Nathan P. Lawrence

724 total citations
24 papers, 506 citations indexed

About

Nathan P. Lawrence is a scholar working on Molecular Biology, Control and Systems Engineering and Ecology. According to data from OpenAlex, Nathan P. Lawrence has authored 24 papers receiving a total of 506 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Control and Systems Engineering and 6 papers in Ecology. Recurrent topics in Nathan P. Lawrence's work include Advanced Control Systems Optimization (7 papers), Fault Detection and Control Systems (5 papers) and Bacteriophages and microbial interactions (4 papers). Nathan P. Lawrence is often cited by papers focused on Advanced Control Systems Optimization (7 papers), Fault Detection and Control Systems (5 papers) and Bacteriophages and microbial interactions (4 papers). Nathan P. Lawrence collaborates with scholars based in Canada, United States and South Korea. Nathan P. Lawrence's co-authors include R. Bhushan Gopaluni, Philip D. Loewen, Aditya Tulsyan, Sidney Altman, Steven Spielberg, Johan U. Backström, Michael G. Forbes, Richard Schumacher, Chunqin Li and Gary B. Smejkal and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Molecular Biology and Automatica.

In The Last Decade

Nathan P. Lawrence

23 papers receiving 487 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nathan P. Lawrence Canada 13 222 160 68 67 62 24 506
Yoshihisa Ishida Japan 10 233 1.0× 211 1.3× 24 0.4× 114 1.7× 74 1.2× 105 703
Sebastian Albrecht Germany 8 150 0.7× 85 0.5× 40 0.6× 34 0.5× 28 0.5× 34 374
Feng Shu China 13 135 0.6× 230 1.4× 65 1.0× 58 0.9× 193 3.1× 59 861
Bin Du China 12 213 1.0× 66 0.4× 18 0.3× 53 0.8× 21 0.3× 24 471
Danilo Sipoli Sanches Brazil 14 92 0.4× 165 1.0× 8 0.1× 87 1.3× 156 2.5× 52 504
Jianxiong Ye China 17 358 1.6× 310 1.9× 10 0.1× 10 0.1× 41 0.7× 60 720
Valerio Mariani Italy 14 257 1.2× 212 1.3× 10 0.1× 11 0.2× 347 5.6× 32 795
Vijay Manikandan Janakiraman United States 13 74 0.3× 135 0.8× 17 0.3× 158 2.4× 28 0.5× 26 526
Shawna Thomas United States 17 195 0.9× 234 1.5× 26 0.4× 85 1.3× 3 0.0× 50 681

Countries citing papers authored by Nathan P. Lawrence

Since Specialization
Citations

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

Fields of papers citing papers by Nathan P. Lawrence

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan P. Lawrence. 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 Nathan P. Lawrence. The network helps show where Nathan P. Lawrence may publish in the future.

Co-authorship network of co-authors of Nathan P. Lawrence

This figure shows the co-authorship network connecting the top 25 collaborators of Nathan P. Lawrence. A scholar is included among the top collaborators of Nathan P. Lawrence 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 Nathan P. Lawrence. Nathan P. Lawrence 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.
Lawrence, Nathan P., Philip D. Loewen, Michael G. Forbes, R. Bhushan Gopaluni, & Ali Mesbah. (2025). A view on learning robust goal-conditioned value functions: Interplay between RL and MPC. Annual Reviews in Control. 60. 101027–101027.
2.
3.
Lawrence, Nathan P., Philip D. Loewen, Shuyuan Wang, Michael G. Forbes, & R. Bhushan Gopaluni. (2024). Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior. Automatica. 164. 111642–111642. 2 indexed citations
4.
Alabi, Tobi Michael, Nathan P. Lawrence, Lin Lu, Zaiyue Yang, & R. Bhushan Gopaluni. (2023). Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system. Applied Energy. 333. 120633–120633. 30 indexed citations
5.
Lawrence, Nathan P., Philip D. Loewen, Shuyuan Wang, Michael G. Forbes, & R. Bhushan Gopaluni. (2023). A modular framework for stabilizing deep reinforcement learning control. IFAC-PapersOnLine. 56(2). 8006–8011. 1 indexed citations
6.
Lawrence, Nathan P., et al.. (2022). Meta-reinforcement learning for the tuning of PI controllers: An offline approach. Journal of Process Control. 118. 139–152. 27 indexed citations
7.
Lawrence, Nathan P., et al.. (2022). Deep reinforcement learning with shallow controllers: An experimental application to PID tuning. Control Engineering Practice. 121. 105046–105046. 73 indexed citations
8.
Lawrence, Nathan P., et al.. (2022). Meta-Reinforcement Learning for Adaptive Control of Second Order Systems. 78–83. 3 indexed citations
9.
Lawrence, Nathan P., Philip D. Loewen, Michael G. Forbes, Johan U. Backström, & R. Bhushan Gopaluni. (2020). Almost Surely Stable Deep Dynamics. Figshare. 33. 18942–18953. 2 indexed citations
10.
Gopaluni, R. Bhushan, Aditya Tulsyan, Benoît Chachuat, et al.. (2020). Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey. IFAC-PapersOnLine. 53(2). 218–229. 33 indexed citations
11.
King, Jonathan L., et al.. (2012). Pressure cycling technology (PCT) reduces effects of inhibitors of the PCR. International Journal of Legal Medicine. 127(2). 321–333. 5 indexed citations
12.
Lazarev, Alexander, et al.. (2008). Isolation of Mitochondria from Cell Cultures by PCT for Proteomic Analysis. BioTechniques. 45(1). 99–100. 7 indexed citations
13.
Okubara, Patricia A., Kurtis L. Schroeder, Chunqin Li, Richard Schumacher, & Nathan P. Lawrence. (2007). Improved extraction of Rhizoctonia and Pythium DNA from wheat roots and soil samples using pressure cycling technology. Canadian Journal of Plant Pathology. 29(3). 304–310. 20 indexed citations
14.
Feng, Tao, Chunqin Li, Gary B. Smejkal, et al.. (2007). Pressure Cycling Technology (PCT) Applications in Extraction of Biomolecules from Challenging Biological Samples. 1(1). 166–173. 10 indexed citations
15.
Smejkal, Gary B., et al.. (2006). Increased protein yields from Escherichia coli using pressure-cycling technology.. PubMed. 17(2). 173–5. 21 indexed citations
16.
Volsky, David J., et al.. (1990). Titration of human immunodeficiency virus type 1 (HIV-1) and quantitative analysis of virus expression in vitro using liquid RNA-RNA hybridization. Journal of Virological Methods. 28(3). 257–271. 14 indexed citations
17.
Lawrence, Nathan P., Donna Wesolowski, H. Gold, et al.. (1987). Characteristics of Ribonuclease P from Various Organisms. Cold Spring Harbor Symposia on Quantitative Biology. 52(0). 233–238. 37 indexed citations
18.
Lawrence, Nathan P., Adam Richman, Rose‐Marie Amini, & Sidney Altman. (1987). Heterologous enzyme function in Escherichia coli and the selection of genes encoding the catalytic RNA subunit of RNase P.. Proceedings of the National Academy of Sciences. 84(19). 6825–6829. 26 indexed citations
19.
Altman, Sidney, H. Gold, Cecilia Guerrier-Takada, et al.. (1987). Cleavage of RNA by RNase P from E. coli. 1 indexed citations
20.
Lawrence, Nathan P. & Sidney Altman. (1986). Site-directed mutagenesis of M1 RNA, the RNA subunit of Escherichia coli ribonuclease P. Journal of Molecular Biology. 191(2). 163–175. 30 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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