Dhiman Ray

796 total citations
32 papers, 517 citations indexed

About

Dhiman Ray is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics and Organic Chemistry. According to data from OpenAlex, Dhiman Ray has authored 32 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 10 papers in Atomic and Molecular Physics, and Optics and 9 papers in Organic Chemistry. Recurrent topics in Dhiman Ray's work include Protein Structure and Dynamics (12 papers), Surfactants and Colloidal Systems (9 papers) and Spectroscopy and Quantum Chemical Studies (8 papers). Dhiman Ray is often cited by papers focused on Protein Structure and Dynamics (12 papers), Surfactants and Colloidal Systems (9 papers) and Spectroscopy and Quantum Chemical Studies (8 papers). Dhiman Ray collaborates with scholars based in India, United States and Italy. Dhiman Ray's co-authors include Michele Parrinello, Ioan Andricioaei, Bijan Das, Ranjit De, Ly Le, Ashwani K. Tiwari, Valerio Rizzi, Narjes Ansari, Michele Invernizzi and Sourav Das and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Chemical Physics and The Journal of Physical Chemistry B.

In The Last Decade

Dhiman Ray

32 papers receiving 511 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dhiman Ray India 14 214 127 118 85 68 32 517
Zackary Falls United States 12 124 0.6× 152 1.2× 58 0.5× 46 0.5× 18 0.3× 28 488
Myungshim Kang United States 15 356 1.7× 171 1.3× 105 0.9× 178 2.1× 35 0.5× 28 689
Van‐Quan Vuong United States 12 178 0.8× 186 1.5× 33 0.3× 123 1.4× 28 0.4× 23 503
Tarak Karmakar India 14 113 0.5× 219 1.7× 143 1.2× 59 0.7× 19 0.3× 62 479
William Harbutt Dawson Japan 16 100 0.5× 181 1.4× 64 0.5× 155 1.8× 17 0.3× 48 576
Johnny C. Wu United States 8 316 1.5× 155 1.2× 46 0.4× 217 2.6× 14 0.2× 8 605
Sukanta Mondal India 17 457 2.1× 226 1.8× 206 1.7× 158 1.9× 41 0.6× 60 1.1k
Maximilian Scheurer Germany 11 190 0.9× 137 1.1× 63 0.5× 200 2.4× 10 0.1× 25 526
Robert E. Duke United States 13 336 1.6× 142 1.1× 29 0.2× 162 1.9× 18 0.3× 17 593
Catalina Soriano‐Correa Mexico 12 116 0.5× 117 0.9× 177 1.5× 104 1.2× 9 0.1× 42 544

Countries citing papers authored by Dhiman Ray

Since Specialization
Citations

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

Fields of papers citing papers by Dhiman Ray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dhiman Ray

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

All Works

20 of 20 papers shown
1.
Ray, Dhiman, et al.. (2025). Acceleration with Interpretability: A Surrogate Model-Based Collective Variable for Enhanced Sampling. Journal of Chemical Theory and Computation. 21(4). 1561–1571. 5 indexed citations
2.
Ray, Dhiman, et al.. (2024). Kinetic View of Enzyme Catalysis from Enhanced Sampling QM/MM Simulations. Journal of Chemical Information and Modeling. 64(9). 3953–3958. 10 indexed citations
3.
Ray, Dhiman, et al.. (2024). A Stochastic Landscape Approach for Protein Folding State Classification. Journal of Chemical Theory and Computation. 20(13). 5428–5438. 6 indexed citations
4.
Ray, Dhiman & Valerio Rizzi. (2024). Enhanced Sampling with Suboptimal Collective Variables: Reconciling Accuracy and Convergence Speed. Journal of Chemical Theory and Computation. 21(1). 58–69. 2 indexed citations
5.
Ray, Dhiman & Michele Parrinello. (2024). Data-driven classification of ligand unbinding pathways. Proceedings of the National Academy of Sciences. 121(10). e2313542121–e2313542121. 8 indexed citations
6.
Ray, Dhiman, et al.. (2024). Molecular Insights into the Conformational and Binding Behaviors of Human Serum Albumin Induced by Surface-Active Ionic Liquids. The Journal of Physical Chemistry B. 128(27). 6622–6637. 2 indexed citations
7.
Ray, Dhiman, et al.. (2023). Deep learning collective variables from transition path ensemble. The Journal of Chemical Physics. 158(20). 32 indexed citations
8.
Ray, Dhiman & Michele Parrinello. (2023). Kinetics from Metadynamics: Principles, Applications, and Outlook. Journal of Chemical Theory and Computation. 19(17). 5649–5670. 55 indexed citations
9.
Ray, Dhiman, et al.. (2022). Force-Field-Dependent DNA Breathing Dynamics: A Case Study of Hoogsteen Base Pairing in A6-DNA. Journal of Chemical Information and Modeling. 62(24). 6749–6761. 5 indexed citations
10.
Ray, Dhiman, Narjes Ansari, Valerio Rizzi, Michele Invernizzi, & Michele Parrinello. (2022). Rare Event Kinetics from Adaptive Bias Enhanced Sampling. Journal of Chemical Theory and Computation. 18(11). 6500–6509. 44 indexed citations
11.
Ray, Dhiman, et al.. (2022). Point mutations in SARS-CoV-2 variants induce long-range dynamical perturbations in neutralizing antibodies. Chemical Science. 13(24). 7224–7239. 10 indexed citations
12.
Ray, Dhiman, Ly Le, & Ioan Andricioaei. (2021). Distant residues modulate conformational opening in SARS-CoV-2 spike protein. Proceedings of the National Academy of Sciences. 118(43). 63 indexed citations
13.
Ray, Dhiman & Ioan Andricioaei. (2020). Free Energy Landscape and Conformational Kinetics of Hoogsteen Base Pairing in DNA vs. RNA. Biophysical Journal. 119(8). 1568–1579. 14 indexed citations
14.
Ray, Dhiman, et al.. (2020). Interfacial water and ion distribution determine ζ potential and binding affinity of nanoparticles to biomolecules. Nanoscale. 12(35). 18106–18123. 15 indexed citations
15.
Ray, Dhiman, et al.. (2019). Effects of alloying on mode-selectivity in H2O dissociation on Cu/Ni bimetallic surfaces. The Journal of Chemical Physics. 150(11). 114702–114702. 21 indexed citations
16.
Ray, Dhiman, et al.. (2018). Controlling Heterogeneous Catalysis of Water Dissociation Using Cu–Ni Bimetallic Alloy Surfaces: A Quantum Dynamics Study. The Journal of Physical Chemistry A. 122(26). 5698–5709. 23 indexed citations
17.
Mondal, Satyajit, Dhiman Ray, & Bijan Das. (2017). Thermodynamics of aggregation of imidazolium-based surface active ionic liquids in aqueous poly(ethylene oxide) media. The Journal of Chemical Thermodynamics. 116. 61–66. 10 indexed citations
18.
Ray, Dhiman, Ranjit De, & Bijan Das. (2016). Thermodynamic, transport and frictional properties in semidilute aqueous sodium carboxymethylcellulose solution. The Journal of Chemical Thermodynamics. 101. 227–235. 14 indexed citations
19.
Ray, Dhiman, Sourav Das, Ranjit De, & Bijan Das. (2015). Sodium carboxymethylcellulose-induced aggregation of 1-decyl-3-methylimidazolium chloride in aqueous solutions. Carbohydrate Polymers. 125. 255–264. 26 indexed citations
20.
Das, Bijan, Dhiman Ray, & Ranjit De. (2014). Influence of sodium carboxymethylcellulose on the aggregation behavior of aqueous 1-hexadecyl-3-methylimidazolium chloride solutions. Carbohydrate Polymers. 113. 208–216. 34 indexed citations

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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