Yaser Mohammadi | Agricultural sustainability | Best Researcher Award

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Dr. Yaser Mohammadi | Agricultural Sustainability | Best Researcher Award

Faculty Memeber | Bu-Ali Sina University | Iran

Dr. Yaser Mohammadi is an Associate Professor at Bu-Ali Sina University, specializing in agricultural sustainability. He holds advanced degrees in agriculture with a focus on sustainable development and environmental behavior. With extensive academic and international experience, he has served as a faculty member and contributed as a Research Assistant at the Agricultural Sustainability Institute at the University of California, Davis, where he collaborated on a major project funded by Nestlé focused on sustainable raw material sourcing. Dr. Mohammadi has led and participated in multiple national and international research and consultancy projects related to pro-environmental behavior, sustainable agribusiness, climate change adaptation, and greenhouse farming. His scholarly output includes over 20 peer-reviewed publications in high-impact journals such as Environmental Management and Land Use Policy, as well as two authored books. He regularly contributes as a peer reviewer for Elsevier journals and serves on the scientific editorial board of the Annual Agricultural Extension and Education Conference at Bu-Ali Sina University. He has collaborated with key Iranian agricultural institutions, including the Agricultural Jihad Organization and the Rural Cooperative Organization, to deliver applied research and policy solutions aimed at enhancing energy efficiency, reducing greenhouse gas emissions, and advancing climate-resilient agriculture. In recognition of his contributions, he was awarded Best Researcher at Bu-Ali Sina University. His research has achieved measurable academic impact, with 325 citations by 315 documents, 20 published documents, and an h-index of 10, demonstrating the depth and reach of his scholarly work.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Avatefi Akmal, F., & Mohammadi, Y. (2025). The nexus of agricultural land use change and food security: A comprehensive systematic review. Land Use Policy, 128, 107717.

2. Jalilian, N., Mohammadi, Y., Naderi Mahdei, K., Nael, M., & Neaman, A. (2025). Land ownership rights enhance farmers’ attitudes toward soil and soil conservation behavior: Insights from Iran. Journal of Environmental Management, 349, 126821.

3. Gholami Jalal, S., Karimi, S., Mohammadi, Y., Yaghoubi Farani, A., & Liobikienė, G. (2025). Developing and prioritizing strategies for sustainable greenhouse agribusiness: A case study in Hamedan Province, Iran. Sustainability, 17(11), 4912.

4. Gholami Jalal, S., Karimi, S., Mohammadi, Y., & Yaghoubi Farani, A. (2024). A framework for identifying and validating indicators to assess agribusiness sustainability: An emphasis on greenhouses in Iran. Agribusiness, 40(1), 141–160.

5. Razzaghi Borkhani, F., Khaleghi, B., Mirtorabi, M. S., & Mohammadi, Y. (2023). Explaining farmers’ pro-environmental behaviors toward plant, soil and water conservation in Iran: An application of value–belief–norm theory. International Journal of Environmental Science and Technology, 20, 2461–2474.

Anubhava Srivastava | Ecosystem | Best Researcher Award

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Dr. Anubhava Srivastava | Ecosystem | Best Researcher Award

Assistant Professor at Sharda University, India

Dr. Anubhava Srivastava is an accomplished academic and researcher in Computer Science, currently serving as Assistant Professor at Sharda University. With a Ph.D. from RGIPT, Jais, his research bridges artificial intelligence, machine learning, geoinformatics, and remote sensing. His innovative doctoral thesis focused on LU/LC mapping and classification using AI/ML on Google Earth Engine. Dr. Srivastava’s academic journey reflects a strong commitment to interdisciplinary applications of data science, from precision agriculture to environmental monitoring. He has published extensively in SCI/Scopus journals and international conferences, authored book chapters with Springer and Elsevier, and holds patents related to IoT applications. A GATE qualifier, he has also completed numerous professional certifications through Coursera. With an H-index of 9 (Google Scholar), his work is well-cited and widely recognized. Passionate about sustainability and digital innovation, Dr. Srivastava’s contributions make him a leading voice in AI-driven geospatial solutions for real-world problems.

Professional Profiles📖

Scopus 

ORCID 

Google Scholar

🎓 Education 

Dr. Srivastava holds a Ph.D. in Computer Science from Rajiv Gandhi Institute of Petroleum Technology (RGIPT), Jais, completed in 2023 with a CPI of 8.67. His doctoral thesis focused on LU/LC classification using AI/ML techniques and Google Earth Engine. He earned his M.Tech in Computer Science and Engineering from Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow, in 2015,  Prior to that, he completed his B.Tech in Computer Science in 2012 with 71.84%. His early education includes a Higher Secondary Certificate (57.60%) and a Secondary Certificate (71.32%) from GIC Sultanpur. His academic training spans critical subjects such as database systems, machine learning, artificial intelligence, and remote sensing algorithms. Dr. Srivastava’s educational background is a blend of foundational computer science and advanced AI-geoinformatics, equipping him to tackle complex, data-driven challenges in environmental science, spatial computing, and smart systems.

🏗 Experience 

Dr. Srivastava has over 9 years of academic experience. He currently serves as an Assistant Professor at Sharda University, Greater Noida (since May 2023), in the Department of Computer Science. Prior to that, he was with Noida Institute of Engineering and Technology (2022–2023) and Rajarshi Rananjay Sinh Institute of Management & Technology, Amethi (2015–2022). His responsibilities have included mentoring postgraduate and undergraduate students, supervising research projects, and teaching cutting-edge courses in AI, machine learning, remote sensing, and databases. Dr. Srivastava has also guided students in developing projects using Google Earth Engine, satellite data, and real-time geospatial analytics. His teaching philosophy emphasizes practical application, data literacy, and sustainability. His contributions extend beyond academics through research collaborations, IEEE conference participation, and involvement in AI-based solutions for socio-economic development and smart agriculture. His interdisciplinary experience bridges academia, technology, and field-based environmental intelligence.

🏆 Awards & Honors 

Dr. Srivastava has made significant strides in both academia and applied research. His design patents—on RFID-based animal tracking and irrigation water supply management—highlight his innovation in IoT for environmental and agricultural applications. He has earned repeated recognition through his publications in high-impact SCI and Scopus journals such as Science of the Total Environment and Applied System Innovation. With an H-index of 9 on Google Scholar and 8 on Scopus, his scholarly work on AI, remote sensing, and GIS is widely cited. He has qualified the prestigious GATE exam thrice (2013, 2016, 2017). Dr. Srivastava’s work has been presented in multiple IEEE and Springer conferences, showcasing his leadership in AI-powered geospatial research. He also contributed chapters to international volumes with Elsevier, CRC Press, and Springer. His recognition as a thought leader in environmental computation, digital literacy, and rural innovation places him among promising young researchers in India.

🔬 Research Focus

Dr. Anubhava Srivastava’s research lies at the intersection of Artificial Intelligence, remote sensing, environmental monitoring, and geospatial data analytics. His Ph.D. work involved LU/LC classification and environmental change detection using AI/ML techniques over Google Earth Engine. He focuses on developing intelligent systems that analyze temporal and spatial patterns of land, forest, and urban landscapes. His recent publications address critical challenges such as forest degradation, fire detection, and digital literacy through geoinformatics. His research integrates NDVI, vegetation indices, satellite image classification, and climate change modeling using Sentinel-2 and Landsat datasets. Beyond environmental domains, his contributions also include cybersecurity in P2P networks, real-time earthquake monitoring, and structural health analysis using 3D point clouds. Through interdisciplinary collaboration, he aims to support SDGs by designing AI-based frameworks that enable informed policymaking, sustainable agriculture, and urban resilience. His long-term goal is to expand geospatial intelligence applications through ethical and scalable AI innovations.

🛠 Skills 

Dr. Srivastava brings a comprehensive skillset in artificial intelligence, machine learning, deep learning, and remote sensing. He is proficient in using Google Earth Engine, Python, MATLAB, and GIS tools for environmental data modeling and visualization. His technical expertise includes supervised and unsupervised classification algorithms, NDVI-based analysis, satellite data processing, API integration, and cloud-native development. He is also adept in computer networks, particularly P2P security protocols, demonstrated in his M.Tech thesis and conference papers. He has authored secure overlays like Heal Gossip and FCCC for environmental and communication systems. Dr. Srivastava’s coursework and certifications from Coursera further validate his mastery in web development, AI, GIS mapping, and cloud computing. His interpersonal and academic skills include research mentorship, technical writing, and effective presentation in reputed conferences. He actively collaborates across disciplines, enhancing his role as a researcher, mentor, and digital innovation advocate.

Publications Top Notes

Review of structural health monitoring techniques in pipeline and wind turbine industries

Authors: VB Sharma, K Singh, R Gupta, A Joshi, R Dubey, V Gupta, S Bharadwaj, A Srivastava

Citations: 44

Year: 2021

Mapping vegetation and measuring the performance of machine learning algorithm in LULC classification in the large area using Sentinel-2 and Landsat-8 datasets of Dehradun

Authors: A Srivastava, S Bharadwaj, R Dubey, VB Sharma, S Biswas

Citations: 35

Year: 2022

Exploring forest transformation by analyzing spatial-temporal attributes of vegetation using vegetation indices

Authors: A Srivastava, S Umrao, S Biswas

Citations: 18

Year: 2023

A probabilistic Gossip-based secure protocol for unstructured P2P networks

Authors: A Srivastava, P Ahmad

Citations: 18

Year: 2016

Determination of optimal location for setting up cell phone tower in city environment using LiDAR data

Authors: S Bharadwaj, R Dubey, MI Zafar, A Srivastava, VB Sharma, V Bhushan

Citations: 16

Year: 2020

Analyzing land cover changes over Landsat-7 data using Google Earth Engine

Authors: A Srivastava, S Biswas

Citations: 14

Year: 2023

GIS mapping of short-term noisy event of Diwali night in Lucknow city

Authors: R Dubey, S Bharadwaj, MI Zafar, V Mahajan, A Srivastava, S Biswas

Citations: 14

Year: 2022

Comparison of Sentinel and Landsat datasets over Lucknow region using gradient tree boost supervised classifier

Authors: A Srivastava, R Dubey, S Biswas

Citations: 13

Year: 2023

FCCC: Forest cover change calculator user interface for identifying fire incidents in forest region using satellite data

Authors: A Srivastava, S Umrao, S Biswas, R Dubey, MI Zafar

Citations: 11

Year: 2023

GIS based road traffic noise mapping and assessment of health hazards for a developing urban intersection

Authors: MI Zafar, R Dubey, S Bharadwaj, A Kumar, KK Paswan, A Srivastava

Citations: 9

Year: 2023

AI-driven environmental monitoring using Google Earth Engine

Authors: A Srivastava, H Sharma

Citations: 5

Year: 2024

A method for extracting deformation features from terrestrial laser scanner 3D point clouds data in RGIPT building

Authors: VB Sharma, R Dubey, A Bhatt, S Bharadwaj, A Srivastava, S Biswas

Citations: 4

Year: 2022

Conclusion✅