Alireza Sharifi | Crop yield prediction | Best Researcher Award

Published on by Cell Biologist

Assoc Prof Dr Alireza Sharifi |  Crop yield prediction |  Best Researcher Award

Dr at  Shahid Rajaee Teacher Training, Iran

Dr. Alireza Sharifi is an Associate Professor at Shahid Rajaee Teacher Training University, specializing in geosciences and remote sensing applications for Precision Agriculture. He obtained his graduate degree from the University of Tehran and has focused his research on Earth Observation Programs, particularly using satellite imagery. Dr. Sharifi has led multiple research projects funded by prestigious organizations such as the National Natural Science Foundation of China, contributing significantly to the fields of hyperspectral image classification, crop mapping, and vegetation monitoring. With numerous publications and a strong academic background, he continues to advance innovative approaches in agricultural sustainability through technology.

Profile:

📚 Academic Background:

Dr. Alireza Sharifi graduated from the University of Tehran with expertise in geosciences and remote sensing applications, focusing on Earth Observation Programs for Precision Agriculture using satellite imagery.

🔍 Research Focus:

His research spans various projects, including hyperspectral image classification, spatio-temporal analysis of forest fires, and integration of satellite images for crop mapping. He has published extensively in reputed journals and holds multiple editorial appointments.

📊 Citations:

  • Citations: 1970 (1878 since 2019)
  • h-index: 28 (since 2019)
  • i10-index: 40 (since 2019)
📄 Publication:

1. Comparison the accuracies of different spectral indices for estimation of vegetation cover fraction in sparse vegetated areas
S Barati, B Rayegani, M Saati, A Sharifi, M Nasri
The Egyptian Journal of Remote Sensing and Space Science 14 (1), 49-56, 2011
Citations: 221

2. Hyperspectral image classification using a hybrid 3D-2D convolutional neural networks
S Ghaderizadeh, D Abbasi-Moghadam, A Sharifi, N Zhao, A Tariq
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Citations: 132

3. Yield prediction with machine learning algorithms and satellite images
A Sharifi
Journal of the Science of Food and Agriculture 101 (3), 891-896, 2021
Citations: 105

4. Spatio-temporal analysis of forest fire events in the Margalla Hills, Islamabad, Pakistan using socio-economic and environmental variable data with machine learning methods
A Tariq, H Shu, S Siddiqui, I Munir, A Sharifi, Q Li, L Lu
Journal of Forestry Research 33 (1), 183-194, 2022
Citations: 76

5. Crop type classification by DESIS hyperspectral imagery and machine learning algorithms
N Farmonov, K Amankulova, J Szatmári, A Sharifi, D Abbasi-Moghadam, …
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Citations: 62

6. Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models
SS Wahla, JH Kazmi, A Sharifi, SA Shirazi, A Tariq, H Joyell Smith
Geocarto International 37 (27), 14963-14982, 2022
Citations: 62

7. Multiscale dual-branch residual spectral–spatial network with attention for hyperspectral image classification
S Ghaderizadeh, D Abbasi-Moghadam, A Sharifi, A Tariq, S Qin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Citations: 60

8. Evaluation of vegetation indices and phenological metrics using time-series MODIS data for monitoring vegetation change in Punjab, Pakistan
P Hu, A Sharifi, MN Tahir, A Tariq, L Zhang, F Mumtaz, SHIA Shah
Water 13 (18), 2550, 2021
Citations: 59

9. Flash flood susceptibility assessment and zonation by integrating analytic hierarchy process and frequency ratio model with diverse spatial data
A Tariq, J Yan, B Ghaffar, S Qin, BG Mousa, A Sharifi, ME Huq, M Aslam
Water 14 (19), 3069, 2022
Citations: 57

10. Remote sensing satellite’s attitude control system: rapid performance sizing for passive scan imaging mode
A Kosari, A Sharifi, A Ahmadi, M Khoshsima
Aircraft Engineering and Aerospace Technology 92 (7), 1073-1083, 2020
Citations: 57

11. Flood mapping using relevance vector machine and SAR data: A case study from Aqqala, Iran
A Sharifi
Journal of the Indian Society of Remote Sensing 48 (9), 1289-1296, 2020
Citations: 55

12. Modeling and predicting land use land cover spatiotemporal changes: A case study in Chalus Watershed, Iran
S Jalayer, A Sharifi, D Abbasi-Moghadam, A Tariq, S Qin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Citations: 54

13. Integration of Sentinel 1 and Sentinel 2 satellite images for crop mapping
S Felegari, A Sharifi, K Moravej, M Amin, A Golchin, A Muzirafuti, A Tariq, …
Applied Sciences 11 (21), 10104, 2021
Citations: 54

14. Development of a method for flood detection based on Sentinel‐1 images and classifier algorithms
A Sharifi
Water and Environment Journal 35 (3), 924-929, 2021
Citations: 54

15. Estimation of forest biomass using multivariate relevance vector regression
A Sharifi, J Amini, R Tateishi
Photogrammetric Engineering & Remote Sensing 82 (1), 41-49, 2016
Citations: 54

16. Agro climatic zoning of saffron culture in Miyaneh city by using WLC method and remote sensing data
A Zamani, A Sharifi, S Felegari, A Tariq, N Zhao
Agriculture 12 (1), 118, 2022
Citations: 50

17. Forest biomass estimation using synthetic aperture radar polarimetric features
A Sharifi, J Amini
Journal of Applied Remote Sensing 9 (1), 097695-097695, 2015
Citations: 49

18. Remotely sensed vegetation indices for crop nutrition mapping
A Sharifi
Journal of the Science of Food and Agriculture 100 (14), 5191-5196, 2020
Citations: 47

19. Using Sentinel-2 data to predict nitrogen uptake in maize crop
A Sharifi
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Citations: 47

20. Speckle reduction of PolSAR images in forest regions using fast ICA algorithm
A Sharifi, J Amini, JT Sri Sumantyo, R Tateishi
Journal of the Indian Society of Remote Sensing 43, 339-346, 2015
Citations: 47

 

Ujjwal Layek | Pollination Biology | Best Researcher Award

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Dr Ujjwal Layek |  Pollination Biology |  Best Researcher Award

Assistant Professor at  Rampurhat College, India

Dr. Ujjwal Layek is an Assistant Professor of Botany at Rampurhat College, specializing in plant-pollinator interactions with a focus on palynology and pollination biology. He holds a Ph.D. from Vidyasagar University and completed his M.Sc. at Visva-Bharati, West Bengal. With over four years of experience in academia, he has authored over 35 publications in esteemed journals such as Elsevier, Springer Nature, and Wiley & Sons. Dr. Layek serves as an editorial board member for journals like Frontiers in Bee Science and Plant Science Today and has reviewed over 60 manuscripts for prestigious publishers including Nature Publishing Group and Elsevier. His research has garnered significant citation recognition, with an H-index of 13. Additionally, he has organized research conferences and workshops and actively collaborates with universities and industries. Dr. Layek’s contributions to research and development have earned him recognition, including an award, and he continues to make strides in advancing our understanding of plant reproductive biology and bee behavior.

Profile:

👨‍🎓 Education & Experience:

Dr. Ujjwal Layek holds a Ph.D. in Botany from Vidyasagar University, following his M.Sc. from Visva-Bharati. With over 4 years of teaching experience, he currently serves as an Assistant Professor at Rampurhat College, specializing in plant-pollinator interactions.

 

📚 Academic Contributions:

As an editorial board member of journals like Frontiers in Bee Science and Plant Science Today, he actively shapes scholarly discourse. Dr. Layek’s commitment to academia is evident through his review of over 60 manuscripts from renowned publishers like Nature Publishing Group and Springer Nature.

 

🌍 Global Impact:

Dr. Layek’s work has garnered international recognition, with publications indexed in SCI, SCIE, Scopus, and PubMed. He has engaged in over 20 collaborative research activities and presented his findings in numerous conferences worldwide.

🔬 Research Focus: Pollination Biology

 

Dr. Ujjwal Layek, an Assistant Professor of Botany at Rampurhat College, specializes in the intricate world of pollination biology. His research delves into the crucial interactions between plants and pollinators, exploring the mechanisms and dynamics that drive successful pollination processes.

🌼 Plant-Pollinator Interactions: Dr. Layek investigates the fascinating relationships between flowering plants and their pollinators, unraveling the complexities of co-evolution and mutual dependencies.

🔍 Palynology Expertise: With a focus on palynology, Dr. Layek examines pollen grains and their role in plant reproduction, shedding light on pollen morphology, dispersal, and its implications for pollination efficiency.

🐝 Foraging Behavior of Pollinators: Understanding the foraging behavior of pollinators like honeybees and stingless bees is central to Dr. Layek’s research. He explores how these vital agents navigate floral landscapes, impacting plant reproductive success.

🌍 Environmental Impact: Dr. Layek’s work not only advances scientific knowledge but also highlights the ecological importance of pollination in maintaining biodiversity and ecosystem stability.

Citations:

Dr. Ujjwal Layek’s contributions to the field of pollination biology have garnered significant attention, with 360 citations overall and 339 citations since 2019. His work has established an h-index of 13 and an i10-index of 15, reflecting the impact and influence of his research in advancing our understanding of plant-pollinator interactions.

Publication Top Notes:

  • “Nesting characteristics, floral resources, and foraging activity of Trigona iridipennis Smith in Bankura district of West Bengal, India”
    • Authors: U Layek, P Karmakar
    • Published in: Insectes sociaux
    • Year: 2018
    • Citations: 41
  • “Impact of managed stingless bee and western honey bee colonies on native pollinators and yield of watermelon: A comparative study”
    • Authors: U Layek, A Kundu, S Bisui, P Karmakar
    • Published in: Annals of Agricultural Sciences
    • Year: 2021
    • Citations: 36
  • “Pollen foraging behaviour of honey bee (Apis mellifera L.) in southern West Bengal, India”
    • Authors: U Layek, SS Manna, P Karmakar
    • Published in: Palynology
    • Year: 2020
    • Citations: 25
  • “Honey sample collection methods influence pollen composition in determining true nectar-foraging bee plants”
    • Authors: U Layek, R Mondal, P Karmakar
    • Published in: Acta Botanica Brasilica
    • Year: 2020
    • Citations: 24
  • “Comparing the pollen forage pattern of stingless bee (Trigona iridipennis Smith) between rural and semi-urban areas of West Bengal, India”
    • Authors: S Bisui, U Layek, P Karmakar
    • Published in: Journal of Asia-Pacific Entomology
    • Year: 2019
    • Citations: 23
  • “Bee plants used as nectar sources by Apis florea Fabricius in Bankura and Paschim Medinipur districts, West Bengal”
    • Authors: U Layek, P Karmakar
    • Published in: Geophytology
    • Year: 2016
    • Citations: 21

 

Liang He | Agronomy | Best Researcher Award

Published on by Cell Biologist

Prof Liang He | Agronomy | Best Researcher Award

dean at  Xinjiang university, China

Dr. He Liang, born in December 1981, is a distinguished professor and serves as the Executive Vice Dean of the School of Computer Science and Technology, as well as the Dean of the School of Intelligence Science and Technology at Xinjiang University. He holds a Ph.D. in Artificial Intelligence and specializes in temporal sequence signal processing, knowledge graphs, and reinforcement learning.

Profile:

Educational Background:

  • Qualification: PhD
  • Specialization: Artificial Intelligence
  • Sub-Division: Knowledge Graphs, Reinforcement Learning

Professional Experience and Achievements:

Dr. He Liang serves as the Executive Vice Dean of the School of Computer Science and Technology and Dean of the School of Intelligence and Science and Technology at Xinjiang University. With a focus on temporal sequence signal processing, knowledge graphs, and reinforcement learning, he has led over 20 scientific research projects and published over 100 academic papers in prestigious journals and conferences, including Nature Communication, IEEE Trans on ASLP, and ICASSP.

He is a well-regarded reviewer for several international journals and conferences such as IEEE Audio, Speech and Language Processing, and Pattern Recognition. Dr. Liang’s contributions to research have earned him over 1000 citations in Scopus/Web of Science.

Research and Development Contributions:

Dr. Liang has made significant contributions to the study of drought stress resistance in cotton plants, exploring optimal irrigation methods to improve yield and conserve water. His research has shown a strong correlation between deficit irrigation and improved cotton yield, leading to optimized irrigation schemes that benefit local agriculture.

Agronomy Research Focus:

Dr. He Liang has directed a significant portion of his research towards addressing agronomic challenges, particularly in the context of arid regions. His work primarily focuses on optimizing agricultural practices through advanced data-driven methodologies and artificial intelligence.

Citations:

  • H-Index: 25 (Total), 24 (Since 2019)
  • i10-Index: 66 (Total), 61 (Since 2019)
  • Total Citations: 2352 (Total), 1836 (Since 2019)

 

Publication Top Notes:

  • Applications of Chemical Vapor Generation in Non-Tetrahydroborate Media to Analytical Atomic Spectrometry
    • Year: 2010
    • Citations: 202
  • Large Margin Softmax Loss for Speaker Verification
    • Year: 2019
    • Citations: 163
  • The Trans-Omics Landscape of COVID-19
    • Year: 2021
    • Citations: 88
  • Speaker Embedding Extraction with Phonetic Information
    • Year: 2018
    • Citations: 77
  • Evaluation of Tungsten Coil Electrothermal Vaporization-Ar/H2 Flame Atomic Fluorescence Spectrometry for Determination of Eight Traditional Hydride-Forming Elements and Cadmium
    • Year: 2008
    • Citations: 55
  • Dynamics and Correlation Among Viral Positivity, Seroconversion, and Disease Severity in COVID-19: A Retrospective Study
    • Year: 2021
    • Citations: 53
  • Enhance Prototypical Network with Text Descriptions for Few-Shot Relation Classification
    • Year: 2020
    • Citations: 53
  • Simultaneous Utilization of Spectral Magnitude and Phase Information to Extract Supervectors for Speaker Verification Anti-Spoofing
    • Year: 2015
    • Citations: 52