Moo Sun Hong

680 total citations
25 papers, 472 citations indexed

About

Moo Sun Hong is a scholar working on Molecular Biology, Materials Chemistry and Control and Systems Engineering. According to data from OpenAlex, Moo Sun Hong has authored 25 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Materials Chemistry and 7 papers in Control and Systems Engineering. Recurrent topics in Moo Sun Hong's work include Viral Infectious Diseases and Gene Expression in Insects (7 papers), Crystallization and Solubility Studies (6 papers) and Protein purification and stability (6 papers). Moo Sun Hong is often cited by papers focused on Viral Infectious Diseases and Gene Expression in Insects (7 papers), Crystallization and Solubility Studies (6 papers) and Protein purification and stability (6 papers). Moo Sun Hong collaborates with scholars based in United States, South Korea and Switzerland. Moo Sun Hong's co-authors include Richard D. Braatz, Andrew J. Maloney, Stacy L. Springs, Mo Jiang, Anthony J. Sinskey, Jacqueline M. Wolfrum, J. Christopher Love, Paul W. Barone, Tam Nguyen and Sha Sha and has published in prestigious journals such as Automatica, Joule and Chemical Engineering Science.

In The Last Decade

Moo Sun Hong

22 papers receiving 459 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Moo Sun Hong United States 9 261 144 93 66 65 25 472
Zhang Zhong China 13 143 0.5× 25 0.2× 63 0.7× 76 1.2× 82 1.3× 48 524
Matthieu Stettler Switzerland 23 978 3.7× 111 0.8× 18 0.2× 361 5.5× 53 0.8× 32 1.2k
Ning Chen China 13 247 0.9× 25 0.2× 100 1.1× 107 1.6× 88 1.4× 37 599
Tuan Anh Phan United States 10 107 0.4× 46 0.3× 23 0.2× 19 0.3× 39 0.6× 34 309
Andrew K. Forrest United Kingdom 18 381 1.5× 58 0.4× 54 0.6× 38 0.6× 6 0.1× 46 960
Zhiyong Ye China 14 127 0.5× 55 0.4× 24 0.3× 31 0.5× 91 1.4× 36 537
Tobias Hahn Germany 19 528 2.0× 12 0.1× 108 1.2× 165 2.5× 40 0.6× 45 779
Richard J. Carter United States 14 336 1.3× 80 0.6× 60 0.6× 21 0.3× 7 0.1× 29 800
Sumit Kumar Singh India 12 208 0.8× 60 0.4× 17 0.2× 38 0.6× 8 0.1× 44 662
Weiyuan Chen China 19 106 0.4× 17 0.1× 61 0.7× 61 0.9× 28 0.4× 64 991

Countries citing papers authored by Moo Sun Hong

Since Specialization
Citations

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

Fields of papers citing papers by Moo Sun Hong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Moo Sun Hong. 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 Moo Sun Hong. The network helps show where Moo Sun Hong may publish in the future.

Co-authorship network of co-authors of Moo Sun Hong

This figure shows the co-authorship network connecting the top 25 collaborators of Moo Sun Hong. A scholar is included among the top collaborators of Moo Sun Hong 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 Moo Sun Hong. Moo Sun Hong 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.
Hong, Moo Sun, Jacqueline M. Wolfrum, Paul W. Barone, et al.. (2025). An Integrated Experimental and Modeling Approach for Crystallization of Complex Biotherapeutics. Crystal Growth & Design. 25(11). 3687–3696.
2.
Hong, Moo Sun, et al.. (2024). Investigation of particle flow effects in slug flow crystallization using the multiscale computational fluid dynamics simulation. Chemical Engineering Science. 297. 120238–120238. 4 indexed citations
3.
Byun, Sejin, Bangzhi Ge, Hyung‐Jun Song, et al.. (2024). Simultaneously engineering electronic and phonon band structures for high-performance n-type polycrystalline SnSe. Joule. 8(5). 1520–1538. 46 indexed citations
4.
Mohr, F. W., Moo Sun Hong, Benjamin T. Smith, et al.. (2023). Tensorial approaches combining time series and batch data for the end-to-end batch manufacturing of monoclonal antibodies. Computers & Chemical Engineering. 182. 108557–108557.
5.
Maloney, Andrew J., José Sangerman, Moo Sun Hong, et al.. (2023). Automated outlier detection and estimation of missing data. Computers & Chemical Engineering. 180. 108448–108448. 6 indexed citations
6.
Hong, Moo Sun, F. W. Mohr, Benjamin T. Smith, et al.. (2023). Smart process analytics for the end-to-end batch manufacturing of monoclonal antibodies. Computers & Chemical Engineering. 179. 108445–108445. 6 indexed citations
7.
Hong, Moo Sun. (2022). Teaching Process Data Analytics and Machine Learning at MIT. Chemical Engineering Education. 56(4). 1 indexed citations
8.
Jeon, Pil Rip, Moo Sun Hong, & Richard D. Braatz. (2022). Compact neural network modeling of nonlinear dynamical systems via the standard nonlinear operator form. Computers & Chemical Engineering. 159. 107674–107674. 5 indexed citations
9.
Hong, Moo Sun, et al.. (2022). Dynamic state feedback controller and observer design for dynamic artificial neural network models. Automatica. 146. 110622–110622. 10 indexed citations
10.
Lee, Yong-Kyu, et al.. (2021). Mathematical modeling and experimental validation of continuous slug-flow tubular crystallization with ultrasonication-induced nucleation and spatially varying temperature. Process Safety and Environmental Protection. 169. 275–287. 18 indexed citations
11.
Hong, Moo Sun & Richard D. Braatz. (2021). Mechanistic modeling and parameter-adaptive nonlinear model predictive control of a microbioreactor. Computers & Chemical Engineering. 147. 107255–107255. 12 indexed citations
12.
Nguyen, Tam, Sha Sha, Moo Sun Hong, et al.. (2021). Mechanistic model for production of recombinant adeno-associated virus via triple transfection of HEK293 cells. Molecular Therapy — Methods & Clinical Development. 21. 642–655. 66 indexed citations
13.
Gimpel, Andreas L., Georgios Katsikis, Sha Sha, et al.. (2021). Analytical methods for process and product characterization of recombinant adeno-associated virus-based gene therapies. Molecular Therapy — Methods & Clinical Development. 20. 740–754. 117 indexed citations
14.
Hong, Moo Sun, et al.. (2021). Output Feedback Control and Observer Design for Dynamic Artificial Neural Networks. 2613–2618. 2 indexed citations
15.
Hong, Moo Sun, et al.. (2021). Tunable protein crystal size distribution via continuous slug-flow crystallization with spatially varying temperature. CrystEngComm. 23(37). 6495–6505. 8 indexed citations
16.
Hong, Moo Sun, M. Lourdes Velez‐Suberbie, Andrew J. Maloney, et al.. (2020). Macroscopic modeling of bioreactors for recombinant protein producing Pichia pastoris in defined medium. Biotechnology and Bioengineering. 118(3). 1199–1212. 17 indexed citations
17.
Tian, Geng, Sau L. Lee, Xiaochuan Yang, et al.. (2017). A dimensionless analysis of residence time distributions for continuous powder mixing. Powder Technology. 315. 332–338. 34 indexed citations
18.
Hong, Moo Sun, et al.. (2017). Challenges and opportunities in biopharmaceutical manufacturing control. Computers & Chemical Engineering. 110. 106–114. 87 indexed citations
19.
20.
Sunwoo, Myung Hoon, et al.. (2002). A fixed-point multimedia DSP chip for portable multimedia services. 94–102. 5 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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