Jesus Flores‐Cerrillo

1.3k total citations
37 papers, 992 citations indexed

About

Jesus Flores‐Cerrillo is a scholar working on Control and Systems Engineering, Mechanical Engineering and Analytical Chemistry. According to data from OpenAlex, Jesus Flores‐Cerrillo has authored 37 papers receiving a total of 992 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Control and Systems Engineering, 14 papers in Mechanical Engineering and 9 papers in Analytical Chemistry. Recurrent topics in Jesus Flores‐Cerrillo's work include Fault Detection and Control Systems (23 papers), Advanced Control Systems Optimization (18 papers) and Process Optimization and Integration (11 papers). Jesus Flores‐Cerrillo is often cited by papers focused on Fault Detection and Control Systems (23 papers), Advanced Control Systems Optimization (18 papers) and Process Optimization and Integration (11 papers). Jesus Flores‐Cerrillo collaborates with scholars based in Canada, United States and Estonia. Jesus Flores‐Cerrillo's co-authors include John F. MacGregor, Yanan Cao, Christopher L.E. Swartz, Honglu Yu, Michael Bâldea, Calvin Tsay, Salvador García‐Muñoz, Lawrence Megan, Christos T. Maravelias and K.A. Subramanian and has published in prestigious journals such as SHILAP Revista de lepidopterología, Industrial & Engineering Chemistry Research and Chemical Engineering Science.

In The Last Decade

Jesus Flores‐Cerrillo

35 papers receiving 963 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jesus Flores‐Cerrillo Canada 16 784 288 137 95 68 37 992
Iván Castillo United States 14 461 0.6× 161 0.6× 92 0.7× 77 0.8× 74 1.1× 42 760
Ricardo Rendall Portugal 13 302 0.4× 148 0.5× 115 0.8× 99 1.0× 68 1.0× 29 557
Yining Dong China 18 941 1.2× 491 1.7× 225 1.6× 156 1.6× 48 0.7× 48 1.3k
Hongyang Yu China 16 408 0.5× 330 1.1× 101 0.7× 343 3.6× 33 0.5× 49 916
Sunwon Park South Korea 21 733 0.9× 180 0.6× 53 0.4× 32 0.3× 88 1.3× 71 1.3k
Xiuxi Li China 16 275 0.4× 265 0.9× 58 0.4× 29 0.3× 112 1.6× 34 878
Richard S. H. Mah United States 16 676 0.9× 204 0.7× 155 1.1× 157 1.7× 71 1.0× 31 921
Huaiping Jin China 19 546 0.7× 174 0.6× 111 0.8× 27 0.3× 273 4.0× 56 1.0k
Manojkumar Ramteke India 16 262 0.3× 154 0.5× 37 0.3× 36 0.4× 68 1.0× 64 772
Christopher L.E. Swartz Canada 20 779 1.0× 273 0.9× 11 0.1× 28 0.3× 94 1.4× 96 1.2k

Countries citing papers authored by Jesus Flores‐Cerrillo

Since Specialization
Citations

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

Fields of papers citing papers by Jesus Flores‐Cerrillo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jesus Flores‐Cerrillo. 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 Jesus Flores‐Cerrillo. The network helps show where Jesus Flores‐Cerrillo may publish in the future.

Co-authorship network of co-authors of Jesus Flores‐Cerrillo

This figure shows the co-authorship network connecting the top 25 collaborators of Jesus Flores‐Cerrillo. A scholar is included among the top collaborators of Jesus Flores‐Cerrillo 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 Jesus Flores‐Cerrillo. Jesus Flores‐Cerrillo 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.
Swartz, Christopher L.E., et al.. (2025). Closed-loop control framework for optimal startup of cryogenic air separation units. Journal of Process Control. 154. 103525–103525.
2.
Wang, Yajun, et al.. (2023). Shared Parameter Network: An efficient process monitoring model. Computers & Chemical Engineering. 181. 108522–108522. 3 indexed citations
3.
Swartz, Christopher L.E., et al.. (2023). Dynamic Optimization of Multiproduct Cryogenic Air Separation Unit Startup. Industrial & Engineering Chemistry Research. 62(27). 10542–10558. 5 indexed citations
4.
Flores‐Cerrillo, Jesus, et al.. (2023). Integration of chemical process operation with energy, global market, and plant systems infrastructure. Computers & Chemical Engineering. 182. 108566–108566. 4 indexed citations
5.
Pappas, Iosif, Styliani Avraamidou, Burcu Beykal, et al.. (2022). A smart manufacturing strategy for multiparametric model predictive control in air separation systems. 4(4). 8 indexed citations
6.
Swartz, Christopher L.E., et al.. (2022). Modeling, simulation, and optimization of multiproduct cryogenic air separation unit startup. AIChE Journal. 69(2). 9 indexed citations
7.
Tsay, Calvin, et al.. (2022). A data-driven linear formulation of the optimal demand response scheduling problem for an industrial air separation unit. Chemical Engineering Science. 252. 117468–117468. 20 indexed citations
8.
Lee, Jangwon, Jin Wang, Jesus Flores‐Cerrillo, & Q. Peter He. (2020). Improving Featured-based Soft Sensing through Feature Selection. IFAC-PapersOnLine. 53(2). 11338–11343. 1 indexed citations
9.
Kumar, Ankur, et al.. (2020). Data-driven process monitoring and fault analysis of reformer units in hydrogen plants: Industrial application and perspectives. Computers & Chemical Engineering. 136. 106756–106756. 30 indexed citations
10.
Lee, Jangwon, Jesus Flores‐Cerrillo, Jin Wang, & Q. Peter He. (2020). A Variable Selection Method for Improving Variable Selection Consistency and Soft Sensor Performance. 725–730. 1 indexed citations
11.
Tsay, Calvin, et al.. (2019). Optimal demand response scheduling of an industrial air separation unit using data-driven dynamic models. Computers & Chemical Engineering. 126. 22–34. 79 indexed citations
12.
Garg, Abhinav, Brandon Corbett, Prashant Mhaskar, Gangshi Hu, & Jesus Flores‐Cerrillo. (2017). Subspace-based model identification of a hydrogen plant startup dynamics. Computers & Chemical Engineering. 106. 183–190. 18 indexed citations
13.
Cao, Yanan, Christopher L.E. Swartz, & Jesus Flores‐Cerrillo. (2017). Preemptive dynamic operation of cryogenic air separation units. AIChE Journal. 63(9). 3845–3859. 17 indexed citations
14.
Cao, Yanan, Christopher L.E. Swartz, Jesus Flores‐Cerrillo, & Jingran Ma. (2016). Dynamic modeling and collocation‐based model reduction of cryogenic air separation units. AIChE Journal. 62(5). 1602–1615. 45 indexed citations
15.
Mhaskar, Prashant, et al.. (2014). Safe-Parking of a Hydrogen Production Unit. Industrial & Engineering Chemistry Research. 53(19). 8147–8154. 3 indexed citations
16.
MacGregor, John F., Honglu Yu, Salvador García‐Muñoz, & Jesus Flores‐Cerrillo. (2005). Data-based latent variable methods for process analysis, monitoring and control. Computers & Chemical Engineering. 29(6). 1217–1223. 89 indexed citations
17.
Flores‐Cerrillo, Jesus & John F. MacGregor. (2005). Latent variable MPC for trajectory tracking in batch processes. Journal of Process Control. 15(6). 651–663. 94 indexed citations
18.
Flores‐Cerrillo, Jesus & John F. MacGregor. (2005). Iterative Learning Control for Final Batch Product Quality Using Partial Least Squares Models. Industrial & Engineering Chemistry Research. 44(24). 9146–9155. 55 indexed citations
19.
Flores‐Cerrillo, Jesus & John F. MacGregor. (2004). Model Predictive Control for Batch Processes Using Latent Variable Methods. IFAC Proceedings Volumes. 37(9). 775–780.
20.
Flores‐Cerrillo, Jesus & John F. MacGregor. (2003). Control of batch product quality by trajectory manipulation using latent variable models. Journal of Process Control. 14(5). 539–553. 89 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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