre Reuben, Jiexin Zhang, Jianjun Zhang, Kim‐Anh Do, Veerabhadran Baladandayuthapani	0
6	Estimating the optimal linear combination of predictors using spherically constrained optimization 2022 ·BMC Bioinformatics ·Priyam Das, (unknown), (unknown), Mona Kamal, Katherine A. Hutcheson, Clifton D. Fuller, Bibhas Chakraborty, Christine B. Peterson	2
7	A distribution-free smoothed combination method to improve discrimination accuracy in multi-category classification 2022 ·Statistical Methods in Medical Research ·(unknown), Jialiang Li, Priyam Das, Xueqing Liu, Lei Feng, Derek J. Hausenloy, Bibhas Chakraborty	1
8	Synthesis of Irrigation Water Use in the United States: Spatiotemporal Patterns 2020 ·Journal of Water Resources Planning and Management ·(unknown), Seung Beom Seo, Priyam Das, A. Sankarasubramanian	9
9	NExUS: Bayesian simultaneous network estimation across unequal sample sizes 2019 ·Bioinformatics ·Priyam Das, Christine B. Peterson, Kim‐Anh Do, Rehan Akbani, Veerabhadran Baladandayuthapani	2
10	Bayesian non-parametric simultaneous quantile regression for complete and grid data 2018 ·Computational Statistics & Data Analysis ·Priyam Das, Subhashis Ghosal	13
11	Modeling the Irrigation Withdrawals Over the Coterminous US Using a Hierarchical Modeling Approach 2018 ·Water Resources Research ·Priyam Das, (unknown), A. Sankarasubramanian	10
12	Black-box optimization on hyper-rectangle using Recursive Modified Pattern Search and application to ROC-based Classification Problem 2016 ·arXiv (Cornell University) ·Priyam Das	0
13	Bayesian quantile regression using random B-spline series prior 2016 ·Computational Statistics & Data Analysis ·Priyam Das, Subhashis Ghosal	13
14	The Ganges and the GAP: An Assessment of Efforts to Clean a Sacred River 2012 ·Sustainability ·Priyam Das, (unknown)	46

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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