Michael S. Chen

929 total citations
18 papers, 641 citations indexed

About

Michael S. Chen is a scholar working on Cardiology and Cardiovascular Medicine, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Michael S. Chen has authored 18 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cardiology and Cardiovascular Medicine, 5 papers in Materials Chemistry and 4 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Michael S. Chen's work include Machine Learning in Materials Science (4 papers), Acute Myocardial Infarction Research (4 papers) and Spectroscopy and Quantum Chemical Studies (3 papers). Michael S. Chen is often cited by papers focused on Machine Learning in Materials Science (4 papers), Acute Myocardial Infarction Research (4 papers) and Spectroscopy and Quantum Chemical Studies (3 papers). Michael S. Chen collaborates with scholars based in United States, Australia and United Kingdom. Michael S. Chen's co-authors include Deepak L. Bhatt, Derek P. Chew, Stephen G. Ellis, David S. Lee, Thomas E. Markland, Jeff Wagner, Zhong-Min Wang, Stephen Wall, Sutapa Ghosal and Joonho Lee and has published in prestigious journals such as Nature Communications, The Journal of Chemical Physics and Journal of Applied Physics.

In The Last Decade

Michael S. Chen

16 papers receiving 615 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael S. Chen United States 11 290 242 124 113 95 18 641
A.N. Ansari United States 11 122 0.4× 91 0.4× 536 4.3× 142 1.3× 31 0.3× 20 800
Marie Greene United States 4 63 0.2× 72 0.3× 366 3.0× 81 0.7× 19 0.2× 6 476
H L Atkins United States 6 41 0.1× 68 0.3× 245 2.0× 67 0.6× 20 0.2× 11 349
Tomoki Kawano Japan 10 131 0.5× 114 0.5× 21 0.2× 75 0.7× 52 0.5× 27 405
P.R. Bradley-Moore United States 5 47 0.2× 64 0.3× 297 2.4× 62 0.5× 19 0.2× 6 415
Masako Nishikawa Japan 16 77 0.3× 23 0.1× 14 0.1× 33 0.3× 38 0.4× 41 607
Yi‐Ju Wu Taiwan 14 119 0.4× 6 0.0× 22 0.2× 40 0.4× 24 0.3× 42 568
Dinghui Wang United States 14 16 0.1× 24 0.1× 163 1.3× 22 0.2× 143 1.5× 45 668
Junwei Shen China 13 26 0.1× 59 0.2× 12 0.1× 36 0.3× 52 0.5× 46 472
Michael S. Kovacs Canada 12 64 0.2× 53 0.2× 361 2.9× 166 1.5× 58 0.6× 39 604

Countries citing papers authored by Michael S. Chen

Since Specialization
Citations

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

Fields of papers citing papers by Michael S. Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael S. Chen. 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 Michael S. Chen. The network helps show where Michael S. Chen may publish in the future.

Co-authorship network of co-authors of Michael S. Chen

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

All Works

18 of 18 papers shown
1.
Chen, Michael S., et al.. (2025). Direct observation and control of non-classical crystallization pathways in binary colloidal systems. Nature Communications. 16(1). 3645–3645. 2 indexed citations
2.
Wang, Yuanqing, Michael S. Chen, Marcus Wieder, et al.. (2025). On the design space between molecular mechanics and machine learning force fields. Applied Physics Reviews. 12(2). 10 indexed citations
3.
Hu, Frank, Michael S. Chen, Minjung Son, et al.. (2025). Two-Dimensional Electronic Spectroscopy in the Condensed Phase Using Equivariant Transformer Accelerated Molecular Dynamics Simulations. The Journal of Physical Chemistry Letters. 16(22). 5561–5569. 2 indexed citations
4.
5.
Chen, Michael S., et al.. (2024). A user-inspired mobility experience of the future: a qualitative investigation. Disability and Rehabilitation Assistive Technology. 20(2). 360–369.
6.
Hu, Frank, Michael S. Chen, Grant M. Rotskoff, Matthew W. Kanan, & Thomas E. Markland. (2024). Accurate and Efficient Structure Elucidation from Routine One-Dimensional NMR Spectra Using Multitask Machine Learning. ACS Central Science. 10(11). 2162–2170. 14 indexed citations
7.
Chen, Michael S., Yuezhi Mao, Andrés Montoya−Castillo, et al.. (2023). Elucidating the Role of Hydrogen Bonding in the Optical Spectroscopy of the Solvated Green Fluorescent Protein Chromophore: Using Machine Learning to Establish the Importance of High-Level Electronic Structure. The Journal of Physical Chemistry Letters. 14(29). 6610–6619. 14 indexed citations
8.
Chen, Michael S., Joonho Lee, Hong‐Zhou Ye, et al.. (2023). Data-Efficient Machine Learning Potentials from Transfer Learning of Periodic Correlated Electronic Structure Methods: Liquid Water at AFQMC, CCSD, and CCSD(T) Accuracy. Journal of Chemical Theory and Computation. 19(14). 4510–4519. 58 indexed citations
9.
Chen, Michael S., et al.. (2021). A framework for automated structure elucidation from routine NMR spectra. Chemical Science. 12(46). 15329–15338. 37 indexed citations
10.
Chen, Michael S., Tobias Morawietz, Hideki Mori, Thomas E. Markland, & Nongnuch Artrith. (2021). AENET–LAMMPS and AENET–TINKER: Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials. The Journal of Chemical Physics. 155(7). 74801–74801. 21 indexed citations
11.
Ghosal, Sutapa, Michael S. Chen, Jeff Wagner, Zhong-Min Wang, & Stephen Wall. (2017). Molecular identification of polymers and anthropogenic particles extracted from oceanic water and fish stomach – A Raman micro-spectroscopy study. Environmental Pollution. 233. 1113–1124. 103 indexed citations
12.
Chen, Michael S., et al.. (2013). Novel metal gates for high κ applications. Journal of Applied Physics. 113(3). 3 indexed citations
13.
Chen, Michael S. & Deepak L. Bhatt. (2007). Bhatt response to the letter to the editor by Michaels. American Heart Journal. 153(3). e7–e7. 1 indexed citations
14.
Chen, Michael S., et al.. (2006). Bare metal stent restenosis is not a benign clinical entity. American Heart Journal. 151(6). 1260–1264. 299 indexed citations
15.
Chen, Michael S., Deepak L. Bhatt, Derek P. Chew, et al.. (2005). Outcomes in African Americans and whites after percutaneous coronary intervention. The American Journal of Medicine. 118(9). 1019–1025. 21 indexed citations
16.
Chen, Michael S., Deepak L. Bhatt, Debabrata Mukherjee, et al.. (2004). Feasibility of simultaneous bilateral carotid artery stenting. Catheterization and Cardiovascular Interventions. 61(4). 437–442. 29 indexed citations
17.
Chen, Michael S. & Deepak L. Bhatt. (2003). Highlights of the 2002 Update to the 2000 American College of Cardiology/American Heart Association Acute Coronary Syndrome Guidelines. Cardiology in Review. 11(3). 113–121. 7 indexed citations
18.
Corey, Joseph M., et al.. (1997). Differentiated B104 neuroblastoma cells are a high-resolution assay for micropatterned substrates. Journal of Neuroscience Methods. 75(1). 91–97. 20 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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