Amrithkala M Shetty | Computer Science and Artificial Intelligence | Women Researcher Award

Published on by Computer Scientists Awards

Women Researcher Award

Amrithkala M Shetty
Affiliation Nitte (Deemed to be University)
Country India
Scopus ID 58767603900
Documents 14
Citations 86
h-index 4
Subject Area Computer Science and Artificial Intelligence
Event Computer Scientists Awards
ORCID 0009-0003-2751-1388

Amrithkala M Shetty

Nitte (Deemed to be University), India

Amrithkala M Shetty, affiliated with Nitte (Deemed to be University), is an Indian researcher whose scholarly work primarily focuses on computer science, artificial intelligence, natural language processing, recommender systems, and sentiment analysis. Her publication record demonstrates sustained contributions toward machine learning methodologies, transformer-based language models, and intelligent analytics for e-commerce applications. With publications indexed in Scopus and research appearing in peer-reviewed journals and conference proceedings, her academic profile reflects continuous engagement with contemporary computational research.[1]

Abstract

The academic contributions of Amrithkala M Shetty emphasize the application of artificial intelligence to text analytics, recommendation systems, and sentiment mining. Her research combines classical machine learning techniques with deep learning architectures, including convolutional neural networks and transformer models such as XLNet, to improve prediction accuracy for online review analysis. These studies contribute to practical decision-support systems while also advancing methodological understanding within computational intelligence and natural language processing.[2]

Keywords

Artificial Intelligence, Sentiment Analysis, Machine Learning, XLNet, Deep Learning, Transformer Models, Recommender Systems, Natural Language Processing, Computer Science.

Introduction

Research in intelligent text processing has become increasingly important because of the rapid growth of digital information and user-generated content. Amrithkala M Shetty’s work addresses this evolving landscape by developing computational methods that improve sentiment classification, recommendation accuracy, and automated interpretation of online reviews. Her publications demonstrate an interdisciplinary approach that integrates data mining, artificial intelligence, and predictive analytics for real-world applications.[3]

Research Profile

According to the provided research metrics, the author has produced 14 Scopus-indexed publications with 86 citations and an h-index of 4. Her scholarly interests include artificial intelligence, machine learning optimization, recommender systems, deep neural networks, and computational linguistics. These indicators reflect an emerging research profile with growing scholarly visibility.[1]

Research Contributions

  • Comparative evaluation of transformer architectures for sentiment classification.
  • Survey research on collaborative filtering recommender systems.
  • Hyperparameter optimization using grid search techniques.
  • Application of attention-based CNN models with pretrained embeddings.
  • Machine learning approaches for e-commerce review analytics.

Publications

  • Fine-tuning XLNet for Amazon Review Sentiment Analysis: A Comparative Evaluation of Transformer Models (ETRI Journal, 2026).
  • A Collaborative Filtering Recommender Systems: Survey (Neurocomputing, 2025).
  • Hyperparameter Optimization of Machine Learning Models Using Grid Search for Amazon Review Sentiment Analysis (2024).
  • Sentiment Exploring on Feedback of E-commerce Data Using Machine Learning Algorithms (2024).
  • Unleashing the Power of 2D CNN with Attention and Pre-trained Embeddings for Enhanced Online Review Analysis (2024).

Research Impact

The research portfolio illustrates practical engagement with modern artificial intelligence methods that support sentiment classification, recommender technologies, and predictive modeling. Publications in recognized journals and conference proceedings demonstrate consistent participation in advancing machine learning applications for digital commerce and intelligent decision-support systems. Citation metrics indicate growing recognition within the research community.[4]

Award Suitability

Based on the available scholarly record, Amrithkala M Shetty demonstrates sustained research activity in computer science and artificial intelligence. Her contributions to transformer-based sentiment analysis, recommender systems, optimization methods, and intelligent data analytics align with the objectives of the Women Researcher Award, which recognizes academic excellence, innovation, and meaningful contributions to scientific advancement within computing disciplines.[5]

Conclusion

The available evidence highlights a developing research career characterized by interdisciplinary work in artificial intelligence and machine learning. Through publications addressing sentiment analysis, recommender systems, and transformer architectures, Amrithkala M Shetty contributes to contemporary computational research while supporting practical applications in intelligent information processing. Her scholarly profile reflects continued academic engagement and potential for future impact.

References

  1. Elsevier. (n.d.). Scopus Author Details: Amrithkala M Shetty, Author ID 58767603900.
    https://www.scopus.com/authid/detail.uri?authorId=58767603900
  2. ETRI Journal. Fine-tuning XLNet for Amazon Review Sentiment Analysis.
    https://doi.org/10.4218/etrij.2024-0318
  3. Neurocomputing. A Collaborative Filtering Recommender Systems: Survey.
    https://doi.org/10.1016/j.neucom.2024.128718
  4. Lecture Notes in Networks and Systems. Hyperparameter Optimization of Machine Learning Models Using Grid Search.
    https://link.springer.com/chapter/10.1007/978-981-99-7814-4_36
  5. International Journal of Computers and Applications. Unleashing the Power of 2D CNN with Attention and Pre-trained Embeddings for Enhanced Online Review Analysis.
    https://doi.org/10.1080/1206212X.2023.2283647

Miljan Vucetic  | Computer Science and Artificial Intelligence | Best Researcher Award

Published on by Computer Scientists Awards

Best Researcher Award

Miljan Vucetic
Vlatacom Institute,Serbia

Miljan Vucetic
Affiliation Vlatacom Institute
Country Serbia
Scopus ID 59022569000
Documents 32
Citations 185
h-index 8
Subject Area Computer Science and Artificial Intelligence
Event Computer Scientists Awards
ORCID 0000-0002-4362-6201

Miljan Vucetic is a Serbian computer scientist, artificial intelligence researcher, and technology leader associated with the Vlatacom Institute. His academic and industrial activities span artificial intelligence, machine learning, intelligent systems, sensor networks, distributed consensus algorithms, cybersecurity, and data analytics. Through appointments in higher education and research institutions, he has contributed to the advancement of applied artificial intelligence and intelligent computing technologies. His scholarly profile includes peer-reviewed publications, technical innovations, and interdisciplinary collaborations addressing contemporary challenges in computer science and engineering.[1]

Abstract

This article presents an overview of the academic achievements, research activities, and scientific contributions of Miljan Vucetic. His work integrates artificial intelligence methodologies with practical applications in networking, distributed systems, intelligent sensing, and data-driven decision making. Through scholarly publications, technological solutions, and leadership roles in research organizations, he has contributed to advancing the field of computer science and artificial intelligence.[2]

Keywords

Artificial Intelligence, Computer Science, Machine Learning, Sensor Networks, Reinforcement Learning, Data Mining, Fuzzy Logic, Intelligent Systems, Consensus Algorithms, Research Excellence.

Introduction

Miljan Vucetic completed a Ph.D. in Computer Science at the Faculty of Organizational Sciences, University of Belgrade. He subsequently developed a multidisciplinary research career connecting academic scholarship with industrial innovation. His professional appointments include positions at Vlatacom Institute, Singidunum University, and VSB – Technical University of Ostrava, where he has participated in teaching, research supervision, and advanced technology development.[3]

Research Profile

As Artificial Intelligence Technology Lead at the Vlatacom Institute, Vucetic has focused on designing intelligent computational frameworks applicable to real-world environments. His research interests encompass machine learning, fuzzy systems, intelligent transportation, distributed consensus mechanisms, cybersecurity-related applications, and heterogeneous network architectures. These topics align with emerging priorities in contemporary digital transformation initiatives.[1]

Research Contributions

Among his notable contributions are studies on fuzzy-guided exploration for multi-agent reinforcement learning in traffic signal control, advanced pattern mining techniques using statistical and fuzzy logic methods, secure randomness generation systems, and adaptive asynchronous gossip algorithms for heterogeneous sensor networks. He has also contributed to applied artificial intelligence solutions involving camera self-calibration technologies and intelligent networked systems.[4]

Publications

  • Fuzzy-Guided Exploration for Multi-Agent Reinforcement Learning in Traffic Signal Control (2026).
  • The Synergy of Statistical and Fuzzy Logic Approaches in Mining Patterns from Peer-to-Peer Lending Data (2026).
  • Synthesis of Sources of Common Randomness Based on Keystream Generators with Shared Secret Keys (2025).
  • Adaptive Asynchronous Gossip Algorithms for Consensus in Heterogeneous Sensor Networks (2025).
  • Artificial Intelligence-Based Camera Self-Calibration Software Solution for Heterogeneous Fixed and Mobile Networks (2025).

Research Impact

With 32 indexed documents, 185 citations, and an h-index of 8, Vucetic has established a measurable scholarly presence within the international computer science community. His publications have contributed to discussions on artificial intelligence deployment, intelligent networking systems, and advanced computational methodologies. The combination of academic productivity and practical technology development demonstrates sustained engagement with research excellence.[1]

Award Suitability

Miljan Vucetic’s record of scientific publication, technological innovation, academic leadership, and interdisciplinary collaboration supports consideration for the Best Researcher Award. His contributions reflect ongoing efforts to bridge theoretical computer science with practical artificial intelligence applications while maintaining active participation in research, education, and industrial development.[5]

Conclusion

The professional accomplishments of Miljan Vucetic illustrate a balanced combination of academic scholarship, research leadership, and technological innovation. His work in artificial intelligence and computer science continues to contribute to the development of intelligent systems and advanced computational solutions, making him a notable researcher within his field.

References

  1. Elsevier. (n.d.). Scopus author details: Miljan Vucetic, Author ID 59022569000. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59022569000
  2. ORCID. (n.d.). Miljan Vucetic Research Profile.
    https://orcid.org/0000-0002-4362-6201
  3. University of Belgrade. Doctoral Studies in Computer Science.
  4. Vucetic, M. (2026). Fuzzy-Guided Exploration for Multi-Agent Reinforcement Learning in Traffic Signal Control. Mathematics.
    https://doi.org/10.3390/math14111942
  5. Vucetic, M. (2026). The Synergy of Statistical and Fuzzy Logic Approaches in Mining Patterns from Peer-to-Peer Lending Data. Expert Systems with Applications.
    https://doi.org/10.1016/j.eswa.2025.129308
  6. Vucetic, M. (2025). Adaptive Asynchronous Gossip Algorithms for Consensus in Heterogeneous Sensor Networks. IEEE Internet of Things Journal.
    https://doi.org/10.1109/JIOT.2025.3559242

Antoine Dufour | Data Science | Innovative Research Award

Published on by Computer Scientists Awards

Innovative Research Award

Antoine Dufour
University of Calgary
Antoine Dufour
Affiliation University of Calgary
Country Canada
Google Scholar ID D1h8F1wAAAAJ
Citations 6315
h-index 38
i10-index 77
Scopus ID 25421482900
Subject Area Data Science
Event Computer Scientists Awards
ORCID 0000-0002-3429-4188

Antoine Dufour is a researcher affiliated with the University of Calgary whose scholarly work has contributed to the interdisciplinary fields of data science, computational analysis, and applied engineering methodologies. His research profile reflects sustained academic engagement through peer-reviewed publications, collaborative scientific initiatives, and international scholarly visibility. The recognition associated with the Innovative Research Award acknowledges his contributions to data-intensive methodologies and advanced computational applications within modern scientific research environments.[1]

Abstract

This article presents an overview of the academic profile, research achievements, and scholarly contributions of Antoine Dufour in the field of data science and computational research. The profile highlights research productivity, publication metrics, interdisciplinary engagement, and scientific impact within contemporary technological research environments. The Innovative Research Award recognizes sustained scholarly activity and contributions to computational methodologies and analytical systems applied across engineering and scientific domains.[2]

Keywords

Data Science, Computational Modeling, Artificial Intelligence, Machine Learning, Engineering Analytics, Research Innovation, Scientific Computing, Information Systems, Statistical Analysis, Applied Data Technologies

Introduction

The increasing role of data-driven technologies in modern research has created new opportunities for interdisciplinary collaboration and scientific advancement. Researchers engaged in computational sciences contribute substantially to the development of analytical frameworks capable of addressing complex engineering and scientific problems. Antoine Dufour has participated in scholarly efforts associated with data analysis, computational systems, and applied technological methodologies, supporting the broader evolution of data-centric research practices.[1][3]

Academic recognition programs such as the Computer Scientists Awards aim to identify researchers whose contributions demonstrate measurable scholarly impact, publication consistency, and active participation within scientific communities. The Innovative Research Award reflects recognition of these academic characteristics within an international research context.[5]

Research Profile

Antoine Dufour is affiliated with the University of Calgary and maintains an active scholarly profile in data science and related computational research areas. His research output includes peer-reviewed journal articles, collaborative studies, and scientific contributions indexed through international academic databases. Citation indicators and bibliometric measures demonstrate sustained academic visibility within relevant scientific communities.[1]

  • Research specialization in data science and computational methodologies.
  • Academic affiliation with the University of Calgary.
  • Indexed scholarly contributions in international citation databases.
  • Interdisciplinary engagement involving engineering and analytical sciences.

Research Contributions

The research contributions associated with Antoine Dufour emphasize the application of computational tools and analytical frameworks to address scientific and engineering challenges. His work includes participation in projects involving data interpretation, optimization methodologies, predictive analysis, and advanced modeling techniques. Such contributions support broader developments in computational research and digital innovation.[3]

In addition to publication activities, his scholarly engagement reflects participation in collaborative research environments that integrate multidisciplinary perspectives. These efforts contribute to the advancement of methodological approaches within data science and computational engineering domains.[4]

Publications

Selected scholarly publications and indexed research outputs associated with Antoine Dufour include contributions related to computational analysis, data modeling, and interdisciplinary technological systems. Publication visibility across indexed academic platforms contributes to citation impact and scholarly dissemination.[2]

  1. Research articles addressing computational data analysis methodologies.
  2. Collaborative studies related to engineering analytics and scientific computing.
  3. Publications indexed within Scopus and scholarly citation platforms.
  4. Interdisciplinary research integrating analytical and digital technologies.

Research Impact

The scholarly impact associated with Antoine Dufour is reflected through citation metrics, academic indexing, and sustained publication activity. Citation indicators, including an h-index of 38 and a substantial citation count, demonstrate continued recognition within scientific literature. These metrics indicate the relevance and visibility of his research contributions within contemporary computational and data science disciplines.[1][2]

Research dissemination through international journals and scholarly databases further supports academic accessibility and interdisciplinary collaboration. Such visibility contributes to the exchange of methodological innovations and computational research practices among scientific communities.[4]

Award Suitability

The Innovative Research Award recognizes researchers demonstrating meaningful contributions to scientific progress through publication quality, research engagement, and scholarly visibility. Antoine Dufour’s academic profile aligns with these criteria through his established publication record, citation impact, and involvement in computational and data science research initiatives.[5]

His work illustrates the integration of computational methodologies with interdisciplinary scientific inquiry, supporting innovation within modern research environments. These characteristics contribute to the suitability of his recognition within the Computer Scientists Awards framework.[3]

Conclusion

Antoine Dufour’s scholarly profile reflects continued participation in data science and computational research through peer-reviewed publications, collaborative projects, and measurable academic impact. His contributions support the advancement of analytical methodologies and interdisciplinary technological applications. Recognition through the Innovative Research Award acknowledges these sustained academic efforts and their relevance within contemporary scientific research communities.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Antoine Dufour, Author ID 25421482900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=25421482900
  2. Google Scholar. (n.d.). Antoine Dufour citation profile and scholarly metrics.
    https://scholar.google.com/citations?user=D1h8F1wAAAAJ&hl=en&oi=ao
  3. Dufour, A. et al. (2013). Applications of computational methodologies in biomass and data analytics research.
    https://doi.org/10.1016/j.biombioe.2013.09.005
  4. ORCID. (n.d.). ORCID profile for Antoine Dufour.
    https://orcid.org/0000-0002-3429-4188
  5. Computer Scientists Awards. (n.d.). International recognition and academic award platform.

    https://computerscientists.net/

Shuang Zhang | Artificial Intelligence | Young Scientist Award

Published on by Computer Scientists Awards

Young Scientist Award

Shuang Zhang
Wuhan University, China
Shuang Zhang
Affiliation Wuhan University
Country China
Scopus ID
57216511036
Documents 1
Citations Citations by 11 documents
h-index 1
Subject Area Artificial Intelligence
Event Computer Scientists Award
ORCID
0000-0002-0218-9519

Shuang Zhang is a researcher affiliated with Wuhan University, China, whose academic activities are associated with artificial intelligence and intelligent computational systems. The researcher’s scholarly profile reflects participation in emerging research areas involving machine learning methodologies, intelligent data analysis, and computational modeling. This academic recognition article has been prepared in relation to the Young Scientist Award under the Computer Scientists Award initiative.[1]

Abstract

This article presents an academic recognition profile of Shuang Zhang, focusing on scholarly engagement within the field of artificial intelligence and intelligent computational systems. The profile examines academic visibility through publication activity, citation performance, and participation in emerging computational research areas. Emphasis is placed on artificial intelligence methodologies, machine learning integration, and interdisciplinary computational applications relevant to modern scientific innovation.[2][3]

Keywords

Artificial Intelligence; Machine Learning; Intelligent Systems; Computational Modeling; Deep Learning; Data Analysis; Neural Networks; Computer Science; Young Scientist Award; Scientific Research.

Introduction

Artificial intelligence has become one of the most influential areas within modern computational science, supporting advancements in automated reasoning, intelligent data processing, and adaptive analytical systems. Research in this field contributes to innovation across engineering, communication technologies, healthcare systems, and digital infrastructures.[3]

Shuang Zhang’s academic profile reflects participation in research activities associated with intelligent computing methodologies and machine learning applications. Such scholarly engagement contributes to the broader scientific development of computational intelligence and data-driven research systems.[1]

Research Profile

Shuang Zhang is affiliated with Wuhan University, an institution recognized for research activities in engineering, computer science, and interdisciplinary technological innovation. The researcher’s academic profile demonstrates engagement with artificial intelligence studies and computational methodologies relevant to intelligent information systems.[1]

The available Scopus profile indicates emerging scholarly visibility through indexed publication activity and citation engagement within the international scientific community. Citation metrics and publication indicators suggest continued academic participation within computational research domains.[1]

The researcher’s ORCID registration additionally supports standardized academic identification and enhances international discoverability across scholarly databases and scientific publication systems.[4]

Research Contributions

The research contributions associated with Shuang Zhang are connected with artificial intelligence methodologies, computational modeling systems, and machine learning applications. Such studies contribute to the advancement of intelligent algorithms and adaptive computational frameworks used in modern scientific and engineering environments.[2]

Artificial intelligence research frequently integrates neural networks, optimization techniques, and predictive analytical systems designed to improve decision-making efficiency and computational accuracy. These interdisciplinary approaches support technological development across numerous scientific and industrial applications.[5]

The researcher’s scholarly engagement contributes to broader academic discussions concerning intelligent systems, machine learning integration, and data-driven computational research methodologies.[3]

Publications

Shuang Zhang has contributed to scholarly publications associated with artificial intelligence and intelligent computational systems research. The publication profile reflects participation in scientific communication and computational science dissemination activities within indexed academic environments.[1]

  • Research studies related to artificial intelligence methodologies and intelligent computational frameworks.[2]
  • Academic works involving machine learning systems and computational data analysis approaches.[5]
  • Scientific contributions supporting interdisciplinary research communication within computer science and intelligent systems domains.[3]

The researcher’s publication activity reflects continued involvement in computational research dissemination and scholarly participation within international academic indexing systems.[1]

Research Impact

Research impact within artificial intelligence is commonly evaluated through publication visibility, citation performance, and interdisciplinary applicability. The available citation metrics associated with Shuang Zhang suggest emerging scholarly recognition within computational science and intelligent systems research communities.[1]

Artificial intelligence technologies contribute substantially to modern digital transformation initiatives, including intelligent automation, predictive analytics, and adaptive computational infrastructures. Research in this field supports innovation across communication systems, healthcare technologies, engineering applications, and data science environments.[5]

The researcher’s academic visibility is strengthened through indexed publication systems, citation tracking platforms, and ORCID-supported scholarly identification mechanisms.[4]

Award Suitability

The academic profile of Shuang Zhang reflects characteristics associated with emerging research excellence and early-career scientific engagement. Indexed publication activity, interdisciplinary research participation, and measurable citation visibility support consideration within academic recognition frameworks oriented toward young researchers and innovative computational studies.[1]

The researcher’s work in artificial intelligence and intelligent systems aligns with the objectives commonly emphasized by international scientific recognition platforms that support innovation, computational research quality, and technological advancement.[6]

The combination of institutional affiliation, indexed scholarly activity, and engagement with artificial intelligence methodologies collectively supports recognition through the Young Scientist Award initiative.[6]

Conclusion

Shuang Zhang represents an emerging academic profile within the field of artificial intelligence and intelligent computational systems. Scholarly engagement in machine learning methodologies, indexed publication activity, and participation in computational science research demonstrate continued involvement in modern technological and scientific innovation environments.[1]

This recognition article highlights the researcher’s academic visibility and emphasizes the continuing relevance of artificial intelligence research within interdisciplinary scientific and technological development frameworks.[3]

References

  1. Elsevier. (n.d.). Scopus author details: Shuang Zhang, Author ID 57216511036. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57216511036
  2. ORCID. (n.d.). ORCID researcher identifier registry.
    https://orcid.org/0000-0002-0218-9519
  3. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.
    https://doi.org/10.1038/nature14539

Dr. Volodymyr Burianov | Artificial Intelligence | Research Excellence Award

Published on by Computer Scientists Awards

Dr. Volodymyr Burianov | Artificial Intelligence | Research Excellence Award

Principal Scientist | Enamine Ltd. | Ukraine

Dr. Volodymyr Burianov is an emerging researcher in organic chemistry specializing in catalytic hydrogenation, heterogeneous catalysis, and the synthesis of heterocyclic compounds for pharmaceutical and advanced material applications. His work focuses on developing efficient catalytic systems, nanocomposite materials, and innovative hydrogenation strategies to enhance reaction selectivity and performance. He has contributed to multiple peer-reviewed publications and international conference presentations, reflecting steady scientific impact. According to available metrics, his research has achieved 56 Scopus citations across 6 documents with an h-index of 5, alongside growing visibility on Google Scholar. His contributions demonstrate strong potential in advancing catalytic science and sustainable chemical synthesis.

Citation Metrics (Scopus)

60

50

40

30

20

0

 

Citations
56

Documents
6

h-index
5

                   ■ Citations ■ Documents ■ h-index


View Scopus Profile View ORCID Profile

Featured Publications

Dr. Andrei Kojukhov | Artificial Intelligence | Research Excellence Award

Published on by Computer Scientists Awards

Dr. Andrei Kojukhov | Artificial Intelligence | Research Excellence Award

Senior Lecturer | Holon Institute of Technology | Israel

Dr. Andrei Kojukhov, is a researcher and academic in computer science specializing in artificial intelligence in education, data science, machine learning, cybersecurity, and next-generation communication systems. His research explores meta-cognitive AI, personalized and ubiquitous learning environments, and the integration of intelligent technologies into modern education and network infrastructures. He has contributed to peer-reviewed journals, international conferences, and standardization initiatives, alongside innovations in 5G, cloud, and network virtualization. His scholarly impact is reflected in Scopus metrics of 17 citations across 6 documents with an h-index of 2, and Google Scholar metrics of 142 citations with an h-index of 6, demonstrating sustained research relevance and interdisciplinary influence.

Citation Metrics

20

16

12

8

4

0

Citations
17

Documents
6

h-index
2

                          ■ Citations
■ Documents
■ h-index


View Scopus Profile View Google Scholar Profile

Featured Publications

Mrs. Kiane Alves e Silva | Technologies | Research Excellence Award

Published on by Computer Scientists Awards

Mrs. Kiane Alves e Silva | Technologies | Research Excellence Award

Polytechnic University of Madrid | Spain

Mrs. Kiane Alves e Silva is a researcher specializing in photovoltaic self-consumption systems, battery storage modelling, and renewable energy communities, with a strong focus on techno-economic assessment and energy system optimization. Her work integrates simulation tools, real-world data, and innovative indicators such as the Mismatch Index to improve decision-making in sustainable energy planning. She has contributed to multiple peer-reviewed journal publications, advancing knowledge in distributed energy solutions and community-based renewable systems. Her research impact is reflected in citation metrics, including Scopus (12 citations, 2 documents, h-index 1) and Google Scholar (14 citations, h-index 2), demonstrating growing academic recognition and influence.

Citation Metrics (Scopus)

20

15

10

0

Citations
12

Documents
2

h-index
1

 Citations    Documents    h-index


View Scopus Profile
 View ORCID Profile

Featured Publications

Off-grid Photovoltaic Systems Implementation for Electrification of Remote Areas
– Brazilian Archives of Biology and Technology, 2023

Quasi-dynamic operation and maintenance plan for photovoltaic systems in remote areas
– Renewable Energy, 2022

Sizing Photovoltaic Self-Consumption Systems for Sustainable Decision-Making
– Sustainability, 2026

Assoc. Prof. Dr. Maikel Leon | Artificial Intelligence | Research Excellence Award

Published on by Computer Scientists Awards

Assoc. Prof. Dr. Maikel Leon | Artificial Intelligence | Research Excellence Award

Associate Professor Practice | University of Miami | United States

Dr. Maikel Leon is a leading researcher in artificial intelligence, explainable AI, fuzzy cognitive maps, machine learning, and intelligent systems, with strong applications in business technology, cybersecurity, transportation, and sustainable computing. His scholarly work bridges theoretical AI models with real-world decision-making, emphasizing transparency, reasoning, and human-centered intelligence. He has authored influential contributions in top-tier journals and IEEE conferences, advancing cognitive mapping, AI safety, sentiment analysis, and large language model governance. His research impact is well established, with over 900 citations on Google Scholar (h-index 17, i10-index 23) and more than 350 Scopus citations across 38 indexed documents (Scopus h-index 11), reflecting sustained international influence and research excellence.

Citation Metrics (Google Scholar)

1000

800

600

400

200

0

 

Citations
927

i10-index
23

h-index
17

                        🟦 Citations  🟥 i10-index  🟩 h-index


View Scopus Profile View ORCID Profile View Google Scholar Profile

Featured Publications

Prof. Hedi Sakli | Artificial Intelligence | Research Excellence Award

Published on by Computer Scientists Awards

Prof. Hedi Sakli | Artificial Intelligence | Research Excellence Award

Professor | University of Tunis El Manar | Tunisia

Hedi Sakli is a senior researcher and academic expert in telecommunications, electromagnetics, antennas, wave propagation, and advanced radiofrequency systems, with strong contributions spanning 5G technologies, metamaterials, optical communications, signal processing, and applied artificial intelligence. His research integrates theoretical electromagnetism with practical engineering applications, including IoT, sensor networks, and AI-assisted health and communication systems. He has authored an extensive body of peer-reviewed scientific work with significant international visibility. According to indexed databases, his research impact includes more than 116 Scopus-indexed documents with over 1,197 citations and an h-index of 14, alongside more than 1,755 Google Scholar citations and an h-index of 17, reflecting sustained scholarly influence and research leadership.

Citation Metrics (Scopus)

1250

1000

750

500

250

0

 

 

Citations
1,197

Documents
116

h-index
14

           🟦 Citations   🟥 Documents   🟩 h-index


View Scopus Profile
 View ORCID Profile
 View Google Scholar Profile

Featured Publications

Cornelia-Aurora Győrödi | Artificial Intelligence | Research Excellence Award

Published on by Computer Scientists Awards

Prof. Dr. Cornelia-Aurora Győrödi | Artificial Intelligence | Research Excellence Award

Professor | University of Oradea | Romania

Prof. Dr. Győrödi Cornelia Aurora is an accomplished researcher in computer science and information technology, specializing in databases, big data management, cloud computing, data mining, web mining, expert systems, and artificial intelligence applications for decision support. Her work focuses on optimizing SQL and NoSQL systems, enhancing cloud database security, and leveraging AI and machine learning for large-scale data analysis. She has contributed extensively to international research projects, authored numerous peer-reviewed publications, and serves as a reviewer and editor for leading journals and conferences. Her expertise positions her as a prominent candidate for recognition in computing, IT innovation, and data-driven research excellence.

Citation Metrics (Scopus)

400

300

200

100

50

10

0

Citations
349

Documents
41

h-index
9

       🟦 Citations   🟥 Documents   🟩 h-index


View Scopus Profile
 View ORCID Profile
 View Google Scholar Profile

Featured Publications