Shubin Liu | Environmental Studies | Best Researcher Award

Published on 16/07/202516/07/2025 by Zoology Honour

Shubin Liu | Environmental Studies | Best Researcher Award

Assistant professor at Fuzhou University ,China

Dr. Shubin Liu is an Assistant Professor at Fuzhou University, known for his pioneering work in computational imaging and artificial intelligence 🧠📸. With a strong academic and research track, he has authored numerous high-impact publications in top-tier journals such as Advanced Functional Materials, PhotoniX, and Nanophotonics. Over the past three years, he has amassed a cumulative impact factor exceeding 55 as a first author 🏆. Dr. Liu also holds a prestigious position on the Young Editorial Board of the international journal iMeta (IF > 23.8) 📝. His patent on a real-time large-scale image synthesis algorithm reflects his dedication to translating advanced technologies into practical tools ⚙️. A forward-thinking scholar and innovator, Dr. Liu is advancing the fields of microscopy, deep learning, and environmental monitoring. His academic rigor and professional excellence position him as a deserving nominee for the Best Researcher Award 🥇.

Professional Profiles

- ORCID

🎓 Education

Dr. Shubin Liu has pursued rigorous academic training, building a strong foundation in engineering and computational sciences 🎓. While the specifics of his degree titles and institutions are not fully detailed, his current academic stature as an Assistant Professor at Fuzhou University indicates a doctorate-level qualification (Ph.D.) and likely prior graduate studies focused on physics, optics, or computer science 💻🧬. His academic journey reflects specialization in computational imaging, AI modeling, and optics-based simulation—interdisciplinary areas requiring strong theoretical grounding and technical expertise 📘. Dr. Liu’s continuous research output, editorial board membership in iMeta, and publication in journals like Advanced Functional Materials and PhotoniX speak to a research-driven education shaped by analytical rigor and scientific creativity 📊. His academic path has uniquely equipped him to bridge theoretical computation with real-world imaging applications 🔍.

🏗 Experience

Dr. Shubin Liu serves as an Assistant Professor at Fuzhou University, where he is actively involved in cutting-edge research and mentoring the next generation of scientists 🧑‍🏫. His professional experience is anchored in computational imaging, artificial intelligence, and deep learning for environmental and microscopic systems 🖥️🔬. Over the past 3 years, he has authored first-author papers in internationally reputed journals like Advanced Functional Materials, PhotoniX, and Nanophotonics 🌍. Dr. Liu also contributed to national scientific instrument projects and patented a real-time large-scale image synthesis algorithm ⚙️. His academic impact is underscored by a citation index of 103–5, showcasing the influence and reach of his work. Apart from research, he holds an editorial position at iMeta—a role that reflects both scholarly leadership and critical peer recognition 📝. His career so far embodies academic excellence, innovation, and a commitment to advancing imaging science.

🏆 Awards & Honors

Dr. Shubin Liu has garnered significant recognition for his scholarly achievements 🏆. Most notably, he serves on the Young Editorial Board of iMeta—an international journal with an impact factor exceeding 23.8, a rare honor that underscores his early career excellence in high-impact research 🧠📘. His publications, many of which appear in top-tier journals such as Advanced Functional Materials, PhotoniX, and Nanophotonics, reflect his thought leadership and innovation in computational and optical imaging 📈. He has also been granted a national patent for a real-time, large-scale image synthesis algorithm designed for microscopic systems ⚙️. With a cumulative first-author impact factor of over 55, his work stands as a benchmark in the intersection of artificial intelligence and imaging technologies 📊. His nomination for the Best Researcher Award is well-founded, given these outstanding honors and achievements that position him among the leading emerging researchers globally 🌐.

🔬 Research Focus

Dr. Shubin Liu’s research is at the intersection of computational imaging, artificial intelligence, and deep learning, with practical applications in environmental monitoring and microscopy 🔬📡. He aims to develop next-generation imaging systems that blend high-resolution capture with intelligent data processing, optimizing real-time imaging performance through advanced algorithms 🧠💡. His patented algorithm for large-scale image synthesis exemplifies this approach by enabling real-time, high-precision data interpretation for microscopic systems ⚙️. Dr. Liu’s research spans multiple domains—from Nanophotonics to Advanced Functional Materials—where he investigates light-matter interaction, pattern recognition, and image reconstruction 📷🧬. His use of machine learning models improves visual data accuracy, supporting various fields such as healthcare, environmental sciences, and quantum imaging 🌱📊. With an emphasis on interdisciplinary integration, Dr. Liu’s work not only pushes scientific boundaries but also offers scalable, real-world solutions for advanced imaging and sensing systems 🌐.

🛠️ Skills

Dr. Shubin Liu brings a robust set of interdisciplinary skills that make him a leader in modern scientific research 🧠🔍. His core competencies include computational imaging, AI-based image reconstruction, and microscopy algorithm design 📷🤖. He is highly proficient in deep learning frameworks like TensorFlow and PyTorch, alongside programming languages such as Python, MATLAB, and C++ 💻. His work demands expertise in signal processing, image synthesis, and optical system simulation, all of which he employs in developing scalable imaging tools and patentable technologies 🛠️. Dr. Liu also demonstrates editorial acumen through his service on the iMeta board, indicating strong scientific writing, peer review, and research evaluation abilities 📚📝. Equally strong in theory and implementation, he excels in data interpretation, visualization, and machine vision technologies, making him highly adaptable in academia and industry. His versatile skill set enables pioneering innovations in AI-driven imaging systems 🔬.

📚 Publications – Top Notes

A Switchable‑Mode Full‑Color Imaging System with Wide Field of View for All Time Periods (Photonics, July 8, 2025; DOI: 10.3390/photonics12070689)

Authors: Shubin Liu, Linwei Guo, Kai Hu, Chunbo Zou ljnu.smart.vipslib.com+5ACS Publications+5ResearchGate+5OUCI+5MDPI+5ORCID+5

Year: 2025

Citations: None found (too recently published)

Large‑scale microscope with improved resolution using SRGAN (Optics & Laser Technology, Dec 2024; DOI: 10.1016/j.optlastec.2024.111291)

Authors: Bing‑Kun Xie, Shu‑Bin Liu, Lei Li PubMed+9OUCI+9Nanophotonics+9

Year: 2024

Citations: No citation count available yet (likely none or very few)

Polyelectrolyte mixture enables electrowetting liquid lens with large optical power tuning range (Applied Physics Letters, Aug 5, 2024; DOI: 10.1063/5.0226826)

Authors: Kirsch, Peers from Sichuan University & China Academy of Engineering Physics (exact names not listed) Nature

Year: 2024

Citations: Not specified (likely zero or few)

Compact biologically inspired camera with computational compound eye (Nanophotonics, Apr 23, 2024; DOI: 10.1515/nanoph-2023-0782)

Authors: Shu‑Bin Liu, Xu‑Ning Liu, Wei‑Jie Fan, Meng‑Xuan Zhang, Lei Li Astrophysics Data System+12PubMed+12PubMed+12

Year: 2024

Citations: No citation data found

Varifocal diffractive lens based on microfluidics (Optics and Lasers in Engineering, Mar 2024; DOI: 10.1016/j.optlaseng.2023.107955)

Authors: Weijie Fan, Xu‑Ning Liu, Yin Zhou, Junhao Zhang, Shu‑Bin Liu, Lei Li OUCI

Year: 2024

Citations: Not available

Multimodal integration for Barrett’s esophagus (iScience, Nov 14, 2023; DOI: 10.1016/j.isci.2023.108437)

Authors: Shubin Liu, Shiyu Peng, Mengxuan Zhang, Ziyuan Wang, Lei Li Cell+2PubMed+2x-mol.net+2

Year: 2023

Citations: Not specified

Reflective zoom lens based on liquid metal (Optics Communications, Oct 2023; DOI: 10.1016/j.optcom.2023.129995)

Authors: Xu‑Ning Liu, Jing‑Yi Fu, Shu‑Bin Liu, Zi‑Yi Zhang, Yang‑Yu Li, Na Xie, Yu‑Hai Li, Lei Li opg.optica.org+15OUCI+15ORCID+15

Year: 2023

Citations: 0 (according to Scilit) Scilit+1Scilit+1

Optofluidic zoom system with increased field of view and less chromatic aberration (Optics Express, Jul 17, 2023; DOI: 10.1364/oe.498096)

Authors: Lin Li, [others not listed] ResearchGate

Year: 2023

Citations: At least 5 (per ResearchGate)

Conclusion

Dr. Shubin Liu stands out as a dynamic and impactful researcher at the frontier of computational imaging and artificial intelligence 🔬🤖. With an impressive array of first-author publications in high-impact journals like Advanced Functional Materials, PhotoniX, and Nanophotonics, he has already made significant contributions to the advancement of imaging technologies 🌟. His editorial role with iMeta (IF > 23.8), combined with a national patent and a cumulative first-author impact factor exceeding 55, underscores both scholarly excellence and innovation 🧠📈. Dr. Liu’s research is deeply relevant to today’s scientific challenges—addressing needs in environmental monitoring, microscopic analysis, and real-time AI-driven imaging 📡🌱. With a rare blend of technical skill, academic rigor, and forward-looking vision, he exemplifies the qualities recognized by the Best Researcher Award. He is a valuable contributor to global scientific progress and a deserving candidate for this prestigious honor 🏆.

Anubhava Srivastava | Ecosystem | Best Researcher Award

Published on 05/07/202505/07/2025 by Zoology Honour

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

Dr. Anubhava Srivastava clearly demonstrates the caliber, consistency, and creativity required for the Best Researcher Award. His research intersects crucial domains like artificial intelligence, geoinformatics, and sustainable development—aligning with global scientific goals. With his growing research influence (Scopus H-index: 8, Google Scholar H-index: 9) and a diversified portfolio of publications, patents, and outreach, he is a highly suitable candidate for this prestigious recognition. With minor expansion in internationalization and technology transfer, Dr. Srivastava is poised for greater academic impact on a global scale.