Tinkle Chugh

2.2k total citations · 2 hit papers
25 papers, 1.5k citations indexed

About

Tinkle Chugh is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Tinkle Chugh has authored 25 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computational Theory and Mathematics, 13 papers in Artificial Intelligence and 8 papers in Management Science and Operations Research. Recurrent topics in Tinkle Chugh's work include Advanced Multi-Objective Optimization Algorithms (20 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Optimal Experimental Design Methods (8 papers). Tinkle Chugh is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (20 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Optimal Experimental Design Methods (8 papers). Tinkle Chugh collaborates with scholars based in United Kingdom, Finland and India. Tinkle Chugh's co-authors include Kaisa Miettinen, Yaochu Jin, Karthik Sindhya, Jussi Hakanen, Dan Guo, Handing Wang, Nirupam Chakraborti, Hemant Kumar Singh, Tapabrata Ray and Richard Allmendinger and has published in prestigious journals such as Journal of Hydrology, IEEE Transactions on Evolutionary Computation and Engineering Applications of Artificial Intelligence.

In The Last Decade

Tinkle Chugh

24 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Data-Driven Evolutionary Optimization: An Overview and Case Studies

2018 457 citations Yaochu Jin, Handing Wang et al. IEEE Transactions on Evolutionary Computation profile →
A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization

2016 420 citations Tinkle Chugh, Yaochu Jin et al. IEEE Transactions on Evolutionary Computation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tinkle Chugh United Kingdom	11	1.1k	950	335	147	112	25	1.5k
Karthik Sindhya Finland	17	1.1k 1.0×	914 1.0×	298 0.9×	162 1.1×	154 1.4×	23	1.6k
Jussi Hakanen Finland	14	822 0.7×	578 0.6×	284 0.8×	144 1.0×	197 1.8×	38	1.2k
Fangqing Gu China	17	1.4k 1.3×	1.4k 1.5×	279 0.8×	55 0.4×	158 1.4×	70	1.8k
Mayank Kumar Goyal India	9	752 0.7×	745 0.8×	144 0.4×	113 0.8×	133 1.2×	38	1.3k
Xiwen Cai China	19	784 0.7×	600 0.6×	200 0.6×	90 0.6×	40 0.4×	34	1.1k
Dan Guo China	5	540 0.5×	527 0.6×	131 0.4×	64 0.4×	52 0.5×	8	781
Md Asafuddoula Australia	11	555 0.5×	564 0.6×	149 0.4×	36 0.2×	74 0.7×	18	798
Songqing Shan Canada	12	826 0.7×	251 0.3×	274 0.8×	166 1.1×	79 0.7×	16	1.2k
Michael J. Sasena United States	10	593 0.5×	198 0.2×	307 0.9×	116 0.8×	65 0.6×	12	937
Dawei Zhan China	11	371 0.3×	304 0.3×	148 0.4×	63 0.4×	81 0.7×	21	854

Countries citing papers authored by Tinkle Chugh

Since Specialization

Citations

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

Fields of papers citing papers by Tinkle Chugh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tinkle Chugh

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

All Works

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20 of 20 papers shown

Ath, George De, et al.. (2024). Is greed still good in multi-objective Bayesian optimisation?. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2103–2106.

Chugh, Tinkle, et al.. (2024). Handling simulation failures of a computationally expensive multiobjective optimization problem in pump design. Engineering Applications of Artificial Intelligence. 136. 108897–108897. 2 indexed citations

López‐Ibáñez, Manuel, et al.. (2023). Treed Gaussian Process Regression for Solving Offline Data-Driven Continuous Multiobjective Optimization Problems. Evolutionary Computation. 31(4). 375–399. 4 indexed citations

Kumar, Krishan, et al.. (2023). Machine Learning Based Prediction of Energy Density for Additively Manufactured AlSi10Mg Samples by Laser Powder Bed Fusion Process. 465–469. 1 indexed citations

Chugh, Tinkle, et al.. (2022). Wind farm layout optimisation using set based multi-objective bayesian optimisation. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 695–698. 2 indexed citations

Ath, George De, Tinkle Chugh, & Alma Rahat. (2022). MBORE. Proceedings of the Genetic and Evolutionary Computation Conference. 33. 776–785. 1 indexed citations

Chugh, Tinkle. (2022). R-MBO. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1817–1825. 2 indexed citations

Fieldsend, Jonathan E., Tinkle Chugh, Richard Allmendinger, & Kaisa Miettinen. (2021). A Visualizable Test Problem Generator for Many-Objective Optimization. IEEE Transactions on Evolutionary Computation. 26(1). 1–11. 8 indexed citations

Palar, Pramudita Satria, Lavi Rizki Zuhal, Tinkle Chugh, & Alma Rahat. (2020). On the Impact of Covariance Functions in Multi-Objective Bayesian Optimization for Engineering Design. AIAA Scitech 2020 Forum. 6 indexed citations

10.

Singh, Hemant Kumar, et al.. (2019). A Multiple Surrogate Assisted Decomposition-Based Evolutionary Algorithm for Expensive Multi/Many-Objective Optimization. IEEE Transactions on Evolutionary Computation. 23(6). 1000–1014. 113 indexed citations

11.

Fieldsend, Jonathan E., Tinkle Chugh, Richard Allmendinger, & Kaisa Miettinen. (2019). A feature rich distance-based many-objective visualisable test problem generator. Proceedings of the Genetic and Evolutionary Computation Conference. 541–549. 13 indexed citations

12.

Chugh, Tinkle, et al.. (2019). Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm. Proceedings of the Genetic and Evolutionary Computation Conference. 1147–1155. 6 indexed citations

13.

Chugh, Tinkle, et al.. (2018). Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies. Proceedings of the Genetic and Evolutionary Computation Conference. 609–616. 13 indexed citations

14.

Jin, Yaochu, Handing Wang, Tinkle Chugh, Dan Guo, & Kaisa Miettinen. (2018). Data-Driven Evolutionary Optimization: An Overview and Case Studies. IEEE Transactions on Evolutionary Computation. 23(3). 442–458. 457 indexed citations breakdown →

15.

Chugh, Tinkle, et al.. (2017). Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system. Jyväskylä University Digital Archive (University of Jyväskylä). 1541–1548. 33 indexed citations

16.

Chugh, Tinkle. (2017). Handling expensive multiobjective optimization problems with evolutionary algorithms. Jyväskylä University Digital Archive (University of Jyväskylä). 3 indexed citations

17.

Chugh, Tinkle, Karthik Sindhya, Jussi Hakanen, & Kaisa Miettinen. (2017). A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms. Soft Computing. 23(9). 3137–3166. 207 indexed citations

18.

Hakanen, Jussi, Tinkle Chugh, Karthik Sindhya, Yaochu Jin, & Kaisa Miettinen. (2016). Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms. 1–8. 22 indexed citations

19.

Chugh, Tinkle, Nirupam Chakraborti, Karthik Sindhya, & Yaochu Jin. (2016). A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem. Materials and Manufacturing Processes. 32(10). 1172–1178. 99 indexed citations

20.

Chugh, Tinkle, Yaochu Jin, Kaisa Miettinen, Jussi Hakanen, & Karthik Sindhya. (2016). A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization. IEEE Transactions on Evolutionary Computation. 22(1). 129–142. 420 indexed citations breakdown →

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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