Dongda Zhang

3.2k total citations
98 papers, 2.2k citations indexed

About

Dongda Zhang is a scholar working on Control and Systems Engineering, Molecular Biology and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Dongda Zhang has authored 98 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Control and Systems Engineering, 34 papers in Molecular Biology and 29 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Dongda Zhang's work include Algal biology and biofuel production (28 papers), Advanced Control Systems Optimization (24 papers) and Microbial Metabolic Engineering and Bioproduction (23 papers). Dongda Zhang is often cited by papers focused on Algal biology and biofuel production (28 papers), Advanced Control Systems Optimization (24 papers) and Microbial Metabolic Engineering and Bioproduction (23 papers). Dongda Zhang collaborates with scholars based in United Kingdom, China and United States. Dongda Zhang's co-authors include Ehecatl Antonio del Rio‐Chanona, Keju Jing, Max Mowbray, Jonathan L. Wagner, Klaus Hellgardt, Vassilios S. Vassiliadis, Panagiotis Petsagkourakis, P. K. Hepler, Patricia Wadsworth and Thomas Savage and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Renewable and Sustainable Energy Reviews.

In The Last Decade

Dongda Zhang

89 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dongda Zhang United Kingdom	30	835	602	545	422	153	98	2.2k
Ehecatl Antonio del Rio‐Chanona United Kingdom	29	618 0.7×	633 1.1×	468 0.9×	397 0.9×	143 0.9×	92	2.0k
A.J.B. van Boxtel Netherlands	27	347 0.4×	302 0.5×	850 1.6×	506 1.2×	227 1.5×	98	2.5k
Fabrizio Bezzo Italy	33	557 0.7×	951 1.6×	363 0.7×	1.3k 3.1×	573 3.7×	149	3.7k
Bernd Hitzmann Germany	31	1.5k 1.8×	437 0.7×	103 0.2×	917 2.2×	145 0.9×	232	3.5k
Jianping Chen China	26	453 0.5×	170 0.3×	248 0.5×	306 0.7×	180 1.2×	171	2.2k
Vassilios S. Vassiliadis United Kingdom	26	391 0.5×	1.2k 1.9×	304 0.6×	345 0.8×	213 1.4×	88	2.5k
M. Nazmul Karim United States	29	1.1k 1.3×	818 1.4×	132 0.2×	1.4k 3.3×	567 3.7×	142	3.2k
Αθανάσιος Ι. Παπαδόπουλος Greece	30	199 0.2×	664 1.1×	368 0.7×	635 1.5×	1.6k 10.4×	104	2.8k
Richard C. Baliban United States	28	1.1k 1.3×	687 1.1×	218 0.4×	906 2.1×	544 3.6×	29	2.9k
Benoît Chachuat United Kingdom	30	181 0.2×	1.7k 2.7×	336 0.6×	241 0.6×	309 2.0×	148	3.0k

Countries citing papers authored by Dongda Zhang

Since Specialization

Citations

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

Fields of papers citing papers by Dongda Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongda Zhang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Avalos‬, José L., et al.. (2025). Reinforcement learning for efficient and robust multi-setpoint and multi-trajectory tracking in bioprocesses. Computers & Chemical Engineering. 202. 109297–109297. 1 indexed citations

Mendoza, César, et al.. (2025). Integrating feature attribution and symbolic regression for automatic model structure identification and strategic sampling. Computers & Chemical Engineering. 197. 109036–109036. 3 indexed citations

Feng, Yansong, et al.. (2025). Accelerating bioprocess digital twin development by integrating hybrid modelling with transfer learning. Chemical Engineering Journal. 511. 162018–162018. 14 indexed citations

Wang, Linqiang, et al.. (2025). Data-driven review of customer engagement: key research themes and future directions. Electronic Commerce Research.

Stitt, E. Hugh, et al.. (2025). Developing a Hybrid Modeling Framework for Enhanced Prediction in Chemical Reaction Kinetics. Industrial & Engineering Chemistry Research. 64(33). 16027–16038.

Shaw, Jane M., et al.. (2025). A novel approach to identify optimal and flexible operational spaces for product quality control. Chemical Engineering Science. 309. 121429–121429.

Bywater, Angela, et al.. (2025). Anaerobic digestion site-wide optimisation and decision-making: An industrial perspective and review. Renewable and Sustainable Energy Reviews. 226. 116402–116402. 1 indexed citations

Cho, Bovinille Anye, et al.. (2024). Synergistic interplay of photobioreactor mixing and static mixer configuration on Rhodoseupdomonas palustris’s growth and biohydrogen production. Fuel. 378. 132861–132861. 3 indexed citations

Mendoza, César, et al.. (2024). Integrating Knowledge-Guided Symbolic Regression and Model-Based Design of Experiments to Accelerate Process Flow Diagram Development. IFAC-PapersOnLine. 58(14). 127–132.

10.

Dickson, Alan J., et al.. (2024). Dynamic Multiscale Hybrid Modelling of a CHO cell system for Recombinant Protein Production. IFAC-PapersOnLine. 58(14). 133–138. 1 indexed citations

11.

Dickson, Alan J., et al.. (2024). A multiscale hybrid modelling methodology for cell cultures enabled by enzyme-constrained dynamic metabolic flux analysis under uncertainty. Metabolic Engineering. 86. 274–287. 3 indexed citations

12.

Hardacre, Christopher, et al.. (2024). Cracking the physical insight of power law models: Bridging the gap between macroscopic kinetics and surface coverages. AIChE Journal. 71(1). 1 indexed citations

13.

Hellgardt, Klaus, et al.. (2024). Investigating the reliability and interpretability of machine learning frameworks for chemical retrosynthesis. Digital Discovery. 3(6). 1194–1212. 4 indexed citations

14.

Cho, Bovinille Anye, et al.. (2022). An MIQP framework for metabolic pathways optimisation and dynamic flux analysis. SHILAP Revista de lepidopterología. 2. 100011–100011. 7 indexed citations

15.

Savage, Thomas, et al.. (2021). Kinetic and hybrid modeling for yeast astaxanthin production under uncertainty. Biotechnology and Bioengineering. 118(12). 4854–4866. 36 indexed citations

16.

Li, Huijun, Xiaojing An, Dongda Zhang, et al.. (2020). Transcriptomics Analysis of the Tumor-Inhibitory Pathways of 6-Thioguanine in MCF-7 Cells via Silencing DNMT1 Activity. SHILAP Revista de lepidopterología. 1 indexed citations

17.

Zhang, Dongda, Ehecatl Antonio del Rio‐Chanona, & Nilay Shah. (2018). Life cycle assessments for biomass derived sustainable biopolymer & energy co-generation. Sustainable Production and Consumption. 15. 109–118. 8 indexed citations

18.

Zhang, Dongda, Ehecatl Antonio del Rio‐Chanona, Vassilios S. Vassiliadis, & Bojan Tamburic. (2015). Analysis of green algal growth via dynamic model simulation and process optimization. Biotechnology and Bioengineering. 112(10). 2025–2039. 25 indexed citations

19.

Zhang, Dongda, et al.. (2015). Analysis of the cyanobacterial hydrogen photoproduction process via model identification and process simulation. Chemical Engineering Science. 128. 130–146. 26 indexed citations

20.

Zhang, Dongda, et al.. (2015). Modelling of light and temperature influences on cyanobacterial growth and biohydrogen production. Algal Research. 9. 263–274. 62 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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