Daniil Bash

646 total citations
10 papers, 429 citations indexed

About

Daniil Bash is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Biomedical Engineering. According to data from OpenAlex, Daniil Bash has authored 10 papers receiving a total of 429 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Materials Chemistry, 3 papers in Electrical and Electronic Engineering and 3 papers in Biomedical Engineering. Recurrent topics in Daniil Bash's work include Machine Learning in Materials Science (7 papers), Advanced Memory and Neural Computing (2 papers) and Advanced Thermoelectric Materials and Devices (2 papers). Daniil Bash is often cited by papers focused on Machine Learning in Materials Science (7 papers), Advanced Memory and Neural Computing (2 papers) and Advanced Thermoelectric Materials and Devices (2 papers). Daniil Bash collaborates with scholars based in Singapore, United States and Canada. Daniil Bash's co-authors include Kedar Hippalgaonkar, Zekun Ren, Tonio Buonassisi, Flore Mekki‐Berrada, Saif A. Khan, Xiaonan Wang, Tan Huang, Qianxiao Li, Siyu Tian and Wai Kuan Wong and has published in prestigious journals such as PLoS ONE, Advanced Functional Materials and Journal of Materials Chemistry A.

In The Last Decade

Daniil Bash

9 papers receiving 423 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniil Bash Singapore	7	263	114	92	53	53	10	429
Flore Mekki‐Berrada Singapore	7	206 0.8×	150 1.3×	74 0.8×	56 1.1×	46 0.9×	9	418
Mustafa Yıldız Türkiye	11	183 0.7×	70 0.6×	74 0.8×	43 0.8×	28 0.5×	22	360
Rick Barto United States	6	285 1.1×	101 0.9×	137 1.5×	47 0.9×	25 0.5×	7	478
Daylond Hooper United States	7	382 1.5×	130 1.1×	104 1.1×	68 1.3×	22 0.4×	13	581
Max C. Gallant United States	4	317 1.2×	83 0.7×	119 1.3×	47 0.9×	13 0.2×	8	505
Lili Bai China	11	191 0.7×	103 0.9×	105 1.1×	16 0.3×	83 1.6×	45	463
Yuki Kameya Japan	13	159 0.6×	138 1.2×	101 1.1×	27 0.5×	31 0.6×	38	619
Kevin Decker United States	5	259 1.0×	88 0.8×	64 0.7×	53 1.0×	12 0.2×	11	363
David Milsted United States	4	285 1.1×	89 0.8×	105 1.1×	46 0.9×	12 0.2×	6	481
Xiaoli Huang China	12	270 1.0×	76 0.7×	108 1.2×	49 0.9×	106 2.0×	43	609

Countries citing papers authored by Daniil Bash

Since Specialization

Citations

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

Fields of papers citing papers by Daniil Bash

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniil Bash

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

All Works

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10 of 10 papers shown

Bash, Daniil, Tan Huang, Tianqi Deng, et al.. (2024). Machine learning based feature engineering for thermoelectric materials by design. Digital Discovery. 3(1). 210–220. 17 indexed citations

Tian, Siyu, Zekun Ren, Selvaraj Venkataraj, et al.. (2024). Correction: Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films. Digital Discovery. 3(5). 1068–1068.

Tian, Siyu, Zekun Ren, Selvaraj Venkataraj, et al.. (2023). Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films. Digital Discovery. 2(5). 1334–1346. 6 indexed citations

Soh, Beatrice W., et al.. (2023). Automated pipetting robot for proxy high-throughput viscometry of Newtonian fluids. Digital Discovery. 2(2). 481–488. 7 indexed citations

Tian, Siyu, Zhe Liu, Selvaraj Venkataraj, et al.. (2022). Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization. PLoS ONE. 17(11). e0276555–e0276555. 2 indexed citations

Bash, Daniil, Zekun Ren, Jayce Jian Wei Cheng, et al.. (2022). Accelerated automated screening of viscous graphene suspensions with various surfactants for optimal electrical conductivity. Digital Discovery. 1(2). 139–146. 9 indexed citations

Mekki‐Berrada, Flore, Zekun Ren, Tan Huang, et al.. (2021). Two-step machine learning enables optimized nanoparticle synthesis. npj Computational Materials. 7(1). 174 indexed citations

Bash, Daniil, Vijila Chellappan, Swee Liang Wong, et al.. (2021). Multi‐Fidelity High‐Throughput Optimization of Electrical Conductivity in P3HT‐CNT Composites. Advanced Functional Materials. 31(36). 34 indexed citations

Liang, Qiaohao, Aldair E. Gongora, Zekun Ren, et al.. (2021). Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains. npj Computational Materials. 7(1). 124 indexed citations

10.

Suwardi, Ady, Daniil Bash, Hong Kuan Ng, et al.. (2019). Inertial effective mass as an effective descriptor for thermoelectrics via data-driven evaluation. Journal of Materials Chemistry A. 7(41). 23762–23769. 56 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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