Mr. Vivek Dwivedi | Machine learning | Research Excellence Award

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Mr. Vivek Dwivedi | Machine learning | Research Excellence Award

Slovak University of Technology in Bratislava | Slovakia

Mr. Vivek Dwivedi is an emerging researcher specializing in computer vision, adaptive camera systems, robotics, and intelligent imaging technologies, with a strong focus on real-time object detection and virtual teleportation systems. His work integrates machine learning, OpenCV, and embedded systems to develop computationally efficient solutions for dynamic visual environments. He has also contributed to research in mechatronics, haptic systems, and origami-inspired robotics. His academic output demonstrates growing impact, with Scopus indexing 12 documents, 25 citations, and an h-index of 3, while Google Scholar reports 37 citations and an h-index of 4, reflecting consistent scholarly advancement.

Citation Metrics ( Scopus )

40

30

20

10

0

Citations 25

Documents
12

h-index
3

                    ■ Citations          ■ i10-index           ■ h-index


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Featured Publications

Dr. Xianchen Liu | Machine Learning | Best Researcher Award

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Dr. Xianchen Liu | Machine Learning | Best Researcher Award

Researcher | Florida International University | United States

Dr. Xianchen Liu is a computer scientist specializing in machine learning, natural language processing, recommender systems, predictive analytics, and data-driven optimization. His research integrates deep learning architectures such as BERT, LSTM, attention mechanisms, and swarm intelligence to address challenges in sentiment analysis, financial risk prediction, dynamic pricing, and energy systems modeling. He has contributed to peer-reviewed journals including Systems and the Journal of Software Engineering and Applications, and presented work at international conferences. According to Scopus, he has 2 indexed documents with 3 citations and an h-index of 1; Google Scholar reports 17 citations with an h-index of 2.

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Featured Publications

Mr. Zeeshan Rasheed | Machine Learning | Research Excellence Award

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Mr. Zeeshan Rasheed | Machine Learning | Research Excellence Award

Lecturer Computer Science | Mir Chakar Khan Rind University Sibi Balochistan | Pakistan

Mr. Zeeshan Rasheed is a computer science researcher whose work spans machine learning, data intelligence, wireless networks, and AI-driven decision systems. His research focuses on optimizing network cooperation, developing neural models for sustainable wireless resource management, improving early disease prediction, and analyzing AI’s role in media and social systems. He has contributed to studies on sentiment analysis, intelligent network strategies, pandemic modelling, and crowdsourced data reliability. His scholarly output reflects a continuous commitment to advancing practical and socially relevant AI applications, supported by publications across multidisciplinary journals. His work also demonstrates growing academic impact with ongoing contributions to emerging technological challenges.

Citation Metrics (Google Scholar)

20

15

10

5

0

Citations
17

Documents
17

h-index
3

Citations
Documents
h-index


View Google Scholar Profile

Featured Publications

Avraham Lalum | Machine Learning | Best Researcher Award

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Mr. Avraham Lalum | Machine Learning | Best Researcher Award

PhD | University of Córdoba | Israel

Avraham (Avi) Lalum is a distinguished legal scholar and researcher specializing in the intersection of real estate law, artificial intelligence, and conflict resolution. His research explores advanced AI-driven models for risk management in real estate transactions, integrating decision-oriented mediation (DOM), behavioral analytics, and deep learning to enhance investment decision frameworks. Lalum’s scholarly contributions bridge the gap between legal regulation and computational modeling, offering innovative methodologies for explainable AI in property law, negotiation, and human–machine interaction. His studies emphasize how artificial intelligence can simulate human reasoning to mitigate financial risk and promote fairness in high-stakes negotiations. His works are widely recognized in Scopus and Web of Science-indexed journals, contributing significantly to the fields of law, data science, and behavioral AI. With a growing academic impact reflected in over 300 citations and an h-index of 6 on Scopus (and 9 on Google Scholar), Lalum’s publications demonstrate both theoretical depth and practical application in LegalTech and AI ethics.

Profile

ORCID

Featured Publications 

Lalum, A., López del Río, L. C., & Villamandos, N. C. (2024). Synthetic reality mapping of real estate using deep learning-based object recognition algorithms. SN Business & Economics, Springer.
Lalum, A., Caridad López del Río, L., & Ceular Villamandos, N. (2025). Multi-dimensional AI-based modeling of real estate investment risk: A regulatory and explainable framework for investment decisions. Mathematics, MDPI.

 

Mr. Zhenduo Meng | Machine Learning | Best Researcher Award

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Zhenduo Meng | Machine Learning | Best Researcher Award

Inner Mongolia University, China

Zhenduo Meng is a graduate student pursuing his M.Sc. in Electronic Information Engineering at the School of Electronic Information Engineering, Inner Mongolia University, with a strong academic foundation built during his B.Eng. studies in Automation at Guangxi University. His research primarily focuses on multi-agent reinforcement learning (MARL), deep reinforcement learning, cooperative control of multi-agent systems, and the broader applications of artificial intelligence in intelligent decision-making. He has actively participated in several research projects, where he contributed to the development of algorithms integrating attention mechanisms and value decomposition methods to improve collaboration efficiency in MARL environments. Recently, his research work, “DDWCN: A Dual-Stream Dynamic Strategy Modeling Network for Multi-Agent Elastic Collaboration,” was accepted for publication in Applied Sciences (2025), highlighting his innovative contributions in the field. Despite being at the early stage of his academic journey, his scholarly output includes 2 documents, and his current citation count stands at zero, reflecting the fresh and emerging nature of his research profile. His h-index is also recorded as zero, consistent with his recent entry into the publication landscape. Proficient in Python, MATLAB, PyTorch, and TensorFlow, along with strong command of both Chinese and English, Meng demonstrates promising potential for impactful contributions in intelligent systems research.

Profile: Scopus

Featured Publications

Meng, Z., Na, X., Wang, T., Liu, J., & Wang, W. (2025). DDWCN: A dual-stream dynamic strategy modeling network for multi-agent elastic collaboration.

Wang, T., Na, X., Nie, Y., Liu, J., Wang, W., & Meng, Z. (2025). Parallel task offloading and trajectory optimization for UAV-assisted mobile edge computing via hierarchical reinforcement learning. Drones, 9(2),

Md. Khabir Uddin Ahamed | Machine Learning | Best Researcher Award

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Mr. Md. Khabir Uddin Ahamed | Machine Learning | Best Researcher Award

Mr. Md. Khabir Uddin Ahamed – Lecturer, Jamalpur Science and Technology University, Bangladesh.

Md. Khabir Uddin Ahamed is a dynamic Bangladeshi academic and researcher in Computer Science & Engineering. Known for his contribution to data-driven technologies, he has authored several impactful publications in domains like machine learning, computer vision, and AI. With strong analytical and problem-solving skills, he’s actively engaged in academic instruction and cutting-edge research. He is currently a Lecturer at Jamalpur Science and Technology University. Khabir combines technical prowess with a passion for innovation, contributing to both academic and social sectors through technological projects and scientific publications.

Publication Profile

Scopus

ORCID

Google Scholar

Education Background

Md. Khabir Uddin Ahamed holds a B.Sc. and M.Sc. in Computer Science & Engineering from Jagannath University, where he secured the 2nd merit position in both undergraduate and postgraduate programs. His academic foundation is further solidified by earlier education from Govt. Science College and BCSIR High School under the Dhaka Board. His strong educational background has shaped his ability to undertake impactful research, particularly in artificial intelligence and data science, and contributed to his success as a university lecturer and researcher.

Professional Experience

Khabir began his teaching career as a Lecturer in the Department of Computer Science & Engineering at Bangladesh University (2022–2023). Since December 2023, he has been serving as a Lecturer at Jamalpur Science and Technology University. In his academic roles, he has taught core courses, guided student research, and contributed to institutional development. He has also participated in multiple training programs under the University Grants Commission of Bangladesh, focusing on modern teaching methods, digital compliance, and administrative tools for higher education.

Awards and Honors

While there are no direct individual award mentions, Khabir’s academic distinction—earning the 2nd merit rank in both B.Sc. and M.Sc.—reflects his scholastic excellence. Furthermore, his publications have earned significant citations, indicating international recognition of his research contributions. His training certifications from the University Grants Commission and Bangladesh Accreditation Council add further credibility to his professional qualifications, reflecting national-level validation and involvement in academic quality assurance systems.

Research Focus

Md. Khabir Uddin Ahamed’s research spans several high-impact areas within computer science, including machine learning, deep learning, data science, computer vision, and blockchain technology. His recent work has explored disease detection using deep learning, behavioral analysis on social media, and intelligent transportation systems. He is passionate about leveraging AI for societal benefit and continues to explore innovative applications of technology to solve real-world problems in agriculture, health, and cybersecurity through interdisciplinary collaboration.

Top Publications 

 

Prof. Dr. Metin Zontul | Machine Learning | Best Researcher Award

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Prof. Dr. Metin Zontul | Machine Learning | Best Researcher Award

Dean, Sivas University of Science and Technology, Turkey

Prof. Dr. Metin Zontul is a seasoned academic and researcher in the fields of machine learning, data mining, and intelligent systems, currently serving as Professor and Dean at the Faculty of Engineering and Natural Sciences, Sivas University of Science and Technology, Turkey. With over 30 years of academic experience, he has held various esteemed positions at several universities in Turkey and contributed significantly to national-level research projects, innovation in artificial intelligence, and academic leadership.

Publication Profile

Google Scholar

ORCID

🎓 Education Background

He earned his Ph.D. in Quantitative Methods in Business Administration (2004) from the Institute of Social Sciences, focusing his dissertation on clustering countries trading with Turkey using SOM-type artificial neural networks. He holds an M.Sc. in Computer-Aided Design, Manufacturing, and Programming (1996), where he analyzed local area network access protocols, and a B.Sc. in Computer Engineering (1993) from Middle East Technical University.

💼 Professional Experience

Prof. Zontul has held multiple academic ranks, starting as a Lecturer at Cumhuriyet University (1994–2005) and advancing to Assistant, Associate, and then Professor at institutions such as Istanbul Aydın University, Arel University, Ayvansaray University, and Topkapi University. He has been a key academic leader, serving as Dean and Department Chair across several faculties. Since 2023, he has led the Faculty of Engineering and Natural Sciences at Sivas UST. He also supervises graduate theses and collaborates on research with TUBITAK and other industry-linked projects.

🏆 Awards and Honors

Prof. Zontul has received Publication Incentive Awards from Istanbul Aydın University in 2014 and 2016 for his scholarly contributions. He is a former member of IEEE and holds a 2024 patent for a Personnel Assignment and Routing System related to unit failure and maintenance operations.

🔬 Research Focus

His research interests span machine learning, deep learning, data mining, signal processing, natural language processing, and intelligent systems. He has contributed extensively to the scientific community through 25+ peer-reviewed journal articles, 20+ conference papers, and collaborative projects involving academia and industry. His supervision of numerous theses and his involvement in over 30 national research projects reflect his commitment to practical and academic advancements in AI.

🔚 Conclusion

Prof. Dr. Metin Zontul stands as a multifaceted academician blending research, leadership, and innovation. His significant contributions to AI, education, and national research initiatives have cemented his reputation as a leading scholar in his field.

📚 Top Publications 

  1. Application of artificial intelligence neural network modeling to predict the generation of domestic, commercial and construction wastes (2021)
    Journal: Waste Management & Research
    Cited by: 92
    Co-authors: G. Coskuner, M.S. Jassim, S. Karateke

  2. Comparative performance analysis of support vector regression and artificial neural network for prediction of municipal solid waste generation (2022)
    Journal: Waste Management & Research
    Cited by: 49
    Co-authors: M.S. Jassim, G. Coskuner

  3. Urban bus arrival time prediction: A review of computational models (2013)
    Journal: International Journal of Recent Technology and Engineering (IJRTE)
    Cited by: 123
    Co-author: M. Altinkaya

  4. Measuring the efficiency of telecommunication sectors of OECD countries using data envelopment analysis (2005)
    Journal: CU Journal of Economics and Administrative Sciences
    Cited by: 41
    Co-authors: O. Kaynar, H. Bircan

  5. Wind speed forecasting using reptree and bagging methods in Kirklareli-Turkey (2013)
    Journal: Journal of Theoretical and Applied Information Technology
    Cited by: 35
    Co-authors: F. Aydin, G. Dogan, S. Sener, O. Kaynar

  6. The prediction of the ZnNi thickness and Ni% of ZnNi alloy electroplating using a machine learning method (2021)
    Journal: Transactions of the IMF
    Cited by: 34
    Co-authors: R. Katirci, H. Aktas

  7. A smart and mechanized agricultural application: From cultivation to harvest (2022)
    Journal: Applied Sciences
    Cited by: 31
    Co-authors: F. Kiani, G. Randazzo, I. Yelmen, A. Seyyedabbasi, S. Nematzadeh, F.A. Anka, et al.

 

 

Mr. Ahmad Faraz Hussain | Machine learning | Best Scholar Award

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Mr. Ahmad Faraz Hussain | Machine learning | Best Scholar Award

PhD student, Zhejiang university, China

Ahmad Faraz Hussain is an accomplished researcher and engineer specializing in audio signal processing, speaker recognition, and wireless sensor networks. With a strong academic background and extensive technical experience, he has contributed significantly to the field of electronics and information engineering. His work spans research, teaching, and industry, reflecting his passion for innovation and education.

Publication Profile

Scopus

🎓 Education:

Ahmad Faraz Hussain earned his Master of Science in Electronics & Information Engineering from the South China University of Technology, China (2017–2019), achieving an impressive 90%. His thesis focused on “Speaker Recognition with Emotional Speech,” showcasing his expertise in audio processing. He completed his Bachelor of Science in Electrical Engineering from the University of Engineering and Technology, Peshawar, Pakistan (2009–2014), with a thesis on “ZigBee-Based Wireless Sensor Network for Building Safety Monitoring.”

💼 Professional Experience:

Ahmad has a diverse professional journey, beginning as a Research Assistant at the South China University of Technology (2017–2019), where he worked on cutting-edge projects in speech recognition. Before that, he served as a Lecturer at Polytechnical College Kohat (2016–2017), imparting knowledge to aspiring engineers. His technical expertise was further honed during his two-year tenure as a Technical Engineer at PTCL, Pakistan, where he worked on telecommunications and networking solutions.

🏆 Awards and Honors:

Ahmad was a recipient of the prestigious CSC Scholarship, which enabled him to pursue his master’s degree in China. His academic excellence and dedication to research have earned him recognition in both academic and professional circles.

🔬 Research Focus:

Ahmad’s research interests lie in audio signal processing, speaker recognition, speech recognition, and wireless sensor networks. His work focuses on developing advanced methodologies for improving speech-based systems and enhancing security through smart sensor networks. His contributions to these fields are evident in his multiple publications and research projects.

🔚 Conclusion:

Ahmad Faraz Hussain is a dedicated researcher and engineer with a strong foundation in speech and wireless sensor technologies. His academic achievements, professional experience, and research contributions highlight his commitment to innovation and education. With a passion for higher learning and community service, he continues to make impactful contributions to the field of electronics and information engineering. 🚀

📚 Publications:

Three-Dimensional Dynamic Positioning Using a Novel Lyapunov-Based Model Predictive Control for Small Autonomous Surface/Underwater Vehicles

Fish Detection and Classification Based on Improved ViT

ZigBee-Based Wireless Sensor Network for Building Safety Monitoring – Published in the Journal of TWASP. Read here.

Speaker Recognition with Emotional Speech – Published in GSJ. Read here.

Speech Emotion Recognition – Under review.

ZigBee and GSM-Based Security System for Business Places– Accepted for publication.

Internet of Things-Based Information System for Smart Wireless Sensor Healthcare Applications – Submitted for review.

Hsiu Hsia Lin | Machine learning | Best Researcher Award

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Prof. Hsiu Hsia Lin | Machine learning | Best Researcher Award

Research Fellow, Chang Gung Memorial Hospital, Taiwan

Dr. Hsiu-Hsia Lin is a dedicated Research Fellow at the Craniofacial Research Center, Chang Gung Memorial Hospital, Taiwan, and an Adjunct Assistant Professor at the Graduate Institute of Dental and Craniofacial Science, Chang Gung University. With a strong foundation in AI and 3D craniofacial image processing, her research contributes significantly to advancements in orthognathic surgery. Dr. Lin’s expertise in surgical navigation and CAD/CAM-assisted surgery is pivotal in improving craniofacial surgical outcomes. 🌟

Publication Profile

Education:

Dr. Lin earned her Ph.D. in Computer Science and Engineering from National Chung Hsing University, Taiwan, following a Master’s in Computer Science from Tunghai University. Her academic journey is deeply rooted in computer science, blending AI with craniofacial research. 🎓📚

Experience:

Dr. Lin has held key research positions, including Assistant Research Fellow and Postdoctoral Fellow at the Craniofacial Research Center, Chang Gung Memorial Hospital. Her postdoctoral work also extended to the Department of Computer Science and Engineering at National Chung Hsing University. Her extensive experience has helped bridge the gap between AI technology and clinical applications. 💼🔬

Research Focus:

Dr. Lin’s research revolves around Pattern Recognition, Artificial Intelligence, and 3D Craniofacial Image Processing. She specializes in computer-aided surgical simulation for orthognathic surgery, surgical navigation, and CAD/CAM-assisted procedures, aiming to optimize outcomes in facial surgery. 🧠💻

Awards and Honors:

Dr. Lin has received multiple recognitions for her contributions to craniofacial research and AI in surgery. Her work continues to shape modern surgical approaches, particularly in orthognathic surgery, enhancing patient outcomes. 🏆👏

Publication Top Notes:

Dr. Lin’s publications focus on integrating AI with medical applications, particularly in 3D craniofacial analysis and orthognathic surgery. Her studies offer novel methods for surgical planning, facial attractiveness assessment, and facial symmetry evaluation.

Quantification of facial symmetry in orthognathic surgery (Dec. 2024) in Comput Biol Med., cited by 5 articles. DOI

Average 3D virtual sk

eletofacial model for surgery planning (Feb. 2024) in Plast Reconstr Surg., cited by 3 articles. DOI

Facial attractiveness assessment using transfer learning (Jan. 2024) in Pattern Recognit., cited by 4 articles. DOI

Optimizing Orthognathic Surgery (Nov. 2023) in J. Clin. Med., cited by 6 articles. DOI

Single-Splint, 2-Jaw Orthognathic Surgery (Nov. 2023) in J Craniofac Surg., cited by 2 articles. DOI

Applications of 3D imaging in craniomaxillofacial surgery (Aug. 2023) in Biomed J., cited by 7 articles. DOI

Facial Beauty Assessment using Attention Mechanism (Mar. 2023) in Diagnostics, cited by 8 articles. DOI

 

Syed Ijaz Ul Haq | Machine Learning | Best Researcher Award

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Dr. Syed Ijaz Ul Haq | Machine Learning | Best Researcher Award 

Research associate, Shandong University of Technology, China

Syed Ijaz Ul Haq is a dedicated Research Assistant in Agronomy at Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan, since September 2021. Currently pursuing a Ph.D. in Agriculture Engineering and Food Science at Shandong University of Technology, China, he is passionate about advancing research in remote sensing, artificial intelligence, and deep learning. With a commitment to excellence and professional development, Syed aims to explore innovative solutions in agriculture. 🌱📚

Publication Profile

ORCID

Strengths for the Award

  1. Specialized Research Interests: Syed has a clear focus on Remote Sensing, AI, and Deep Learning, which are critical areas in modern agricultural research. His work on machine learning techniques for pest detection and weed analysis demonstrates innovative applications of technology in agriculture.
  2. Academic Background: Currently pursuing a Ph.D. in Agricultural Engineering and Food Science at Shandong University of Technology, Syed is in an excellent position to contribute cutting-edge research to the field.
  3. Professional Experience: His role as a Research Assistant at Pir Mehr Ali Shah Arid Agriculture University allows him to gain practical experience and engage with ongoing research projects, enhancing his research skills.
  4. Publication Record: With multiple publications in reputable journals, including articles on trace elements’ effects on crop growth and the use of AI for weed detection, he demonstrates the ability to conduct and disseminate impactful research.
  5. Peer Review Engagement: His involvement as a reviewer for the American Society of Plant Biologists reflects recognition by peers and contributes to his professional development.

Areas for Improvement

  1. Broader Research Impact: While Syed has several publications, expanding his research to include interdisciplinary collaborations or more diverse agricultural challenges could enhance his visibility and impact in the field.
  2. Networking and Collaboration: Actively seeking collaborations with other researchers or institutions could provide Syed with additional insights and resources, fostering a more extensive research network.
  3. Professional Development: Attending more international conferences and workshops could enhance his skills and provide opportunities for exposure to global trends in agricultural research and technology.
  4. Outreach and Application of Research: Engaging with local communities or agricultural practitioners to apply his findings could bridge the gap between research and real-world application, leading to significant societal impacts.

Education

Syed is currently enrolled in a Ph.D. program in Agriculture Engineering and Food Science at Shandong University of Technology, Zibo, Shandong, China, where he has been studying since July 2022. His academic focus revolves around integrating advanced technologies to enhance agricultural practices. 🎓🌾

Experience

Since September 2021, Syed has served as a Research Assistant in Agronomy at Pir Mehr Ali Shah Arid Agriculture University, where he contributes to various agricultural research projects, gaining valuable experience and insights into the field. His role involves collaborating with researchers to explore sustainable agricultural practices and technologies. 🧑‍🔬🌍

Research Focus

Syed’s research primarily focuses on the application of remote sensing, AI, and deep learning techniques in agriculture. His work aims to improve crop yield, pest detection, and weed management, making significant contributions to sustainable farming practices. 🤖🌿

Awards and Honours

Syed has been recognized for his contributions to agricultural research, including serving as a Reviewer for the American Society of Plant Biologists since 2021. His academic excellence is reflected in his ongoing Ph.D. studies, showcasing his dedication to advancing the field. 🏆📜

Publications

Influence of Trace Elements (Co, Ni, Se) on Growth, Nodulation and Yield of Lentil
Published in Polish Journal of Environmental Studies, 2024
Cited by: Crossref

Identification of Pest Attack on Corn Crops Using Machine Learning Techniques
Published in 2023
Cited by: Crossref

Weed Detection in Wheat Crops Using Image Analysis and Artificial Intelligence (AI)
Published in Applied Sciences, 2023
Cited by: Crossref

Conclusion

Syed Ijaz Ul Haq shows strong potential as a candidate for the Research for Best Researcher Award due to his focused research interests, current academic pursuits, publication record, and peer engagement. To further enhance his candidacy, he should consider broadening his research scope, expanding his professional network, and increasing the real-world applicability of his research findings. If he continues on this trajectory, he has the potential to make substantial contributions to agricultural research, making him a deserving recipient of this award.