Mr. Ehab Elhosary | Vision and Language | Research Excellence Award

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Nisharg Nargund | Document Image Analysis | Young Researcher Award

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Mr. Nisharg Nargund | Document Image Analysis | Young Researcher Award

Undergrad Researcher | Kalinga Institute of Industrial Technology | India

Mr. Nisharg Nargund is an emerging researcher in artificial intelligence and machine learning at the Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India. His research focuses on large language models, retrieval-augmented generation, transformer architectures, and multi-agent AI systems. He has authored Ten scholarly and professional publications, with 2 Scopus-indexed documents receiving 19 citations and an h-index of 1. His work has been presented at leading international conferences, earning Best Paper and Best Poster awards. Through academic collaborations, industry internships, and open-source projects, his research contributes to scalable, ethical, and societally impactful AI solutions in education, language technology, and industry.

 

Citation Metrics (Scopus)

30

20

10

0

Citations
19

Documents
2

h-index
1

🟩 Citations đŸŸ„ Documents đŸŸ© h-index

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Featured Publications


Deep learning in Industry 4.0: Transforming manufacturing through data-driven innovation.

– In Distributed Computing and Intelligent Technology: 20th International Conference, ICDCIT 2024, Bhubaneswar, India, January 17–20, 2024, Proceedings. (2024). Cited By : 31

Conversational text extraction with large language models using retrieval-augmented systems.

– In Proceedings of the 6th International Conference on Computational Intelligence and Networks . (2025). Cited By : 5

Innovative fusion of LSTM and Bi-GRU networks for enhanced hate speech detection in social media.

– International Research Journal of Modernization in Engineering Technology and Science (IRJMETS). (2024). 

Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

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Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

Doctorate at University of Aveiro , Portugal

Profiles

Scopus

Orcid

Google Scholar

Academic Background

Dr. Kais Iben Nassar is a researcher with a focus on Condensed Matter Physics and Computational Chemistry. He completed his PhD in Physics of Condensed Materials in 2022 through a joint program between the University of Aveiro, Portugal, and the University of Sfax, Tunisia. Dr. Nassar is renowned for his work in materials science, particularly in the study of 2D materials like MXenes and their applications in energy storage and catalysis.

Education

  • PhD in Physics of Condensed Materials
    Université de Sfax & Universidade de Aveiro (2022)
    Achieved with highest honors.
  • Master’s in Condensed Matter Physics
    Université de Sfax (2018)
    Graduated with distinction.
  • Fundamental License in Physics-Chemistry
    Université de Sfax (2016)
    Graduated with distinction.

Professional Experience

  • Postdoctoral Researcher
    Universidade de Aveiro, CICECO (2023 – Present)
    Focus on MXenes catalysts and computational chemistry.
  • Researcher
    UniversitĂ© de Sfax & Universidade de Aveiro (2018 – 2021)
    Conducted research on perovskites and materials science.
  • Invited Assistant Professor
    UniversitĂ© de Sfax (2021 – 2022)
    Taught and mentored students in physics and chemistry.

🔬 Research Interests

Dr. Nassar’s research interests encompass Condensed Materials Physics, nano-materials, computational chemistry, and machine learning. His work includes investigating the properties of 2D materials such as MXene, exploring their potential in energy storage, catalysis, and electronics. He is actively engaged in the preparation and characterization of new perovskite ceramics and the study of their structural, electrical, and magnetic properties. Dr. Nassar is also a member of the European Materials Acceleration Center for Energy (EU-MACE) under the COST Action CA22123.

 Publications

Tailoring of structural, morphological, electrical, and magnetic properties of LaMn1−xFexO3 ceramics
  • Authors: Thakur, P., Nassar, K.I., Kumar, D., Essid, M., Lal, M.
  • Journal: RSC Advances
  • Year: 2024
Structural, electrical properties of bismuth and niobium-doped LaNiO3 perovskite obtained by sol–gel route for future electronic device applications
  • Authors: Nassar, K.I., Benamara, M., Kechiche, L., Teixeira, S.S., Graça, M.P.F.
  • Journal: Indian Journal of Physics
  • Year: 2024
Investigating Fe-doped Ba0.67Ni0.33Mn1−xFexO3 (x = 0, 0.2) ceramics: insights into electrical and dielectric behaviors
  • Authors: Tayari, F., Iben Nassar, K., Algessair, S., Hjiri, M., Benamara, M.
  • Journal: RSC Advances
  • Year: 2024
Sol–gel synthesized (Bi0.5Ba0.5Ag)0.5 (NiMn)0.5O3 perovskite ceramic: An exploration of its structural characteristics, dielectric properties and electrical conductivity
  • Authors: Tayari, F., Iben Nassar, K., Benamara, M., Soreto Teixeira, S., Graça, M.P.F.
  • Journal: Ceramics International
  • Year: 2024
Study of Electrical and Dielectric Behaviors of Copper-Doped Zinc Oxide Ceramic Prepared by Spark Plasma Sintering for Electronic Device Applications
  • Authors: Benamara, M., Iben Nassar, K., Rivero-AntĂșnez, P., SerrĂ , A., Esquivias, L.
  • Journal: Nanomaterials
  • Year: 2024

Ms. Linjing Wei | Deep Learning | Best Researcher Award

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Ms. Linjing Wei | Deep Learning | Best Researcher Award

Linjing Wei at Gansu Agricultural University, China

Profile

Scopus

Academic Background:

Ms. Linjing Wei is a distinguished female professor at Gansu Agricultural University, specializing in Grassland Science with a research focus on Grassland Informatics. Born in July 1977, she has made significant contributions to her field through her extensive research, academic guidance, and numerous publications.

Education:

Ms. Wei earned her PhD in Grassland Science from Gansu Agricultural University in June 2015. Her educational background has provided a strong foundation for her academic and research pursuits.

Professional Experience:

Ms. Wei teaches several courses for master’s students, including Introduction to Cloud Computing, Case Analysis of Software Engineering, Information Systems and Information Resource Management, and Distributed Systems and Cloud Computing Technology. As the first supervisor, she has guided numerous master’s students in various majors, particularly in Agricultural Engineering and Information Technology.

Research Interests:

Ms.Wei's research interests lie in Grassland Informatics. Over the past five years, she has led several key research projects with significant funding, focusing on areas such as data resource integration, intelligent cloud platforms for agricultural logistics, ecosystem restoration and monitoring, sustainable development planning, and trustworthy traceability systems for agricultural products. Her published works include papers in prestigious journals like Sensors and the Canadian Journal of Remote Sensing, as well as contributions to national-level textbooks and academic monographs.

📝 Academic Achievements:

Ms. Wei has an impressive list of published papers, including "Fine Segmentation of Chinese Character Strokes Based on Co-ordinate Awareness and Enhanced BiFPN" in Sensors (2024), "Enhanced Wheat Head Detection in Images Using Fourier Domain Adaptation and Random Guided Filter" in Canadian Journal of Remote Sensing (2024), and "Feature Selection in High Dimensional Biomedical Data Based on BF-SFLA" in Neurogenetics (2022).

 Publications:

Fine Segmentation of Chinese Character Strokes Based on Coordinate Awareness and Enhanced BiFPN
  • Authors:Mo, H., Wei, L.
  • Journal: Sensors
  • Year: 2024
A Smart Chicken Farming Platform for Chicken Behavior Identification and Feed Residual Estimation
  • Authors: Yang, J., Gao, J., Li, Y., Lu, Q., Zheng, H.
  • Journal: Proceedings - 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
  • Year: 2023
Feature Selection in High Dimensional Biomedical Data Based on BF-SFLA
  • Authors: Dai, Y., Niu, L., Wei, L., Tang, J.
  • Journal: Frontiers in Neuroscience
  • Year: 2022
Jointly Learning Topics in Sentence Embedding for Document Summarization
  • Authors: Gao, Y., Xu, Y., Huang, H., Wei, L., Liu, L.
  • Journal: IEEE Transactions on Knowledge and Data Engineering
  • Year: 2020
Study on the Matching Algorithm of Turf Grass Introduction Features Based on Big Data Analysis
  • Authors: Wei, L., Dong, W., Gan, S., Wang, Y.
  • Year: 2019