Elahe Karampour | Artificial Intelligence | Best Researcher Award

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Ms. Elahe Karampour | Artificial Intelligence| Best Researcher Award

 

Ms. Elahe  Karampour  K.N.Toosi University Of Technology, Iran

Elahe Karampour is a dedicated researcher specializing in Geodesy and Geomatics Engineering with a focus on spatial-temporal data analysis and network science. She is currently pursuing her Master of Science at K.N. Toosi University of Technology, Tehran, Iran, with a thesis on analyzing location-based social networks using geometric curves. She has served as a research assistant, contributing to advancements in community detection and link prediction in spatial networks. Elahe is also an experienced educator, having taught GIS, spatial databases, and social network analysis. She has received national recognition for her academic excellence and was awarded a fully funded research visit to ScaDS.AI in Germany. Her expertise spans programming, spatial modeling, and AI-driven geospatial analytics.

🌍 Professional Profile:

Orcid

🏆 Suitability for the Best Researcher Award

 

Elahe Karampour is an outstanding researcher with significant contributions to geospatial data analysis, particularly in network science and location-based social networks. Her pioneering research integrates Ricci curvature and hyperbolic geometry for community detection and link prediction, leading to novel advancements in spatial-temporal modeling. She has published influential research in high-impact journals, demonstrating her expertise and innovation. Elahe’s research excellence is further recognized through a prestigious fully funded research visit to ScaDS.AI in Germany. With strong technical proficiency in R, Python, PostgreSQL, and GIS software, she bridges theory and application, developing intelligent recommender systems for urban planning. Her exceptional academic record, teaching excellence, and innovative research make her a prime candidate for the Best Researcher Award.

🎓 Education 

Elahe Karampour holds a Master of Science in Geodesy and Geomatics Engineering from K.N. Toosi University of Technology, Tehran, Iran (2021–2024). Her research focuses on spatial-temporal data analysis and social network modeling, with a thesis titled “Analysis of Location-Based Social Networks with Geometric Curves,” receiving a perfect grade of 20/20. She completed her Bachelor of Science in Geodesy and Geomatics Engineering at the University of Zanjan, Iran (2015–2020). Elahe ranked 23rd nationwide in the Iranian Master’s University Entrance Exam, showcasing her academic excellence. Her strong analytical and technical skills, coupled with expertise in GIS, AI, and network analysis, enable her to make significant contributions to the field of geospatial research and urban data science.

🏢 Work Experience 

Elahe Karampour has extensive research and teaching experience in geospatial data analysis and network science. As a Research Assistant (2022–2024) at K.N. Toosi University of Technology, she developed advanced models for community detection and link prediction in location-based social networks using geometric methods. She also worked as a Lecturer (2024) at Babol Noshirvani University of Technology, teaching spatial analysis and visualization to undergraduate students. Additionally, she served as a Teaching Assistant (2023–2024), guiding master’s and PhD students in GIS, social network analysis, and spatial databases. Her technical expertise in R, Python, PostgreSQL, and QGIS, combined with her ability to integrate AI with geospatial analysis, has positioned her as a leader in her research domain.

🏅 Awards and Honors 

Elahe Karampour has received multiple accolades for her academic and research excellence. She ranked 23rd nationwide in the Iranian Master’s University Entrance Exam (2021), demonstrating her strong academic foundation. She was awarded a fully funded research grant for a short-term visit to ScaDS.AI Center for Scalable Data Analytics and Artificial Intelligence in Germany (2023), recognizing her contributions to AI-driven geospatial analysis. Additionally, she was listed among the top-ranked teachers by her students for her exceptional teaching performance. Her work in network science and geospatial modeling has led to publications in high-impact journals, further cementing her status as a leading researcher. These achievements underscore her dedication and outstanding contributions to the field of geospatial and network science.

🔬 Research Focus 

Elahe Karampour’s research centers on spatial-temporal data analysis, network science, and AI-driven geospatial modeling. She specializes in analyzing location-based social networks using advanced mathematical frameworks such as Ricci curvature and hyperbolic geometry for community detection and link prediction. Her work integrates graph-based modeling with GIS technologies to enhance urban planning, mobility analysis, and personalized recommender systems. Elahe has developed innovative approaches to analyzing complex data structures, utilizing machine learning and AI techniques for geospatial applications. She is particularly interested in the intersection of mathematics, computer science, and geospatial technologies, aiming to create data-driven solutions for urban analytics and smart city development. Her research has been recognized internationally, reinforcing her expertise in geospatial data science.

📊 Publication Top Notes:

  • Karampour, E., Malek, M.R., & Eidi, M. (2025). Discrete Ricci flow: A powerful method for community detection in location-based social networks. Computers and Electrical Engineering, 123, 110302.

R Lakshman Naik |Computer Science and Engineering | Best Paper Award

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Mr.R Lakshman Naik|Computer Science and Engineering| Best Paper Award

Research Scholar at Indian Institute of Information Technology Sonepat , Haryana, India

Mr. R. Lakshman Naik is a Research Scholar at the Indian Institute of Information Technology (IIIT) Sonepat, Haryana, India. His research focuses on advanced topics in computer science, artificial intelligence, data science, or related fields. As a dedicated scholar, he actively contributes to academic research, publications, and innovative technological developments. IIIT Sonepat, recognized as an Institute of National Importance, provides a dynamic environment for cutting-edge research and interdisciplinary collaboration.

Publication Profile

Scopus

Education :

Lakshman Naik Ramavathu holds a Master of Technology (M.Tech) degree in Digital Communication from Kakatiya University, Warangal (2014-16), and another M.Tech in Computer Science and Engineering from JNT University, Hyderabad (2009-11). He completed his Bachelor of Technology (B.Tech) in Electronics and Communication Engineering from JNT University, Hyderabad (2001-05). His diverse educational background provides a strong foundation in computer science, digital communication, and information technology.

Experience :

Currently, he serves as an Assistant Professor (C) in the Department of Information Technology at KU College of Engineering & Technology, Warangal, where he has been teaching since 2016. His teaching expertise includes Operating Systems, Computer Architecture and Organization, Data Communication and Networking, Machine Learning, Python Programming, and Mobile Cloud Computing.

Prior to his academic career, he worked as a Part-time Lecturer in the Department of Computer Science at Kakatiya University (2012-2016), where he taught subjects like System Software, Cloud Computing, Mobile Communication, and Open-Source Software.

Research Focus :

Lakshman Naik Ramavathu’s research interests include Machine Learning, Cloud Computing, Data Mining, and Computer Networking. His work revolves around optimizing computational frameworks, developing intelligent predictive models, and improving networking protocols for enhanced system performance.

Skills:

Sun Certified System Administrator for Sun Solaris 9 (Part-I & II)Microsoft Certified Professional in Windows 2003 Enterprise Server Expertise in Cloud Computing, Machine Learning, Computer Networks, and Data Mining

Awards:

Recognized for impactful research contributions in cloud computing and machine learning Multiple research papers published in high-impact international journals Significant contributions to academia and industry in system administration and computing

 

Publication :

  • Comparison of Data Mining Versus Traditional Analysis in Textile Business”

    • Publication: IFRSA International Journal of Data Warehousing & Mining
    • ISSN (Online): 2249–2186
    • ISSN (Print): 2249–7161
    • Volume: 1, Issue 1

  • “DFFS: Detecting Fraud in Finance Sector”

    • Authors: R. Lakshman Naik, Dr. Manjula Bairam
    • Publication: International Journal of Advanced Engineering Sciences and Technologies
    • ISSN: 2230-7818
    • Volume: 9, Issue 2

  • “Study of Trends in Higher Education”

    • Publication: International Journal of Computer Trends and Technology
    • ISSN: 2231-2803
    • Volume: 1, Issue 1

  • “Stock Prediction using Neural Network”

    • Publication: International Journal of Advanced Engineering Sciences and Technologies
    • ISSN: 2230-7818
    • Volume: 10, Issue 1

  • “Session Data Protection Using Tree-Based Dependency”

    • Publication: International Journal of Advances in Engineering & Technology
    • ISSN: 2231-1963
    • Volume: 2, No. 1

  • “Secure Authentication Scheme for Mobile Ad Hoc Networks”

    • Publication: International Journal of Mobile & Adhoc Network
    • ISSN (Online): 2231-6825
    • ISSN (Print): 2249-202X
    • Volume: 2, Issue 1

  • “Secure Scheme of Data Protection in Cloud Computing”

    • Publication: International Journal of Computer Science and Technology
    • ISSN: 0976-8491
    • ISSN: 2229-4333
    • Volume: 3, No. 1

  • “Cloud Computing: Research Issues and Implications”

    • Publication: International Journal of Cloud Computing and Services Science
    • ISSN: 2089-3337
    • Volume: 2, No. 2

  • “Prediction of BSE Stock Data using MapReduce K-Mean Cluster Algorithm”

    • Publication: International Journal of Current Engineering and Technology, INPRESSCO
    • E-ISSN: 2277–4106
    • P-ISSN: 2347–5161
    • Volume: 5, No. 3

  • “Current Apprises of Opinion Mining Methods”

    • Publication: International Journal of Engineering and Advanced Technology (IJEAT)
    • ISSN: 2249–8958
    • Volume: 9, Issue 2

 

 Conclusion

Based on his research achievements, Lakshman Naik Ramavathu is well-suited for a Best Paper Award, provided the submission is among his most impactful and high-quality research works. Enhancing recent publications, collaborations, and practical implementations will further solidify his standing in the academic and research community.