M.J. Willis

1.1k total citations
42 papers, 771 citations indexed

About

M.J. Willis is a scholar working on Control and Systems Engineering, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, M.J. Willis has authored 42 papers receiving a total of 771 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Control and Systems Engineering, 19 papers in Artificial Intelligence and 6 papers in Molecular Biology. Recurrent topics in M.J. Willis's work include Fault Detection and Control Systems (30 papers), Advanced Control Systems Optimization (27 papers) and Neural Networks and Applications (14 papers). M.J. Willis is often cited by papers focused on Fault Detection and Control Systems (30 papers), Advanced Control Systems Optimization (27 papers) and Neural Networks and Applications (14 papers). M.J. Willis collaborates with scholars based in United Kingdom, Australia and Sweden. M.J. Willis's co-authors include G.A. Montague, M.T. Tham, C. Di Massimo, A.J. Morris, A.J. Morris, Hugo Hiden, Andrew Whiting, Stephen K. Scott, A.R. Wright and Katarina Novakovic and has published in prestigious journals such as Automatica, Chemical Physics Letters and Energy.

In The Last Decade

M.J. Willis

38 papers receiving 700 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M.J. Willis United Kingdom	12	519	294	109	101	73	42	771
N. Bhat United States	5	587 1.1×	397 1.4×	108 1.0×	86 0.9×	28 0.4×	8	811
M.T. Tham United Kingdom	17	900 1.7×	414 1.4×	184 1.7×	153 1.5×	125 1.7×	80	1.3k
X.Z. Wang United Kingdom	13	265 0.5×	101 0.3×	177 1.6×	134 1.3×	40 0.5×	29	835
Arthur K. Kordon United States	11	465 0.9×	161 0.5×	301 2.8×	167 1.7×	27 0.4×	33	703
Iván Castillo United States	14	461 0.9×	83 0.3×	161 1.5×	92 0.9×	52 0.7×	42	760
C. Di Massimo United Kingdom	6	368 0.7×	201 0.7×	65 0.6×	61 0.6×	65 0.9×	10	502
Derrick K. Rollins United States	14	324 0.6×	72 0.2×	91 0.8×	66 0.7×	42 0.6×	68	761
Richard S. H. Mah United States	16	676 1.3×	93 0.3×	204 1.9×	155 1.5×	22 0.3×	31	921
V. Van Breusegem Belgium	11	315 0.6×	74 0.3×	107 1.0×	51 0.5×	133 1.8×	20	561
Xinggao Liu China	13	225 0.4×	102 0.3×	84 0.8×	102 1.0×	27 0.4×	15	390

Countries citing papers authored by M.J. Willis

Since Specialization

Citations

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

Fields of papers citing papers by M.J. Willis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.J. Willis. 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 M.J. Willis. The network helps show where M.J. Willis may publish in the future.

Co-authorship network of co-authors of M.J. Willis

This figure shows the co-authorship network connecting the top 25 collaborators of M.J. Willis. A scholar is included among the top collaborators of M.J. Willis 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 M.J. Willis. M.J. Willis 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

Robbins, David, et al.. (2007). CrystalMation: Capacity, reproducibility and efficiency of a fully integrated automatic high-throughput crystallization platform. Acta Crystallographica Section A Foundations of Crystallography. 63(a1). s117–s117. 1 indexed citations

Burnham, Samantha C., M.J. Willis, & A.R. Wright. (2007). IDENTIFYING CHEMICAL REACTION NETWORK MODELS. IFAC Proceedings Volumes. 40(5). 225–230. 1 indexed citations

Novakovic, Katarina, Christophe Grosjean, Stephen K. Scott, et al.. (2006). Achieving pH and Qr oscillations in a palladium-catalysed phenylacetylene oxidative carbonylation reaction using an automated reactor system. Chemical Physics Letters. 435(1-3). 142–147. 27 indexed citations

Montague, G.A., M.J. Willis, & A.J. Morris. (2005). Artificial neural network model based control. 2. 2134–2138. 1 indexed citations

McKay, Ben, M.J. Willis, & G.W. Barton. (2002). On the application of genetic programming to chemical process systems. 2. 701–706.

Willis, M.J.. (1997). Systems Modelling using Genetic Programming. Computers & Chemical Engineering. 21(1-2). S1161–S1166. 16 indexed citations

Willis, M.J. & G.A. Montague. (1993). Auto-Tuning PI(D) Controllers with Artificial Neural Networks. IFAC Proceedings Volumes. 26(2). 141–144. 6 indexed citations

Willis, M.J.. (1992). Soft-sensing via artificial neural networks. 3 indexed citations

Montague, G.A., A.J. Morris, & M.J. Willis. (1992). Neural networks (methodologies for process modelling and control). Annual Review in Automatic Programming. 17. 43–48. 2 indexed citations

10.

Willis, M.J., G.A. Montague, & A.J. Morris. (1992). Special Feature. Modelling of industrial processes using artificial neural networks. Computing & Control Engineering Journal. 3(3). 113–113. 6 indexed citations

11.

Willis, M.J., G.A. Montague, C. Di Massimo, M.T. Tham, & A.J. Morris. (1992). Artificial neural networks in process estimation and control. Automatica. 28(6). 1181–1187. 156 indexed citations

12.

Cox, C.S., et al.. (1992). Intelligent Tuning of P+I Controllers for Bioprocess Application. IFAC Proceedings Volumes. 25(10). 403–408. 2 indexed citations

13.

Massimo, C. Di, G.A. Montague, M.J. Willis, M.T. Tham, & A.J. Morris. (1992). Towards improved penicillin fermentation via artificial neural networks. Computers & Chemical Engineering. 16(4). 283–291. 80 indexed citations

14.

Montague, G.A., M.J. Willis, M.T. Tham, & A.J. Morris. (1991). Artificial neural network based multivariable predictive control. 119–123. 8 indexed citations

15.

Montague, G.A., M.J. Willis, M.T. Tham, & A.J. Morris. (1991). Artificial neural network based control. 266–271. 11 indexed citations

16.

Willis, M.J., M.T. Tham, G.A. Montague, & A.J. Morris. (1991). Non-Linear Predictive Control. IFAC Proceedings Volumes. 24(1). 69–74. 14 indexed citations

17.

Massimo, C. Di, M.J. Willis, G.A. Montague, M.T. Tham, & A.J. Morris. (1991). Bioprocess model building using artificial neural networks. Bioprocess Engineering. 7(1-2). 77–82. 31 indexed citations

18.

Willis, M.J., C. Di Massimo, G.A. Montague, M.T. Tham, & A.J. Morris. (1991). Artificial neural networks in process engineering. IEE Proceedings D Control Theory and Applications. 138(3). 256–256. 185 indexed citations

19.

Willis, M.J., G.A. Montague, C. Di Massimo, M.T. Tham, & A.J. Morris. (1991). Non-Linear Predictive Control using Optimisation Techniques. 2788–2793. 5 indexed citations

20.

Lant, Paul, M.J. Willis, G.A. Montague, M.T. Tham, & A.J. Morris. (1990). A Comparison of Adaptive Estimation with Neural based Techniques for Bioprocess Application. 2173–2178. 21 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.

Explore authors with similar magnitude of impact