Md Yeasin

702 total citations
71 papers, 344 citations indexed

About

Md Yeasin is a scholar working on Plant Science, Soil Science and Management Science and Operations Research. According to data from OpenAlex, Md Yeasin has authored 71 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Plant Science, 13 papers in Soil Science and 11 papers in Management Science and Operations Research. Recurrent topics in Md Yeasin's work include Stock Market Forecasting Methods (10 papers), Soil Carbon and Nitrogen Dynamics (8 papers) and Market Dynamics and Volatility (7 papers). Md Yeasin is often cited by papers focused on Stock Market Forecasting Methods (10 papers), Soil Carbon and Nitrogen Dynamics (8 papers) and Market Dynamics and Volatility (7 papers). Md Yeasin collaborates with scholars based in India, United States and Saudi Arabia. Md Yeasin's co-authors include Ranjit Kumar Paul, A. K. Paul, Tanmoy Karak, Pramod Kumar, Ajit Gupta, Jyotirekha G. Handique, Jiban Saikia, Puja Khare, Owais Ali Wani and Shamal Shasang Kumar and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Md Yeasin

53 papers receiving 336 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Md Yeasin India 10 77 66 51 47 47 71 344
Xianghua Wu China 9 177 2.3× 54 0.8× 75 1.5× 75 1.6× 84 1.8× 16 419
Liana E. Pozza Australia 8 180 2.3× 223 3.4× 20 0.4× 82 1.7× 44 0.9× 14 643
Mert Dedeoğlu Türkiye 9 73 0.9× 148 2.2× 36 0.7× 137 2.9× 55 1.2× 32 408
Qiting Chen China 11 43 0.6× 52 0.8× 24 0.5× 22 0.5× 119 2.5× 30 281
Muhammad Waqas Thailand 12 40 0.5× 146 2.2× 14 0.3× 51 1.1× 154 3.3× 34 490
Daniel B. Taylor United States 12 47 0.6× 17 0.3× 17 0.3× 88 1.9× 25 0.5× 34 362
Andres M. Ticlavilca United States 11 111 1.4× 197 3.0× 12 0.2× 26 0.6× 150 3.2× 16 433
Jiancang Xie China 10 46 0.6× 50 0.8× 5 0.1× 77 1.6× 33 0.7× 23 368

Countries citing papers authored by Md Yeasin

Since Specialization
Citations

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

Fields of papers citing papers by Md Yeasin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Md Yeasin

This figure shows the co-authorship network connecting the top 25 collaborators of Md Yeasin. A scholar is included among the top collaborators of Md Yeasin 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 Md Yeasin. Md Yeasin 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.
2.
Upadhyay, Pravin Kumar, Kapila Shekhawat, Sanjay Singh Rathore, et al.. (2025). An insight into productivity, profitability, and sustainable energy use in maize under precision nitrogen management using a smartphone app. Information Processing in Agriculture. 13(1). 26–46. 1 indexed citations
3.
Sasi, Minnu, Sandeep Kumar, Md Yeasin, et al.. (2025). Optimizing single and co-culture soymilk fermentation using weissella probiotics for improved nutritional and sensory quality. Food Bioscience. 69. 106791–106791.
4.
Babu, Subhash, Sanjay Singh Rathore, Pravin Kumar Upadhyay, et al.. (2025). Designing sustainable agricultural production model: Balancing food, economy, and environmental outcomes in humid subtropics. Cleaner Engineering and Technology. 27. 101016–101016. 2 indexed citations
5.
Hasan, Murtaza, et al.. (2025). Design, Development and Testing of an IoT‐Based Smart Vertical Hydroponic System for Optimized Nutrient Management in a Controlled Environment. Irrigation and Drainage. 74(5). 1904–1920. 2 indexed citations
6.
Yeasin, Md, et al.. (2024). Ensemble machine learning models for forecasting tropical cyclones in North Indian region. Earth Science Informatics. 17(4). 3705–3714.
7.
Paul, Ranjit Kumar, et al.. (2024). CEEMDAN-Based Hybrid Machine Learning Models for Time Series Forecasting Using MARS Algorithm and PSO-Optimization. Neural Processing Letters. 56(2). 5 indexed citations
8.
Yeasin, Md, et al.. (2024). IFNN: Intuitionistic Fuzzy Logic Based Neural Network Model for Time Series Forecasting. National Academy Science Letters. 48(5). 579–584. 1 indexed citations
9.
Wani, Owais Ali, Syed Sheraz Mahdi, Md Yeasin, et al.. (2024). Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas. Scientific Reports. 14(1). 27876–27876. 16 indexed citations
10.
Yeasin, Md, et al.. (2024). WaveFLSTM: Wavelet-based fuzzy LSTM model for forecasting complex time series data. Neural Computing and Applications. 37(17). 10707–10721. 2 indexed citations
11.
Yeasin, Md, et al.. (2023). MethSemble-6mA: an ensemble-based 6mA prediction server and its application on promoter region of LBD gene family in Poaceae. Frontiers in Plant Science. 14. 1256186–1256186. 1 indexed citations
12.
Paul, Ranjit Kumar, et al.. (2023). An MRA Based MLR Model for Forecasting Indian Annual Rainfall Using Large Scale Climate Indices. International Journal of Environment and Climate Change. 13(5). 137–150. 4 indexed citations
13.
Sengupta, Suparna, et al.. (2023). Assessment and health risk of fluoride from Northeast Indian tea (Camellia sinensis L.): Fixing up the maximum residue level of fluoride in tea. Journal of Food Composition and Analysis. 127. 105928–105928. 6 indexed citations
14.
Wani, Owais Ali, Vikas Sharma, Shamal Shasang Kumar, et al.. (2023). Climate plays a dominant role over land management in governing soil carbon dynamics in North Western Himalayas. Journal of Environmental Management. 338. 117740–117740. 15 indexed citations
15.
Handique, Jyotirekha G., Ranjit Kumar Paul, Md Yeasin, et al.. (2023). Can tea pruning litter biochar be a friend or foe for tea (Camellia sinensis L.) plants' growth and growth regulators?: Feasible or fumes of fancy. Industrial Crops and Products. 195. 116394–116394. 12 indexed citations
16.
Paul, Ranjit Kumar, et al.. (2023). Wavelets in Combination with Stochastic and Machine Learning Models to Predict Agricultural Prices. Mathematics. 11(13). 2896–2896. 11 indexed citations
17.
Paul, Ranjit Kumar, et al.. (2023). Deep Learning Technique for Forecasting the Price of Cauliflower. Current Science. 124(9). 1065–1065. 2 indexed citations
18.
Yadav, Brijesh Kumar, Lal Chand Malav, Md Yeasin, et al.. (2023). Spatiotemporal Responses of Vegetation to Hydroclimatic Factors over Arid and Semi-arid Climate. Sustainability. 15(21). 15191–15191. 5 indexed citations
19.
Paul, Ranjit Kumar, et al.. (2023). Ensemble of Time Series and Machine Learning Model for Forecasting Volatility in Agricultural Prices. National Academy Science Letters. 46(3). 185–188. 6 indexed citations
20.
Paul, Ranjit Kumar, et al.. (2023). Modeling Asymmetric Volatility: A News Impact Curve Approach. Mathematics. 11(13). 2793–2793. 3 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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