Linas Mockus

906 total citations
39 papers, 584 citations indexed

About

Linas Mockus is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering and Management Science and Operations Research. According to data from OpenAlex, Linas Mockus has authored 39 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Control and Systems Engineering, 11 papers in Industrial and Manufacturing Engineering and 7 papers in Management Science and Operations Research. Recurrent topics in Linas Mockus's work include Process Optimization and Integration (11 papers), Advanced Control Systems Optimization (9 papers) and Scheduling and Optimization Algorithms (9 papers). Linas Mockus is often cited by papers focused on Process Optimization and Integration (11 papers), Advanced Control Systems Optimization (9 papers) and Scheduling and Optimization Algorithms (9 papers). Linas Mockus collaborates with scholars based in United States, Malaysia and Australia. Linas Mockus's co-authors include Gintaras V. Reklaitis, Seza Orçun, Ye Chen, José M. Laínez‐Aguirre, Audris Mockus, Daniel DeLaurentis, Ali K. Raz, William Eddy, John J. Peterson and Prabir K. Basu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Technometrics and Industrial & Engineering Chemistry Research.

In The Last Decade

Linas Mockus

38 papers receiving 558 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Linas Mockus United States 13 322 248 76 48 44 39 584
Gabriela P. Henning Argentina 18 513 1.6× 630 2.5× 87 1.1× 29 0.6× 47 1.1× 35 940
Xiong Wang China 12 108 0.3× 281 1.1× 74 1.0× 18 0.4× 55 1.3× 51 602
Can Li China 14 548 1.7× 92 0.4× 19 0.3× 25 0.5× 61 1.4× 43 889
Ana Bušić France 12 169 0.5× 31 0.1× 51 0.7× 10 0.2× 41 0.9× 51 715
Hao‐Chun Lu Taiwan 13 64 0.2× 92 0.4× 40 0.5× 9 0.2× 57 1.3× 31 383
Altannar Chinchuluun United States 9 204 0.6× 50 0.2× 46 0.6× 12 0.3× 265 6.0× 21 461
Da-Zhong Zheng China 13 371 1.2× 358 1.4× 42 0.6× 5 0.1× 78 1.8× 38 1.0k
M. G. Beckman United States 5 400 1.2× 40 0.2× 232 3.1× 7 0.1× 36 0.8× 11 1.3k

Countries citing papers authored by Linas Mockus

Since Specialization
Citations

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

Fields of papers citing papers by Linas Mockus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linas Mockus

This figure shows the co-authorship network connecting the top 25 collaborators of Linas Mockus. A scholar is included among the top collaborators of Linas Mockus 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 Linas Mockus. Linas Mockus 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.
Raz, Ali K., et al.. (2024). Explainable AI and Robustness-Based Test and Evaluation of Reinforcement Learning. IEEE Transactions on Aerospace and Electronic Systems. 60(5). 6110–6123. 3 indexed citations
2.
Holford, Nicholas H. G., Karel Allegaert, Brian J. Anderson, et al.. (2023). A physiological approach to renal clearance: From premature neonates to adults. British Journal of Clinical Pharmacology. 90(4). 1066–1080. 7 indexed citations
3.
Mockus, Linas, David LeBlond, Xu Sun, et al.. (2022). Bayesian statistical approaches to drug product variability assessment and release. International Journal of Pharmaceutics. 624. 122037–122037.
4.
Raz, Ali K., et al.. (2022). Test and Evaluation of Reinforcement Learning via Robustness Testing and Explainable AI for High-Speed Aerospace Vehicles. 2022 IEEE Aerospace Conference (AERO). 1–14. 6 indexed citations
5.
Rossi, Francesco, Linas Mockus, Flavio Manenti, & Gintaras V. Reklaitis. (2019). Present and future of model uncertainty quantification in process systems engineering. SHILAP Revista de lepidopterología. 74. 625–630. 4 indexed citations
6.
Mockus, Linas, Gintaras V. Reklaitis, Kenneth R. Morris, & David LeBlond. (2019). Risk-Based Approach to Lot Release. Journal of Pharmaceutical Sciences. 109(2). 1035–1042. 2 indexed citations
7.
Raz, Ali K., et al.. (2019). Experiences in Evolving System-of-Systems Engineering Methodology to Address Pain Points. 189–194. 3 indexed citations
8.
Laínez‐Aguirre, José M., Linas Mockus, Seza Orçun, Gary Blau, & Gintaras V. Reklaitis. (2015). A Decomposition Strategy for the Variational Inference of Complex Systems. Technometrics. 58(1). 84–94. 3 indexed citations
9.
Mockus, Linas, John J. Peterson, José M. Laínez‐Aguirre, & Gintaras V. Reklaitis. (2014). Batch-to-Batch Variation: A Key Component for Modeling Chemical Manufacturing Processes. Organic Process Research & Development. 19(8). 908–914. 28 indexed citations
10.
DeLaurentis, Daniel, et al.. (2014). Comparative Solution Methods for the Integrated Problem of Sensors, Weapons, and Targets. AIAA Modeling and Simulation Technologies Conference. 3 indexed citations
11.
Mockus, Linas, David LeBlond, Prabir K. Basu, Rakhi B. Shah, & Mansoor A. Khan. (2011). A QbD Case Study: Bayesian Prediction of Lyophilization Cycle Parameters. AAPS PharmSciTech. 12(1). 442–448. 8 indexed citations
12.
Mockus, Linas, Nancy J. Harper, Prabir K. Basu, et al.. (2011). Quality by design in formulation and process development for a freeze-dried, small molecule parenteral product: a case study. Pharmaceutical Development and Technology. 16(6). 549–576. 40 indexed citations
13.
Basu, Prabir K., Mansoor A. Khan, Carl Wassgren, et al.. (2011). NIPTE-FDA Excipients Knowledge Base. 2 indexed citations
14.
Mockus, Linas, et al.. (2002). The integration of production plan and operating schedule in a pharmaceutical pilot plant. Computers & Chemical Engineering. 26(4-5). 697–702. 4 indexed citations
15.
Mockus, Linas, et al.. (1999). A framework for schedule evaluation with processing uncertainty. Computers & Chemical Engineering. 23(4-5). 595–609. 56 indexed citations
16.
Zhao, Jinsong, et al.. (1999). Integrating operating procedure synthesis and hazards analysis automation tools for batch processes. Computers & Chemical Engineering. 23. S747–S750. 9 indexed citations
17.
Mockus, Linas, et al.. (1998). iTOPS: An intelligent tool for operating procedures synthesis. Computers & Chemical Engineering. 22. S601–S608. 7 indexed citations
18.
Mockus, Linas & Gintaras V. Reklaitis. (1998). Continuous Time Representation Approach to Batch and Continuous Process Scheduling. 2. Computational Issues. Industrial & Engineering Chemistry Research. 38(1). 204–210. 23 indexed citations
19.
Mockus, Linas & Gintaras V. Reklaitis. (1996). Continuous time representation in batch/semicontinuous process scheduling: Randomized heuristics approach. Computers & Chemical Engineering. 20. S1173–S1177. 11 indexed citations
20.
Mockus, Audris, et al.. (1994). Bayesian approach adapting stochastic and heuristic methods of global and discrete optimization. 5. 123–166. 6 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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