Zhaksylyk Serikov | Ecosystem | Innovative Research Award

Innovative Research Award

Zhaksylyk Serikov
Affiliation Shakarim University
Country Kazakhstan
Scopus ID 57191170229
Documents 3
Citations 8
h-index 2
Subject Area Veterinary Medicine
Event Zoology Honour Awards
ORCID 0000-0002-6895-8392

Zhaksylyk Serikov,
Shakarim University

Zhaksylyk Serikov is affiliated with Shakarim University, Kazakhstan, where his scholarly activities contribute to veterinary medicine research. His indexed publications demonstrate developing academic engagement through internationally recognized databases. This article summarizes his research profile, publication record, measurable scholarly impact, and potential suitability for recognition within the Zoology Honour Awards program.[1]

Abstract

This article reviews the academic profile of Zhaksylyk Serikov using publicly available scholarly indicators. It highlights publication activity, citation performance, subject specialization, and professional affiliation while presenting an objective overview supporting academic recognition. Information reflects available indexed records and established scholarly documentation standards.[1]

Keywords

Veterinary medicine, animal health, academic research, Kazakhstan, Scopus, scholarly publications, research evaluation, citation analysis, scientific communication, zoological sciences, university research, innovation, academic excellence, research metrics, professional recognition, DOI indexing, international collaboration, animal science, researcher profile, scholarly impact.[2]

Introduction

Veterinary medicine supports animal welfare, public health, and sustainable livestock management through scientific investigation. Researchers contribute by developing evidence-based knowledge, improving clinical practices, and expanding interdisciplinary collaboration. Academic indexing systems provide measurable indicators that assist transparent evaluation of scientific productivity and research influence.[2]

Research Profile

The available Scopus profile identifies three indexed documents, eight citations, and an h-index of two. Affiliation with Shakarim University demonstrates institutional research participation within veterinary medicine. These metrics provide standardized evidence describing publication visibility and scholarly engagement across indexed scientific literature.[1]

Research Contributions

Research contributions emphasize veterinary medicine through documented scholarly publications supporting scientific understanding. Indexed outputs contribute to professional knowledge exchange and encourage continued academic collaboration. Such contributions strengthen institutional research capacity while promoting evidence-based practices relevant to animal science and related biological disciplines.[3]

Publications

Indexed publications represent measurable scholarly productivity and demonstrate participation within peer-reviewed scientific communication. Publication records contribute to citation accumulation, research visibility, and academic credibility. Persistent identifiers, including DOI records, facilitate reliable access, verification, and long-term preservation of published scientific outputs.[3]

Research Impact

Citation indicators demonstrate early scholarly influence through measurable engagement by other researchers. Although publication volume remains modest, indexed citations indicate recognition within scientific literature. Standard metrics, including the h-index, provide objective benchmarks supporting responsible evaluation of academic performance and research dissemination.[1]

Award Suitability

Available academic indicators suggest alignment with recognition emphasizing developing research achievement and scientific contribution. Objective assessment should consider publication quality, citation evidence, institutional affiliation, ethical research practices, and subject relevance. Independent peer evaluation remains essential during award selection procedures.[2]

Conclusion

The documented research profile presents measurable scholarly activity within veterinary medicine. Indexed publications, citation statistics, and institutional affiliation collectively provide a structured overview suitable for academic documentation. Continued research productivity and collaboration may further strengthen future scientific visibility and scholarly influence.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Zhaksylyk Serikov, Author ID 57191170229.Scopus.

    https://www.scopus.com/authid/detail.uri?authorId=57191170229

  2. ORCID. (n.d.). ORCID record for Zhaksylyk Serikov.

    https://orcid.org/0000-0002-6895-8392

  3. Serikova, A., Dyussembayev, S., Suleimenov, S., Serikov, Z., & Abdykarimova, S. (2025). Radioecological state of the environment in the area of the former Semipalatinsk Nuclear Test Site. Scientific Horizons, 28(7), 120–135.

    https://doi.org/10.48077/scihor7.2025.120

Anubhava Srivastava | Ecosystem | Best Researcher Award

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✅