Tejas Shah

708 total citations
34 papers, 470 citations indexed

About

Tejas Shah is a scholar working on Biomaterials, Organic Chemistry and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Tejas Shah has authored 34 papers receiving a total of 470 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Biomaterials, 8 papers in Organic Chemistry and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Tejas Shah's work include Advanced Polymer Synthesis and Characterization (7 papers), Nanoparticle-Based Drug Delivery (6 papers) and biodegradable polymer synthesis and properties (5 papers). Tejas Shah is often cited by papers focused on Advanced Polymer Synthesis and Characterization (7 papers), Nanoparticle-Based Drug Delivery (6 papers) and biodegradable polymer synthesis and properties (5 papers). Tejas Shah collaborates with scholars based in United States, India and Australia. Tejas Shah's co-authors include Dilip V. Vasava, Chris A. Flask, Guanshu Liu, Mark D. Pagel, Mihaela C. Stefan, Michael C. Biewer, Nicolas Salem, Frank O’Mahony, Wilfred Gomes and Jeffrey L. Duerk and has published in prestigious journals such as Accounts of Chemical Research, Blood and The Journal of Physical Chemistry B.

In The Last Decade

Tejas Shah

29 papers receiving 455 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tejas Shah United States 10 139 101 98 85 51 34 470
Byeong-Il Lee South Korea 12 79 0.6× 106 1.0× 52 0.5× 270 3.2× 85 1.7× 76 525
Katarzyna Kaczmarek Poland 14 114 0.8× 101 1.0× 80 0.8× 275 3.2× 41 0.8× 26 412
Xiangqian Hong China 10 105 0.8× 96 1.0× 80 0.8× 276 3.2× 117 2.3× 18 569
Xiangji Chen China 17 207 1.5× 112 1.1× 163 1.7× 158 1.9× 174 3.4× 39 828
Ying Pan China 14 88 0.6× 72 0.7× 23 0.2× 103 1.2× 87 1.7× 26 684
Yue Qian China 19 179 1.3× 321 3.2× 65 0.7× 228 2.7× 203 4.0× 57 879
Jin Hou China 14 77 0.6× 154 1.5× 183 1.9× 186 2.2× 51 1.0× 26 597
Eleni Alexandratou Greece 12 70 0.5× 115 1.1× 148 1.5× 212 2.5× 89 1.7× 41 634

Countries citing papers authored by Tejas Shah

Since Specialization
Citations

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

Fields of papers citing papers by Tejas Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tejas Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Tejas Shah. A scholar is included among the top collaborators of Tejas Shah 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 Tejas Shah. Tejas Shah 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.
Shah, Tejas, et al.. (2025). Computational design to experimental validation: molecular dynamics-assisted development of polycaprolactone micelles for drug delivery. Journal of Materials Chemistry B. 13(13). 4166–4178. 4 indexed citations
2.
Shah, Tejas, et al.. (2025). Fluorescent Poly(ε-Caprolactone)s Micelles for Anticancer Drug Delivery and Bioimaging. Biomacromolecules. 26(6). 3651–3665. 2 indexed citations
3.
Shah, Tejas, et al.. (2024). Numerical Solution of Differential Equations. SSRN Electronic Journal.
4.
Wang, Hanghang, et al.. (2024). Effect of aromatic substituents on thermoresponsive functional polycaprolactone micellar carriers for doxorubicin delivery. Frontiers in Pharmacology. 15. 1356639–1356639. 8 indexed citations
5.
Abbas, Muhammad, et al.. (2024). Synthesis and characterization of holmium based metal–organic frameworks. CrystEngComm. 26(39). 5567–5573. 2 indexed citations
6.
Shah, Tejas, Mihaela C. Stefan, & Hedieh Torabifard. (2024). Dynamics of Amphiphilic Poly(ε-Caprolactone) Micelles with Doxorubicin and Transition Temperature Predictions Using All-Atom Molecular Dynamics Simulation. The Journal of Physical Chemistry B. 128(48). 11981–11991. 2 indexed citations
7.
Shah, Tejas, et al.. (2023). The correlation of screen time with sleep quality: A cross-sectional study on undergraduate medical students. National Journal of Physiology Pharmacy and Pharmacology. 1–1. 4 indexed citations
8.
Shah, Tejas, et al.. (2023). Comparison of 2D- and 3D-generated Radiomics feature maps in glioblastoma tissue subtypes segmented from DCE perfusion MRI. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition.
9.
Shah, Tejas, et al.. (2023). Recent Advances in Polycaprolactones for Anticancer Drug Delivery. Pharmaceutics. 15(7). 1977–1977. 53 indexed citations
10.
Jaggi, Shalini, et al.. (2023). Expert Opinion by Clinicians on the Use of Insulin Therapy in People with Hepatic Impairment. Journal of the Association of Physicians of India. 71(2). 78–85. 1 indexed citations
11.
Gomes, Wilfred, D. Ingerly, Tejas Shah, et al.. (2022). Ponte Vecchio: A Multi-Tile 3D Stacked Processor for Exascale Computing. 2022 IEEE International Solid- State Circuits Conference (ISSCC). 42–44. 59 indexed citations
12.
Chawla, Manoj, Tejas Shah, Jothydev Kesavadev, et al.. (2022). Sodium-glucose Cotransporter-2 Inhibitors in Primary and Secondary Prevention of Cardiovascular and Renal Outcomes in Patients with Type 2 Diabetes Mellitus: A Meta-analysis. Journal of the Association of Physicians of India. 70(8). 42–50.
13.
Shah, Tejas, et al.. (2022). Successful Use of Subcutaneous Stimulation for Bilateral Sacroiliac Joint Pain. Cureus. 14(11). e31495–e31495.
14.
Shah, Tejas, et al.. (2022). Successful Dorsal Root Ganglion Stimulation for Chronic Pancreatitis: A Case Report. Cureus. 14(11). e31852–e31852. 3 indexed citations
15.
16.
Gupta, Rakesh K., Marc Van Cauteren, Tejas Shah, et al.. (2020). Evaluating feasibility of high resolution T1-perfusion MRI with whole brain coverage using compressed SENSE: Application to glioma grading. European Journal of Radiology. 129. 109049–109049. 14 indexed citations
17.
Pavan‐Kumar, Annam, Prakash Koringa, Namrata Patel, et al.. (2016). Complete mitochondrial genome of threatened mahseer Tor tor (Hamilton 1822) and its phylogenetic relationship within Cyprinidae family. Journal of Genetics. 95(4). 853–863. 9 indexed citations
18.
Reddy, Bhaskar, Tejas Shah, Anand Patel, et al.. (2015). Identification of putative SNPs in progressive retinal atrophy affected Canis lupus familiaris using exome sequencing. Mammalian Genome. 26(11-12). 638–649. 3 indexed citations
19.
Shah, Tejas, et al.. (2014). A Review of Requirement Engineering Issues and Challenges in Various Software Development Methods. International Journal of Computer Applications. 99(15). 36–45. 32 indexed citations
20.
Sandhu, Gurpreet S., Luis Solorio, Ann‐Marie Broome, et al.. (2009). Whole animal imaging. WIREs Systems Biology and Medicine. 2(4). 398–421. 26 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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