David Mai

899 total citations · 1 hit paper
15 papers, 549 citations indexed

About

David Mai is a scholar working on Oncology, Biomedical Engineering and Molecular Biology. According to data from OpenAlex, David Mai has authored 15 papers receiving a total of 549 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 8 papers in Biomedical Engineering and 7 papers in Molecular Biology. Recurrent topics in David Mai's work include CAR-T cell therapy research (8 papers), Virus-based gene therapy research (3 papers) and Viral Infectious Diseases and Gene Expression in Insects (3 papers). David Mai is often cited by papers focused on CAR-T cell therapy research (8 papers), Virus-based gene therapy research (3 papers) and Viral Infectious Diseases and Gene Expression in Insects (3 papers). David Mai collaborates with scholars based in United States and Russia. David Mai's co-authors include Neil C. Sheppard, Carl H. June, Michael J. Mitchell, Margaret M. Billingsley, Alex G. Hamilton, Kelsey L. Swingle, Ningqiang Gong, Savan K. Patel, Rebecca M. Haley and Xuexiang Han and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Materials and Nano Letters.

In The Last Decade

David Mai

14 papers receiving 544 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Ionizable Lipid Nanoparticles with Integrated Immune Checkpoint Inhibition for mRNA CAR T Cell Engineering

2023 66 citations Alex G. Hamilton, Kelsey L. Swingle et al. Advanced Healthcare Materials profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Mai United States	8	270	265	198	126	82	15	549
Alvin J. Mukalel United States	12	475 1.8×	142 0.5×	139 0.7×	115 0.9×	94 1.1×	16	664
Feifei Qi China	8	166 0.6×	197 0.7×	333 1.7×	89 0.7×	80 1.0×	8	472
Xiaoyang Zhang China	10	205 0.8×	192 0.7×	401 2.0×	128 1.0×	137 1.7×	22	637
Tanmay Dichwalkar United States	4	155 0.6×	136 0.5×	258 1.3×	198 1.6×	58 0.7×	6	418
Zachary Spencer Dunn United States	13	143 0.5×	136 0.5×	318 1.6×	227 1.8×	54 0.7×	19	495
George C. Hartoularos United States	8	403 1.5×	313 1.2×	103 0.5×	85 0.7×	69 0.8×	12	723
Hannah C. Safford United States	11	355 1.3×	181 0.7×	119 0.6×	109 0.9×	55 0.7×	16	628
Hongliang Fang China	9	191 0.7×	185 0.7×	244 1.2×	219 1.7×	53 0.6×	10	600
Laurens Raes Belgium	10	221 0.8×	188 0.7×	104 0.5×	55 0.4×	57 0.7×	12	379
Llian Mabardi United States	3	221 0.8×	398 1.5×	312 1.6×	336 2.7×	46 0.6×	4	670

Countries citing papers authored by David Mai

Since Specialization

Citations

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

Fields of papers citing papers by David Mai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Mai

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

All Works

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15 of 15 papers shown

Cesaro, Angela, et al.. (2025). Using synthetic biology to understand the gut-brain axis. Cell Reports Physical Science. 6(3). 102458–102458. 2 indexed citations

Mai, David, et al.. (2024). ZFP36 disruption is insufficient to enhance the function of mesothelin-targeting human CAR-T cells. Scientific Reports. 14(1). 3113–3113. 1 indexed citations

Padilla, Marshall S., Ningqiang Gong, Margaret M. Billingsley, et al.. (2024). Antigen Presenting Cell Mimetic Lipid Nanoparticles for Rapid mRNA CAR T Cell Cancer Immunotherapy. Advanced Materials. 36(26). e2313226–e2313226. 48 indexed citations

Mai, David, Carly M. Harro, A. Sanyal, et al.. (2024). Stem Loop Mediated Transgene Modulation in Human T Cells. ACS Synthetic Biology. 13(12). 3897–3907.

Abramyan, Tigran M., Dmitry Gil, Jessica Johnson, et al.. (2024). Resolving the Size and Charge of Small Particles: A Predictive Model of Nanopore Mechanics. The Journal of Physical Chemistry C. 128(41). 17619–17630. 1 indexed citations

Xue, Lulu, Ajay S. Thatte, David Mai, et al.. (2023). Responsive biomaterials: optimizing control of cancer immunotherapy. Nature Reviews Materials. 9(2). 100–118. 109 indexed citations

Hamilton, Alex G., Kelsey L. Swingle, Ryann A. Joseph, et al.. (2023). Ionizable Lipid Nanoparticles with Integrated Immune Checkpoint Inhibition for mRNA CAR T Cell Engineering. Advanced Healthcare Materials. 12(30). e2301515–e2301515. 66 indexed citations breakdown →

Mai, David, Omar Johnson, Ting–Jia Fan, et al.. (2023). Combined disruption of T cell inflammatory regulators Regnase-1 and Roquin-1 enhances antitumor activity of engineered human T cells. Proceedings of the National Academy of Sciences. 120(12). e2218632120–e2218632120. 51 indexed citations

Mai, David, Carl H. June, & Neil C. Sheppard. (2022). In vivo gene immunotherapy for cancer. Science Translational Medicine. 14(670). eabo3603–eabo3603. 23 indexed citations

10.

Diebo, Bassel G., David J. Kim, David Mai, et al.. (2022). 132. Utilizing the Dubousset Functional Test to bridge the gap between functional testing and postural radiographic sagittal alignment. The Spine Journal. 22(9). S69–S70. 2 indexed citations

11.

Chandrasekharan, Prashant, K. L. Barry Fung, Xinyi Zhou, et al.. (2021). Non-radioactive and sensitive tracking of neutrophils towards inflammation using antibody functionalized magnetic particle imaging tracers. Nanotheranostics. 5(2). 240–255. 32 indexed citations

12.

Billingsley, Margaret M., Alex G. Hamilton, David Mai, et al.. (2021). Orthogonal Design of Experiments for Optimization of Lipid Nanoparticles for mRNA Engineering of CAR T Cells. Nano Letters. 22(1). 533–542. 133 indexed citations

13.

Mai, David, Neil C. Sheppard, & Bruce L. Levine. (2021). Advances in engineering and synthetic biology toward improved therapeutic immune cells. Current Opinion in Biomedical Engineering. 20. 100342–100342. 2 indexed citations

14.

Kugelman, David N., et al.. (2020). Urban Cycling Expansion is Associated with an Increased Number of Clavicle Fractures.. PubMed. 78(2). 101–107. 2 indexed citations

15.

Zhou, Xinyi Y., Zhi Wei Tay, Prashant Chandrasekharan, et al.. (2018). Magnetic particle imaging for radiation-free, sensitive and high-contrast vascular imaging and cell tracking. Current Opinion in Chemical Biology. 45. 131–138. 77 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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