Dengtian Yang | Computer Science | Best Researcher Award

Published on by NESIN Awards

Mr. Dengtian Yang | Computer Science | Best Researcher Award

Student at Institute of Microelectronics of the Chinese Academy of Sciences, China

Yang Dengtian is a promising researcher in the field of Circuit and System, currently pursuing his Ph.D. at the Institute of Microelectronics of the Chinese Academy of Sciences. His research interests focus on hardware-software co-optimization, object detection, and hardware acceleration, with key contributions in developing post-processing accelerators for object detection and improving micro-architecture design for GPGPU. Yang’s project experience spans from UAV object detection to the design of System on Chip (SoC) and the deployment of deep learning models on specialized hardware like NVDLA IP. His dedication to advancing technology is reflected in his published works in renowned journals. Yang is a proactive learner, often sharing his findings on blogs, contributing to the academic community’s growth. His work is poised to have a significant impact in fields such as artificial intelligence, hardware design, and computer vision.

Professional Profile 

Education

Yang Dengtian began his academic journey at Xi’an Jiaotong University, where he earned his Bachelor’s degree in Electronic Science and Technology in 2020. His strong foundational knowledge in electronics laid the groundwork for his current research. In 2020, he began his Ph.D. at the Institute of Microelectronics of the Chinese Academy of Sciences, specializing in Circuit and System. His doctoral research has primarily focused on hardware-software co-optimization and advanced object detection systems, areas that combine his deep understanding of both electronics and cutting-edge computing techniques. Yang’s education has been integral in shaping his research pursuits, allowing him to contribute valuable insights into hardware acceleration and the optimization of machine learning systems. His academic journey is ongoing, with an expected completion of his Ph.D. in 2025.

Professional Experience

Yang has worked on several innovative projects throughout his academic career. His recent project, “Learn and Improve Vortex GPGPU,” focuses on understanding GPGPU micro-architecture design and developing improvements for performance optimization. Another notable project was the “Post-Processing Accelerator for Object Detection,” where he investigated hardware-software co-optimization methods, contributing to the development of a unified accelerator system for object detection. In 2023, Yang worked on the “SoC Building and Yolox-Nano Network Deployment Based on NVDLA IP,” where he built an SoC with NVDLA IP and deployed a Yolox-Nano model on a specialized hardware platform. Yang has also worked on solutions to reduce off-chip memory accesses for CNN inference and deployed deep learning models using Vitis-AI. These experiences, along with his publications in renowned journals, highlight his advanced technical expertise and problem-solving abilities in cutting-edge electronics and AI research.

Research Interest

Yang Dengtian’s primary research interest lies in the intersection of Circuit and System design, hardware-software co-optimization, and artificial intelligence (AI). His work focuses on developing hardware accelerators for deep learning applications, particularly in object detection and micro-architecture optimization. He is passionate about creating more efficient systems for processing large-scale data, especially in environments that require real-time processing, such as unmanned aerial vehicles (UAVs) and embedded systems. Yang’s research includes developing GPGPU micro-architectures, improving System on Chip (SoC) designs, and enhancing the deployment of deep learning models on specialized hardware, such as NVDLA IP. His research aims to bridge the gap between hardware capabilities and software needs, making AI applications more accessible and efficient. He is particularly interested in creating unified frameworks for hardware-software co-design, which could significantly advance machine learning and computer vision technologies.

Awards and Honors

Yang Dengtian’s outstanding contributions to research have been recognized through various accolades. His publication in reputable journals, such as Information and IEICE Transactions on Information and Systems, demonstrates the impact of his work in the field of hardware and software co-optimization. While still early in his career, Yang’s commitment to research excellence has already led to numerous recognitions in his academic community. He has also been acknowledged for his innovative projects in hardware acceleration for AI applications, particularly in the development of post-processing accelerators for object detection. Yang’s work is a testament to his technical expertise and his potential for future awards as his research continues to make significant strides in the fields of electronics, AI, and machine learning. Given his promising trajectory, Yang is likely to receive further honors as his doctoral studies progress and his body of work grows.

Conclusion

Yang Dengtian is undoubtedly a strong contender for the Best Researcher Award due to his innovative approach to research, technical expertise, and significant contributions to the field of hardware-software co-design and optimization. His passion for learning, combined with his publications and project experience, highlights his potential to make substantial advancements in his area of study. However, expanding his collaborations and enhancing the practical impact of his research could further solidify his status as a leading researcher in the field.

Recommendation: Yang Dengtian is highly deserving of the Best Researcher Award, with his strengths outweighing areas for improvement. His future contributions are expected to have a lasting impact in the fields of object detection, hardware acceleration, and micro-architecture design.

Publications Top Noted

  • Title: Nano-carriers of combination tumor physical stimuli-responsive therapies
    Authors: W Jin, C Dong, D Yang, R Zhang, T Jiang, D Wu
    Journal: Current Drug Delivery
    Volume & Issue: 17 (7), 577-587
    Year: 2020
    Cited by: 7
  • Title: Object Detection Post Processing Accelerator Based on Co-Design of Hardware and Software
    Authors: D Yang, L Chen, X Hao, Y Zhang
    Journal: Information
    Volume & Issue: 16 (1), 63
    Year: 2025
    Cited by: Not yet cited (as of 2025)

 

Volodymyr Polishchuk | Computer Science | Best Researcher Award

Published on by NESIN Awards

Prof. Volodymyr Polishchuk | Computer Science | Best Researcher Award

Uzhhorod National University, Ukraine

Volodymyr Polishchuk is a distinguished academic specializing in information technology, fuzzy systems, and decision-making models. Currently serving as a Professor at both Uzhhorod National University in Ukraine and the Technical University of Košice in Slovakia, he has made significant contributions to the fields of artificial intelligence, risk assessment, and sustainable tourism. With a career spanning over a decade, he has co-authored numerous publications, including journal articles and book chapters, focusing on the application of advanced decision models in various sectors. His research is internationally recognized, and he is an active member of several academic networks. He is known for his interdisciplinary approach, bridging information technology with real-world challenges such as healthcare, aviation education, and urban development.

Professional Profile 

Education

Volodymyr Polishchuk holds a prestigious Doctor of Sciences (DrSc.) degree from Uzhhorod National University, where he also completed his undergraduate and graduate education. His academic journey in information technology, mathematics, and fuzzy systems laid a strong foundation for his future research and teaching. As a professor at the university, he has guided numerous students and collaborated on innovative projects. Additionally, his academic credentials are complemented by his position at the Technical University of Košice in Slovakia, where he continues to contribute to cutting-edge research in his fields of expertise. His educational background supports his broad interdisciplinary approach, allowing him to address complex problems in various domains such as tourism, healthcare, and risk management.

Professional Experience

Professor Polishchuk has been a dedicated faculty member at Uzhhorod National University since 2011, where he teaches and conducts research at the Faculty of Information Technology. Over the years, he has gained recognition for his expertise in decision-making models and fuzzy systems. In addition to his role at Uzhhorod, he has been a professor at the Technical University of Košice, Slovakia. His professional experience extends beyond teaching, as he has collaborated on numerous international research projects and published widely in top-tier journals. He has also worked on hybrid decision models for risk assessment in sectors such as sustainable tourism, healthcare, and aviation education. His leadership in academic research has earned him recognition through various academic platforms, and he continues to actively engage with the global research community.

Research Interests

Volodymyr Polishchuk’s research primarily focuses on information technology, fuzzy systems, and decision-making models, with a particular emphasis on their practical applications across various industries. He is deeply engaged in developing hybrid models for evaluating complex processes, such as tourism sustainability, risk assessment, and healthcare outcomes. His work also explores the integration of artificial intelligence in decision-making, specifically in aviation education and urban development. Additionally, he is interested in the application of multicriteria decision analysis (MCDA) in solving real-world challenges. Polishchuk’s interdisciplinary approach allows him to connect cutting-edge technology with pressing global issues, contributing valuable insights to sectors like smart cities, start-up financing, and pandemic management. His research has significant implications for optimizing resource allocation, improving system efficiency, and mitigating risks in both public and private sectors.

Awards and Honors

Throughout his academic career, Volodymyr Polishchuk has earned several prestigious honors and recognition for his contributions to research and education. His interdisciplinary approach to problem-solving has led to numerous successful collaborations with leading academic and industry experts across Europe. He has been acknowledged by his peers for his innovative contributions to the fields of fuzzy logic, decision support systems, and sustainability models. Polishchuk’s research papers are widely cited, indicating the significant impact his work has had on the academic community. His exceptional leadership in research has also helped foster international collaborations, particularly in the development of sustainable tourism models and risk assessment frameworks for emerging sectors. His continued excellence in academia and research is further demonstrated by his involvement in high-impact projects and his active participation in global conferences.

Publications Top Noted

  1. Artificial Intelligence Technology for Assessing the Practical Knowledge of Air Traffic Controller Students Based on Their Responses in Multitasking Situations
    • Authors: Antoško, M., Polishchuk, V., Kelemen, M., Korniienko, A., Kelemen, M.
    • Year: 2025
    • Journal: Applied Sciences (Switzerland)
    • Volume: 15(1), 308
    • Citations: 0
  2. A large-scale decision-making model for the expediency of funding the development of tourism infrastructure in regions
    • Authors: Skare, M., Gavurova, B., Polishchuk, V.
    • Year: 2025
    • Journal: Expert Systems
    • Volume: 42(1), e13443
    • Citations: 1
  3. On Convergence of the Uniform Norm and Approximation for Stochastic Processes from the Space Fψ(Ω)
    • Authors: Rozora, I., Mlavets, Y., Vasylyk, O., Polishchuk, V.
    • Year: 2024
    • Journal: Journal of Theoretical Probability
    • Volume: 37(2), pp. 1627–1653
    • Citations: 0
  4. THE IMPACT OF DIGITAL DISINFORMATION ON QUALITY OF LIFE: A FUZZY MODEL ASSESSMENT
    • Authors: Gavurova, B., Moravec, V., Hynek, N., Petruzelka, B., Stastna, L.
    • Year: 2024
    • Journal: Technological and Economic Development of Economy
    • Volume: 30(4), pp. 1120–1145
    • Citations: 0
  5. An information-analytical system for assessing the level of automated news content according to the population structure – A platform for media literacy system development
    • Authors: Gavurova, B., Skare, M., Hynek, N., Moravec, V., Polishchuk, V.
    • Year: 2024
    • Journal: Technological Forecasting and Social Change
    • Volume: 200, 123161
    • Citations: 0
  6. Decision Support System Regarding the Possibility of Financing Cross-Border Cooperation Projects
    • Authors: Polishchuk, V., Kelemen, M., Polishchuk, I., Kelemen, M.
    • Year: 2024
    • Conference: CEUR Workshop Proceedings
    • Volume: 3702, pp. 58–71
    • Citations: 0
  7. Hybrid Mathematical Model of Risk Assessment of UAV Flights Over Airports
    • Authors: Polishchuk, V., Kelemen, M., Kelemen, M., Scerba, M.
    • Year: 2024
    • Conference: New Trends in Civil Aviation
    • Citations: 0
  8. A Fuzzy Multicriteria Model of Sustainable Tourism: Examples From the V4 Countries
    • Authors: Skare, M., Gavurova, B., Polishchuk, V.
    • Year: 2024
    • Journal: IEEE Transactions on Engineering Management
    • Volume: 71, pp. 12182–12193
    • Citations: 6
  9. Fuzzy multicriteria evaluation model of cross-border cooperation projects under resource curse conditions
    • Authors: Skare, M., Gavurova, B., Polishchuk, V.
    • Year: 2023
    • Journal: Resources Policy
    • Volume: 85, 103871
    • Citations: 3
  10. A fuzzy model for evaluating the level of satisfaction of tourists regarding accommodation establishments according to social class on the example of V4 countries
  • Authors: Skare, M., Gavurova, B., Polishchuk, V., Nawazish, M.
  • Year: 2023
  • Journal: Technological Forecasting and Social Change
  • Volume: 193, 122609
  • Citations: 7

Naeem Ullah | Computer Science | Best Researcher Award

Published on by NESIN Awards

Mr. Naeem Ullah | Computer Science | Best Researcher Award

PhD Student at Software Engineering Research Group (SERG-UOM) University of Malakand, Pakistan

Mr. Naeem Ullah is a dedicated academic and researcher currently pursuing a PhD in Computer Science, with a focus on cybersecurity challenges in vehicle-to-vehicle communication from a software engineering perspective. Holding a strong academic record with a CGPA of 3.75/4.00, he has presented his research at international forums, such as the 2nd Annual International Workshop on Software Engineering, where he shared his Multivocal Literature Review (MLR) protocol on cybersecurity culture. Mr. Ullah has also received recognition for his teaching excellence, earning the Best Teacher Award in 2018. His work experience includes roles as a lecturer at the University Model College KPK, part-time tutor at Allama Iqbal Open University, and facilitator for continuous professional development programs for teachers. His research, currently under review, addresses crucial cybersecurity issues in vehicle-to-vehicle communications. Mr. Ullah’s commitment to furthering his knowledge is evident through multiple certifications in data science, networking, and cybersecurity.

Professional Profile 

Education

Mr. Naeem Ullah has a strong educational background in Computer Science. He is currently pursuing a PhD in Computer Science with a focus on cybersecurity challenges in vehicle-to-vehicle communication, maintaining an impressive CGPA of 3.75/4.00. His research aims to develop a mitigation model for cybersecurity issues in connected vehicle systems, reflecting his deep engagement with current technological challenges. Mr. Ullah completed his Master’s degree in Computer Science in 2019, achieving a CGPA of 3.7/4.00, with his thesis titled Software Development Process Improvement Model for Small Pakistani Software Development Companies. He also holds a Bachelor’s degree in Computer Science from 2014, with a CGPA of 3.62/4.00. His final year project, Auction Management System, showcased his ability to apply practical solutions to real-world problems. Mr. Ullah’s academic journey is marked by consistent excellence and a strong commitment to advancing his expertise in the field of computer science.

Professional Experience

Mr. Naeem Ullah has accumulated diverse professional experience in both academic and research roles. He has served as a Lecturer in Computer Science at the University Model College KPK, Peshawar, Pakistan, where he taught and mentored students in various computer science subjects. In addition, he has worked as a part-time tutor for Allama Iqbal Open University, Islamabad, since 2022, focusing on Information and Communication Technologies (ICT). Mr. Ullah has also contributed to teacher development programs, serving as a facilitator for the Continuous Professional Development (CPD) of Primary School Teachers (PSTs) through the Provincial Institute of Teacher Education (PITE) in KPK. His role as a part-time researcher at the Department of Computer Science and IT at the University of Malakand further underscores his involvement in academic research. Earlier in his career, he worked as a Secondary School Teacher at the Elementary and Secondary Education Department, KPK. His experiences reflect a blend of teaching, research, and educational development.

Research Interest

Mr. Naeem Ullah’s research interests primarily focus on cybersecurity, particularly in the context of emerging technologies such as vehicle-to-vehicle (V2V) communication. His PhD research investigates cybersecurity challenges and proposes mitigation models for securing V2V communication systems from a software engineering perspective. This area of research is highly relevant due to the increasing integration of connected vehicles and the need for secure communication protocols to protect sensitive data. Additionally, Mr. Ullah is interested in software engineering, with a particular emphasis on improving software development processes for small software companies in Pakistan, as demonstrated in his Master’s thesis. He has also contributed to the field of cybersecurity culture through his work on a Multivocal Literature Review (MLR) protocol, which identifies cybersecurity challenges and best practices in V2V communication. His research endeavors aim to address critical issues in both cybersecurity and software engineering, contributing to the development of safer, more efficient technologies.

Award and Honor

Mr. Naeem Ullah has received notable recognition for his academic and professional achievements. In 2022, he presented his Multivocal Literature Review (MLR) Protocol at the 2nd Annual International Workshop on Software Engineering (WSE-2022), organized by the Software Engineering Research Group at the University of Malakand. This presentation, focused on Cybersecurity Culture, showcased his expertise and contribution to the field of cybersecurity. Additionally, Mr. Ullah earned the prestigious Best Teacher Award from the Director of Elementary and Secondary Education, KPK, Pakistan, in 2018. This recognition highlights his excellence in teaching and his commitment to fostering the growth and development of his students. These awards and honors reflect Mr. Ullah’s dedication to advancing both his academic research and educational practices, demonstrating his commitment to the fields of computer science and cybersecurity while contributing positively to the educational community.

Conclusion

Naeem Ullah is a promising candidate for the Best Researcher Award, with a solid academic record, a focused and impactful research topic, and a commitment to both education and professional development. His strengths lie in his dedication to advancing cybersecurity research in emerging technologies like vehicle-to-vehicle communication and his capacity for leadership in educational initiatives. To further enhance his candidacy, Naeem could focus on increasing his research output, expanding his research scope, and engaging more in international collaborations to elevate the impact of his work.

Publications Top Noted

  • Title: Solutions to Cybersecurity Challenges in Secure Vehicle-to-Vehicle Communications: A Multivocal Literature Review
    Authors: Naeem Ullah, S.U. Khan, M. Niazi, A.A. Khan, J.A. Nasir
    Journal: Information and Software Technology
    Year: 2025
    Volume: 179
    Article ID: 107639
    Citations: 0
  • Title: Challenges and Their Practices in Adoption of Hybrid Cloud Computing: An Analytical Hierarchy Approach
    Authors: S.U. Khan, H.U. Khan, Naeem Ullah, R.A. Khan
    Journal: Security and Communication Networks
    Year: 2021
    Article ID: 1024139
    Citations: 2
  • Title: Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review
    Authors: S. Nazir, Y. Ali, Naeem Ullah, I. García-Magariño
    Journal: Wireless Communications and Mobile Computing
    Year: 2019
    Article ID: 5931315
    Citations: 138
  • Title: Practices for Clients in the Adoption of Hybrid Cloud
    Authors: S.U. Khan, Naeem Ullah
    Journal: Proceedings of the Pakistan Academy of Sciences: Part A
    Year: 2017
    Volume: 54(1A)
    Pages: 13–32
    Citations: 3

Hossein Nematzadeh | Computer Science | Best Researcher Award

Published on by NESIN Awards

Dr. Hossein Nematzadeh | Computer Science | Best Researcher Award

Assist Prof at Universidad de Malaga, Spain

Dr. Hossein Nematzadeh is an accomplished researcher and academic with a Ph.D. in Computer Science from the University of Technology, Malaysia. He is currently an Assistant Professor at the Modern College of Business and Science in Oman, with prior experience as a researcher at Universidad de Málaga, Spain, and an assistant professor at Islamic Azad University, Iran. His research interests span Data Science, Artificial Intelligence, Cryptography, and Software Engineering, with a particular focus on explainable AI, feature selection, evolutionary algorithms, and image encryption. Dr. Nematzadeh has published extensively in high-impact journals, contributing to advancements in AI and machine learning. He is also an experienced educator, having taught a wide array of computer science courses at various academic levels. With expertise in technologies like Python, MATLAB, and AWS, he is committed to both advancing research and mentoring the next generation of computer scientists.

Professional Profile 

Education

Dr. Hossein Nematzadeh has a strong academic foundation in Computer Science, having completed his Ph.D. at the University of Technology, Malaysia in 2014. Prior to his doctoral studies, he earned his Master’s degree from the same institution in 2009, further solidifying his expertise in the field. Dr. Nematzadeh also holds a Bachelor’s degree from Mazandaran University of Science and Technology, obtained in 2007. His educational journey reflects a deep commitment to the study of computer science, particularly in areas such as Artificial Intelligence, Data Science, and Cryptography. Throughout his academic career, he has gained a robust understanding of both theoretical and practical aspects of the field, which has informed his subsequent research and teaching. This solid educational background, combined with his ongoing research contributions, enables him to be a leader in his academic and professional endeavors.

Professional Experience

Dr. Hossein Nematzadeh has extensive professional experience in academia and research. He is currently serving as an Assistant Professor at the Modern College of Business and Science in Oman, where he teaches and supervises students in the field of Computer Science. Prior to this role, he was a researcher at Universidad de Málaga in Spain from 2021 to 2024, contributing to several high-impact research projects in Artificial Intelligence and Data Science. From 2012 to 2021, he served as an Assistant Professor at Islamic Azad University in Iran, where he taught various computer science courses and engaged in research activities. Throughout his career, Dr. Nematzadeh has built a reputation as both an educator and a researcher, publishing extensively in leading journals and presenting his work in international forums. His expertise spans across Data Science, Artificial Intelligence, and Cryptography, making him a prominent figure in these fields.

Research Interest

Dr. Hossein Nematzadeh’s research interests lie at the intersection of Data Science, Artificial Intelligence, Cryptography, and Software Engineering. He is particularly focused on developing advanced techniques in explainable AI, feature selection, and noise detection, with an emphasis on making AI models more interpretable and reliable. His work in evolutionary algorithms and fuzzy logic explores ways to optimize decision-making processes and improve system performance. Dr. Nematzadeh is also passionate about cryptography, specifically in areas such as image encryption, which contributes to enhancing data security in digital environments. Additionally, he has a strong interest in software engineering, with research dedicated to verification and validation processes, as well as the application of Petri nets to model and analyze complex systems. His research aims to push the boundaries of AI and machine learning, providing solutions to both theoretical and practical challenges in these rapidly evolving fields.

Award and Honor

Dr. Hossein Nematzadeh has earned recognition for his contributions to research and academia throughout his career. He has received several honors for his work in the fields of Data Science, Artificial Intelligence, and Cryptography, particularly for his research on explainable AI and feature selection methods. Dr. Nematzadeh’s scholarly impact is reflected in his publications in prestigious journals such as Engineering Applications of Artificial Intelligence and Knowledge-Based Systems. His work has been widely cited, demonstrating the influence of his research on the scientific community. In addition to his academic accomplishments, Dr. Nematzadeh has been actively involved in mentoring students and contributing to the advancement of his field through teaching and supervision. His dedication to fostering new talent in Computer Science and his continuous pursuit of research excellence have earned him respect within academic circles, making him a highly regarded figure in the global academic and research community.

Publications Top Noted

  • Title: Medical image encryption using a hybrid model of modified genetic algorithm and coupled map lattices
    Authors: H Nematzadeh, R Enayatifar, H Motameni, FG Guimarães, VN Coelho
    Year: 2018
    Cited by: 157
  • Title: A hybrid feature selection method based on information theory and binary butterfly optimization algorithm
    Authors: Z Sadeghian, E Akbari, H Nematzadeh
    Year: 2021
    Cited by: 116
  • Title: Heuristic filter feature selection methods for medical datasets
    Authors: M Alirezanejad, R Enayatifar, H Motameni, H Nematzadeh
    Year: 2020
    Cited by: 78
  • Title: Binary search tree image encryption with DNA
    Authors: H Nematzadeh, R Enayatifar, M Yadollahi, M Lee, G Jeong
    Year: 2020
    Cited by: 72
  • Title: Frequency based feature selection method using whale algorithm
    Authors: H Nematzadeh, R Enayatifar, M Mahmud, E Akbari
    Year: 2019
    Cited by: 66
  • Title: Emergency role-based access control (E-RBAC) and analysis of model specifications with alloy
    Authors: F Nazerian, H Motameni, H Nematzadeh
    Year: 2019
    Cited by: 52
  • Title: Predicting air pollution in Tehran: Genetic algorithm and back propagation neural network
    Authors: M Asghari, H Nematzadeh
    Year: 2016
    Cited by: 51
  • Title: A novel image security technique based on nucleic acid concepts
    Authors: M Yadollahi, R Enayatifar, H Nematzadeh, M Lee, JY Choi
    Year: 2020
    Cited by: 33
  • Title: Mapping to convert activity diagram in fuzzy UML to fuzzy petri net
    Authors: H Motameni, A Movaghar, I Daneshfar, H Nemat Zadeh, J Bakhshi
    Year: 2008
    Cited by: 30
  • Title: Automatic ensemble feature selection using fast non-dominated sorting
    Authors: S Abasabadi, H Nematzadeh, H Motameni, E Akbari
    Year: 2021
    Cited by: 28
  • Title: A mixed solution-based high agreement filtering method for class noise detection in binary classification
    Authors: M Samami, E Akbari, M Abdar, P Plawiak, H Nematzadeh, ME Basiri, …
    Year: 2020
    Cited by: 24
  • Title: Comparison of Decision Tree Methods in Classification of Researcher’s Cognitive Styles in Academic Environment
    Authors: ZN Balagatabi, R Ibrahim, HN Balagatabi
    Year: 2015
    Cited by: 24

Amir Reza Rahimi | Computer | Best Researcher Award

Published on by NESIN Awards

Dr. Amir Reza Rahimi | Computer | Best Researcher Award

PHD at University of Valencia, Spain

Dr. Amir Reza Rahimi is a Ph.D. candidate at the University of Valencia, specializing in language, literature, culture, and their applications. With extensive experience teaching English at universities, high schools, and language institutes in Iran, he is actively involved in research projects like FORTHEM and SOCIEMOVE, focusing on fostering socioemotional skills through virtual exchange. Dr. Rahimi has conducted workshops for language teachers on integrating technology into English teaching and has published extensively in prestigious journals such as Computer-Assisted Language Learning and Computers in Human Behavior Reports. His research has been presented at international conferences, and he is recognized for introducing innovative educational methodologies, earning the Best Research Award in Innovation in Data Analysis. His expertise spans psycholinguistics, CALL, MOOCs, virtual exchange, and teacher education. With a passion for advancing language learning, Dr. Rahimi continues to make significant contributions to the intersection of technology and education.

Professional Profile 

Education

Dr. Amir Reza Rahimi has an extensive academic background, beginning with a Bachelor’s degree in English Language Teaching from the University of Mohaghegh Ardabili in Iran, completed between 2014 and 2017. He then pursued a Master’s degree in English Language Teaching at Shahid Rajaee Teacher Training University in Tehran, Iran, where he conducted research on the impact of massive open online courses (MOOCs) on Iranian EFL learners’ self-regulation and motivation. Dr. Rahimi is currently a Ph.D. candidate at the University of Valencia, Spain, where he is studying language, literature, culture, and their applications. His doctoral research is focused on exploring innovative methods in language learning, particularly through virtual exchange and computer-assisted language learning (CALL). Throughout his educational journey, Dr. Rahimi has continuously demonstrated a commitment to advancing the field of language education through research, publications, and participation in international academic projects.

Professional Experience

Dr. Amir Reza Rahimi has a rich and diverse professional experience in the field of language education. He has taught English at various institutions, including universities, high schools, and language institutes in Iran, where he developed expertise in teaching English as a foreign language (EFL). His teaching career spans over several years, during which he contributed to curriculum development and language instruction. Dr. Rahimi is currently involved in the FORTHEM Research Project and the SOCIEMOVE project, where he serves as a mentor researcher and focuses on developing socioemotional skills through virtual exchange. Additionally, he has conducted workshops for language teachers, helping them incorporate technology into their teaching practices. His research, which bridges the gap between language learning and technology, has led to numerous publications in high-impact journals. Dr. Rahimi’s professional experience reflects his dedication to enhancing language education through innovative methodologies and research-driven approaches.

Research Interest

Dr. Amir Reza Rahimi’s research interests primarily focus on the intersection of language education, technology, and learner motivation. His work explores various aspects of computer-assisted language learning (CALL), particularly how digital tools and virtual exchanges can enhance language learning experiences. Dr. Rahimi is deeply interested in the role of massive open online courses (MOOCs) and the development of self-regulation and motivation in online language learners. He also delves into psycholinguistics, exploring how emotional and psychological factors influence language acquisition. His research further investigates the impact of socioemotional skills on language learners, especially through virtual exchange programs like SOCIEMOVE. Additionally, he examines theory development in education, with a particular emphasis on innovative research designs, such as bisymmetric approaches. Dr. Rahimi’s work aims to bridge the gap between technology and language teaching, contributing to the advancement of both educational theory and practice in the digital age.

Award and Honor

Dr. Amir Reza Rahimi has received several prestigious awards and honors for his outstanding contributions to language education and research. Notably, he won the Best Research Award in Innovation in Data Analysis from ScienceFather for introducing a new research design to the field of education, specifically a bisymmetric research design. This recognition highlights his innovative approach to research methodology, particularly in the context of computer-assisted language learning (CALL). Dr. Rahimi’s research has also earned him multiple publications in top-tier journals such as Computer-Assisted Language Learning, Computers in Human Behavior Reports, and Education and Information Technologies, where his work on language learning, virtual exchange, and online motivation has gained significant academic attention. His accomplishments have been further acknowledged through his active participation in international conferences, including the TESOL International Convention and the World CALL Conference. Dr. Rahimi’s honors reflect his commitment to advancing language education through technology and innovation.

Conclusion

Amir Reza Rahimi is a highly accomplished researcher whose contributions to CALL, psycholinguistics, and educational technology make him a strong contender for the Best Researcher Award. His innovative approaches, impactful publications, and leadership in international projects are commendable. To further solidify his candidacy, increased interdisciplinary collaboration, a focus on societal impact, and broader dissemination of his work are recommended. Overall, his profile aligns well with the criteria for excellence in research, making him a suitable nominee for this award.

Publications Top Noted

  • The role of university teachers’ 21st-century digital competence in their attitudes toward ICT integration in higher education: Extending the theory of planned behavior
    Authors: AR Rahimi, D Tafazoli
    Year: 2022
    Citation: The JALT CALL Journal, 18(2), 1832-4215
  • Unifying EFL learners’ online self‑regulation and online motivational self‑system in MOOCs: A structural equation modeling approach
    Authors: AR Rahimi, Z Cheraghi
    Year: 2022
    Citation: Journal of Computers in Education, 9(4)
  • EFL learners’ attitudes toward the usability of LMOOCs: A qualitative content analysis
    Authors: AR Rahimi, D Tafazoli
    Year: 2022
    Citation: The Qualitative Report, 27(1), 158-173
  • The role of EFL learners’ L2 self-identities, and authenticity gap on their intention to continue LMOOCs: Insights from an exploratory partial least approach
    Author: AR Rahimi
    Year: 2023
    Citation: Computer Assisted Language Learning, 1-32
  • Online motivational self-system in MOOC: A qualitative study
    Author: AR Rahimi
    Year: 2021
    Citation: From emotion to knowledge: emerging ecosystems in language learning, 79-86
  • Beyond digital competence and language teaching skills: The bi-level factors associated with EFL teachers’ 21st-century digital competence to cultivate 21st-century digital skills
    Author: AR Rahimi
    Year: 2024
    Citation: Education and Information Technologies, 29(8), 9061-9089
  • A bi-phenomenon analysis to escalate higher educators’ competence in developing university students’ information literacy (HECDUSIL): The role of language lecturers’ conceptual …
    Author: AR Rahimi
    Year: 2024
    Citation: Education and Information Technologies, 29(6), 7195-7222
  • The role of twenty-first century digital competence in shaping pre-service teacher language teachers’ twenty-first century digital skills: the Partial Least Square Modeling …
    Authors: AR Rahimi, Z Mosalli
    Year: 2024
    Citation: Journal of Computers in Education
  • A tri-phenomenon perspective to mitigate MOOCs’ high dropout rates: the role of technical, pedagogical, and contextual factors on language learners’ L2 motivational selves, and …
    Author: AR Rahimi
    Year: 2024
    Citation: Smart Learning Environments, 11(1), 11
  • Determinants of Online Platform Diffusion during COVID-19: Insights from EFL Teachers’ Perspectives
    Authors: AR Rahimi, S Atefi Boroujeni
    Year: 2022
    Citation: Journal of Foreign Language Teaching and Translation Studies, 7(4), 111-136
  • The role of ChatGPT readiness in shaping language teachers’ language teaching innovation and meeting accountability: A bisymmetric approach
    Authors: AR Rahimi, A Sevilla-Pavón
    Year: 2024
    Citation: Computers and Education: Artificial Intelligence, 7, 100258
  • Exploring the direct and indirect effects of EFL learners’ online motivational self-system on their online language learning acceptance: the new roles of current L2 self and …
    Authors: AR Rahimi, Z Mosalli
    Year: 2024
    Citation: Asian-Pacific Journal of Second and Foreign Language Education, 9(1), 49

Mohammad Ali Balafar | Computer Science | Best Researcher Award

Published on by NESIN Awards

Prof. Dr. Mohammad Ali Balafar | Computer Science | Best Researcher Award

Prof at University of Tabriz, Iran

Prof. Dr. Mohammad Ali Balafar is a distinguished researcher in Artificial Intelligence and Multimedia Systems. With an h-index of 24 (Google Scholar) and inclusion in Stanford’s top 2% most-cited authors, his work is widely recognized for its impact. He leads the Intelligent Information Technology and Multimedia Research Laboratory at Tabriz University, focusing on deep learning, image processing, machine learning, and graph neural networks. His research projects address real-world problems, including image encryption, stock price prediction, and medical diagnosis through brain image segmentation. Dr. Balafar has authored numerous high-impact publications in reputable journals like IEEE Transactions and Chaos, Solitons & Fractals. Fluent in four languages, he fosters collaboration across diverse academic and cultural landscapes. His work blends innovation with application, making him a pioneer in intelligent systems. A strong advocate of interdisciplinary research, Dr. Balafar’s contributions exemplify excellence in both theoretical advancements and practical implementations.

Professional Profile

Education

Prof. Dr. Mohammad Ali Balafar has a strong academic foundation, specializing in Artificial Intelligence and Multimedia Systems. He earned his Bachelor’s degree in Computer Engineering, laying the groundwork for his expertise in computational systems and programming. Pursuing advanced studies, he obtained a Master’s degree in Software Engineering, where he focused on algorithm development and software methodologies. Dr. Balafar then completed his Ph.D. in Computer Engineering, concentrating on cutting-edge technologies such as image processing, data mining, and deep learning. Throughout his educational journey, he honed his skills in machine learning, graph neural networks, and intelligent information systems, which later became central to his research. His academic excellence was complemented by multilingual proficiency (Azerbaijani, English, Farsi, and Turkish), facilitating collaboration in diverse research environments. These educational milestones have equipped Dr. Balafar with the theoretical knowledge and technical expertise essential for pioneering innovations in artificial intelligence and intelligent multimedia technologies.

Professional  Experience

Prof. Dr. Mohammad Ali Balafar is a seasoned academic and researcher with extensive experience in Artificial Intelligence and Multimedia Systems. Currently, he serves as a faculty member in the Department of Electrical and Computer Engineering at Tabriz University. He is the founder and head of the Intelligent Information Technology and Multimedia Research Laboratory, established in 1391 (2012), where he leads innovative projects in areas such as image processing, machine vision, and robotics. Dr. Balafar has been instrumental in advancing intelligent multimedia systems through diverse research initiatives, including expert recommendation systems, stock price prediction, and medical imaging for diagnosing diseases like MS. He has authored numerous high-impact publications and collaborated with leading scholars, contributing to advancements in fields such as deep learning and data mining. With fluency in multiple languages and a global academic network, his professional career reflects a blend of academic rigor, research innovation, and leadership in cutting-edge technology development.

Research Interests

Prof. Dr. Mohammad Ali Balafar’s research interests are deeply rooted in the fields of Artificial Intelligence, Machine Learning, and Multimedia Systems, with a focus on addressing complex computational challenges. His expertise spans a wide range of cutting-edge topics, including Deep Learning, Image Processing, Computer Vision, and Graph Neural Networks. He is particularly interested in developing intelligent systems that can process and analyze visual data, such as creating efficient algorithms for image encryption, clustering, and anomaly detection. Dr. Balafar’s work also delves into Data Mining, where he applies advanced techniques to uncover patterns and insights in domains such as medical diagnostics, stock price prediction, and emergency service optimization. His contributions aim to bridge the gap between theory and application, advancing technologies that enhance real-world decision-making. This interdisciplinary approach not only pushes the boundaries of innovation but also showcases his dedication to solving impactful societal and scientific problems.

Awards and Honors

Prof. Dr. Mohammad Ali Balafar is a highly acclaimed researcher whose contributions have been recognized through various awards and honors. Notably, he has been included in Stanford University’s list of the top 2% most-cited scientists worldwide, based on a one-year performance metric—a testament to his impactful research and global influence in Artificial Intelligence and Multimedia Systems. Dr. Balafar’s scholarly achievements, reflected in his impressive h-index of 24 (Google Scholar) and over 2,380 citations, underscore his standing as a leading researcher in fields like Deep Learning, Image Processing, and Graph Neural Networks. His role as the head of the Intelligent Information Technology and Multimedia Research Laboratory further highlights his leadership in advancing innovative solutions for complex technological challenges. These accolades, combined with his extensive publication record in top-tier journals, position Dr. Balafar as a pioneer in his domain, earning him well-deserved recognition in the academic and research communities.

Conclusion

Dr. Mohammad Ali Balafar is a highly accomplished researcher with a solid track record of impactful publications, innovative research, and academic leadership. His diverse skill set, coupled with his contributions to AI and multimedia systems, makes him a strong candidate for the Best Researcher Award. Enhancing his global collaborations and industry engagement could further solidify his standing as a leading figure in his field.

Publications Top Noted

  • Review of brain MRI image segmentation methods
    • Authors: MA Balafar, AR Ramli, MI Saripan, S Mashohor
    • Year: 2010
    • Citations: 643
  • Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts
    • Authors: M Dashtban, M Balafar
    • Year: 2017
    • Citations: 167
  • A hybrid algorithm using a genetic algorithm and multiagent reinforcement learning heuristic to solve the traveling salesman problem
    • Authors: MM Alipour, SN Razavi, MR Feizi Derakhshi, MA Balafar
    • Year: 2018
    • Citations: 134
  • A novel image encryption algorithm based on polynomial combination of chaotic maps and dynamic function generation
    • Authors: M Asgari-Chenaghlu, MA Balafar, MR Feizi-Derakhshi
    • Year: 2019
    • Citations: 131
  • Gene selection for tumor classification using a novel bio-inspired multi-objective approach
    • Authors: M Dashtban, M Balafar, P Suravajhala
    • Year: 2018
    • Citations: 104
  • Gaussian mixture model based segmentation methods for brain MRI images
    • Authors: MA Balafar
    • Year: 2014
    • Citations: 95
  • The state-of-the-art in expert recommendation systems
    • Authors: N Nikzad–Khasmakhi, MA Balafar, MR Feizi–Derakhshi
    • Year: 2019
    • Citations: 89
  • Fuzzy C-mean based brain MRI segmentation algorithms
    • Authors: MA Balafar
    • Year: 2014
    • Citations: 85
  • CGFFCM: Cluster-weight and Group-local Feature-weight learning in Fuzzy C-Means clustering algorithm for color image segmentation
    • Authors: AG Oskouei, M Hashemzadeh, B Asheghi, MA Balafar
    • Year: 2021
    • Citations: 70
  • CWI: A multimodal deep learning approach for named entity recognition from social media using character, word and image features
    • Authors: M Asgari-Chenaghlu, MR Feizi-Derakhshi, L Farzinvash, MA Balafar
    • Year: 2022
    • Citations: 48
  • Cy: Chaotic yolo for user intended image encryption and sharing in social media
    • Authors: M Asgari-Chenaghlu, MR Feizi-Derakhshi, N Nikzad-Khasmakhi
    • Year: 2021
    • Citations: 36
  • A new method for MR grayscale inhomogeneity correction
    • Authors: MA Balafar, AR Ramli, S Mashohor
    • Year: 2010
    • Citations: 36

Humam Kourani | Computer Science | Best Researcher Award

Published on by NESIN Awards

Mr. Humam Kourani | Computer Science | Best Researcher Award

Research Associate at Fraunhofer FIT, Germany

Mr. Humam Kourani is a dedicated and highly skilled researcher with a strong background in Data Science and Computer Science. He holds both a Master’s and Bachelor’s degree from RWTH Aachen University, specializing in process mining, artificial intelligence, and data-driven decision-making. He has gained valuable experience working in research institutions and industry settings, most notably at the Fraunhofer Institute for Applied Information Technology and Fondazione Bruno Kessler in Italy. His research focuses on improving data science methodologies, particularly in process mining and workflow language models. With a solid academic foundation, practical experience, and significant contributions to his field, Humam has proven himself to be a promising and impactful researcher.

Professional Profile

Education

Humam Kourani completed his Master of Science in Data Science from RWTH Aachen University in 2022, with a focus on Computer Science. His master’s thesis explored the improvement of the Hybrid Miner by utilizing causal graph metrics, an area critical for process mining. Prior to that, he earned his Bachelor of Science degree in Computer Science from the same institution in 2019. His Bachelor’s thesis involved the development of a scalable interactive event data visualization tool in Python, further showcasing his technical skills. Humam’s academic journey reflects his dedication to mastering complex data science concepts and his drive to contribute to the field’s advancement through academic research and innovation.

Professional  Experience

Mr. Kourani’s professional experience spans key positions in research and data science. Since May 2022, he has been working as a Research Associate at the Fraunhofer Institute for Applied Information Technology, specializing in Data Science and Artificial Intelligence. In this role, he contributes to research on process mining, artificial intelligence, and data-driven decision-making. Earlier, he held student assistant roles at RWTH Aachen University, including positions at the Chair of Process and Data Science and the Chair of Process and Data Science in 2021. Humam also completed an Erasmus+ internship at Fondazione Bruno Kessler in Italy, where he gained hands-on experience in process and data intelligence. His professional experience reflects a consistent focus on leveraging data science and AI for practical problem-solving and research innovation.

Research Interests

Humam Kourani’s research interests lie primarily in data science, artificial intelligence, and process mining. He is particularly focused on enhancing data-driven methods for analyzing and improving business processes, with an emphasis on process modeling and workflow languages. His recent work has explored innovative approaches, such as large language models for process modeling, and improving existing hybrid mining techniques using causal graph metrics. Through his work, Humam aims to bridge the gap between advanced computational techniques and practical business process applications, enabling more efficient decision-making. His research also delves into the intersection of data science and AI, with a strong interest in developing scalable models that address real-world challenges across various industries.

Awards and Honors

Humam Kourani has received several prestigious awards in recognition of his outstanding research contributions. He won the Best Paper Award at the EMMSAD 2024 conference for his paper on “Process Modeling with Large Language Models”. Additionally, he received the Best Paper Award at the BPM 2023 conference for his work on the “POWL: Partially Ordered Workflow Language”. These awards highlight the significance of his research in the fields of process mining and business process management. Humam was also honored with membership in the PADS Excellence Honors Class at RWTH Aachen University in 2022, further underscoring his academic excellence. These honors attest to his innovative contributions to the research community and his growing influence in the fields of data science and AI.

Conclusion

Humam Kourani is undoubtedly a highly talented researcher with a solid foundation in data science and process mining. His research achievements, international experience, and awards demonstrate that he is already making significant contributions to his field. His multidisciplinary skills, coupled with his passion for continuous learning, make him a standout candidate for the Best Researcher Award. While there are opportunities for growth in areas like expanding his publication base and increasing leadership roles in research initiatives, his strengths far outweigh these minor areas of improvement. Humam Kourani is a promising researcher with the potential for continued excellence and impact in the field of data science and artificial intelligence.

Publications Top Noted

  • Title: Process Modeling With Large Language Models
    Authors: H. Kourani, A. Berti, D. Schuster, W.M.P. van der Aalst
    Year: 2024
    Citations: 21
  • Title: Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, Evaluation Strategies, and Future Challenges
    Authors: A. Berti, H. Kourani, H. Hafke, C.Y. Li, D. Schuster
    Year: 2024
    Citations: 8
  • Title: POWL: Partially Ordered Workflow Language
    Authors: H. Kourani, S.J. van Zelst
    Year: 2023
    Citations: 7
  • Title: ProMoAI: Process Modeling with Generative AI
    Authors: H. Kourani, A. Berti, D. Schuster, W.M.P. van der Aalst
    Year: 2024
    Citations: 5
  • Title: PM4KNIME: Process Mining Meets the KNIME Analytics Platform
    Authors: H. Kourani, S.J. van Zelst, B.D. Lehmann, G. Einsdorf, S. Helfrich, F. Liße
    Year: 2022
    Citations: 5
  • Title: Scalable Discovery of Partially Ordered Workflow Models with Formal Guarantees
    Authors: H. Kourani, D. Schuster, W. Van Der Aalst
    Year: 2023
    Citations: 4
  • Title: PM-LLM-Benchmark: Evaluating Large Language Models on Process Mining Tasks
    Authors: A. Berti, H. Kourani, W.M.P. van der Aalst
    Year: 2024
    Citations: 3
  • Title: Discovering Hybrid Process Models with Bounds on Time and Complexity: When to be Formal and When Not?
    Authors: W.M.P. van der Aalst, R. De Masellis, C. Di Francescomarino, C. Ghidini, H. Kourani
    Year: 2023
    Citations: 3
  • Title: Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies
    Authors: A. Berti, H. Kourani, H. Häfke, C.Y. Li, D. Schuster
    Year: 2024
    Citations: 2
  • Title: Mining for Long-Term Dependencies in Causal Graphs
    Authors: H. Kourani, C. Di Francescomarino, C. Ghidini, W. van der Aalst, S. van Zelst
    Year: 2022
    Citations: 2
  • Title: Bridging Domain Knowledge and Process Discovery Using Large Language Models
    Authors: A. Norouzifar, H. Kourani, M. Dees, W. van der Aalst
    Year: 2024
    Citations: 0 (preprint)
  • Title: Leveraging Large Language Models for Enhanced Process Model Comprehension
    Authors: H. Kourani, A. Berti, J. Hennrich, W. Kratsch, R. Weidlich, C.Y. Li, A. Arslan, et al.
    Year: 2024
    Citations: 0 (preprint)
  • Title: Discovering Hybrid Process Models with Bounds on Time and Complexity: When to be Formal and When Not?
    Authors: W. van der Aalst, R. De Masellis, C. Di Francescomarino, C. Ghidini, H. Kourani
    Year: 2023
    Citations: 0

Shahbaz Gul Hassan | Computer Science | Best Researcher Award

Published on by NESIN Awards

Assoc. Prof. Dr.Shahbaz Gul Hassan | Computer Science | Best Researcher Award

Associat professor at Zhongkai University of Agriculture and Engineering, China

Dr. Shahbaz Gul Hassan is an accomplished Associate Professor at Zhongkai University of Agriculture and Engineering, specializing in agricultural information technology and computer science. With a strong academic background, including a Ph.D. from China Agricultural University, he focuses on machine learning, image processing, and predictive modeling in the context of agricultural and environmental systems. His work has earned significant recognition, including awards for research and innovation in agricultural technology. Dr. Hassan’s numerous high-impact publications in top-tier journals demonstrate his ability to integrate advanced computational techniques into real-world applications in agriculture.

Professional Profile

Education

Dr. Shahbaz Gul Hassan completed his Ph.D. in Agricultural Information Technology at China Agricultural University, Beijing, in 2017. His research during his Ph.D. focused on the integration of information technology with agriculture, particularly in areas such as machine learning and predictive modeling. Prior to his Ph.D., he earned a Master’s in Computer Science from PMAS Arid Agriculture University, Rawalpindi, in 2011, where he developed a deep understanding of computer science applications in agriculture. He completed his Bachelor’s degree in Science from the University of Punjab, Lahore, in 2007. These educational milestones have equipped Dr. Hassan with a solid foundation in both computer science and agricultural technology, enabling him to innovate at the intersection of these two fields. His academic journey reflects a consistent focus on enhancing agricultural practices through advanced technologies, positioning him as a leading figure in agricultural information systems and technology research.

Experience

Dr. Shahbaz Gul Hassan has extensive experience in both academia and industry. He is currently an Associate Professor at Zhongkai University of Agriculture and Engineering, Guangzhou, China, where he has been teaching since 2019. Prior to this, he served as a Postdoctoral Researcher in Agricultural Engineering at South China Agricultural University, Guangzhou, from 2017 to 2019. In this role, he applied his expertise in machine learning and image processing to agricultural engineering projects. Dr. Hassan also worked as a Ph.D. Research Scholar at China Agricultural University, Beijing, from 2013 to 2017, where he focused on applying technology to solve critical problems in agriculture. Earlier, he worked as a Software Engineer at MTBC in Rawalpindi from 2011 to 2012. His diverse professional experience blends research, teaching, and practical applications of technology in agriculture, with a focus on using advanced computing to optimize agricultural processes.

Research Interests

Dr. Shahbaz Gul Hassan’s research focuses on the application of machine learning, image processing, and predictive modeling to solve agricultural challenges. He is particularly interested in developing smart technologies for precision farming and environmental monitoring. One of his key areas of research involves computer vision and machine learning techniques for detecting and predicting behaviors and conditions in agricultural environments, such as water quality and animal health. His work aims to enhance automation in agriculture and improve sustainability by leveraging data-driven technologies. Dr. Hassan also focuses on predictive modeling for environmental variables such as humidity, temperature, and dissolved oxygen levels in aquaculture. These models help optimize farming processes and ensure better resource management. His research not only pushes the boundaries of agricultural technology but also contributes to the development of sustainable practices in farming and aquaculture. Dr. Hassan’s interdisciplinary approach integrates computer science and engineering with practical agricultural needs to drive innovation.

Awards and Honors

Dr. Shahbaz Gul Hassan has received numerous prestigious awards for his outstanding contributions to agricultural research. In December 2023, he was honored with the First Prize in the Guangdong Province Agricultural Technology Promotion Award. He also received the Third Prize from the Guangdong Provincial Science and Technology Department in January 2024. Dr. Hassan’s work on a microservice-based agricultural app earned him the Second Prize in the 16th China University Computer Design Competition in the Guangdong-Hong Kong-Macao Greater Bay Area. Additionally, he was awarded the Excellent Instructor Award in the 13th Blue Bridge Cup Provincial Competition. His work has been recognized by the Guangdong Computer Society, where he received the Second Prize for Outstanding Paper. These awards reflect Dr. Hassan’s innovative approach to integrating advanced technologies in agriculture, as well as his ability to drive real-world impact with his research. His accolades highlight his leadership and dedication to improving agricultural technologies globally.

Conclusion

Dr. Shahbaz Gul Hassan is an outstanding candidate for the Best Researcher Award. His innovative approach to integrating machine learning with agricultural processes, alongside his strong academic qualifications and prolific output, make him a leading figure in his field. His numerous prestigious awards and contributions to practical agricultural technologies demonstrate the significant real-world impact of his work. Dr. Hassan is a researcher who continues to push the boundaries of knowledge and practical application in agricultural engineering and information technology, making him a valuable contender for the award.

Publications Top Noted

Title: Green synthesis of iron oxide nanorods using Withania coagulans extract improved photocatalytic degradation and antimicrobial activity
Authors: S Qasim, A Zafar, MS Saif, Z Ali, M Nazar, M Waqas, AU Haq, T Tariq, …
Citations: 175
Year: 2020

Title: Prediction of the temperature in a Chinese solar greenhouse based on LSSVM optimized by improved PSO
Authors: H Yu, Y Chen, SG Hassan, D Li
Citations: 158
Year: 2016

Title: Bioinspired synthesis of zinc oxide nano-flowers: A surface enhanced antibacterial and harvesting efficiency
Authors: M Hasan, M Altaf, A Zafar, SG Hassan, Z Ali, G Mustafa, T Munawar, …
Citations: 114
Year: 2021

Title: Models for estimating feed intake in aquaculture: A review
Authors: M Sun, SG Hassan, D Li
Citations: 108
Year: 2016

Title: Phyto-reflexive zinc oxide nano-flowers synthesis: an advanced photocatalytic degradation and infectious therapy
Authors: MS Saif, A Zafar, M Waqas, SG Hassan, A ul Haq, T Tariq, S Batool, …
Citations: 75
Year: 2021

Title: Fractionation of Biomolecules in Withania coagulans Extract for Bioreductive Nanoparticle Synthesis, Antifungal and Biofilm Activity
Authors: M Hasan, A Zafar, I Shahzadi, F Luo, SG Hassan, T Tariq, S Zehra, …
Citations: 66
Year: 2020

Title: Phytotoxic evaluation of phytosynthesized silver nanoparticles on lettuce
Authors: M Hasan, K Mehmood, G Mustafa, A Zafar, T Tariq, SG Hassan, …
Citations: 53
Year: 2021

Title: Green synthesis of Cordia myxa incubated ZnO, Fe2O3, and Co3O4 nanoparticle: Characterization, and their response as biological and photocatalytic agent
Authors: S Batool, M Hasan, M Dilshad, A Zafar, T Tariq, Z Wu, R Chen, …
Citations: 49
Year: 2022

Title: Physiological and anti-oxidative response of biologically and chemically synthesized iron oxide: Zea mays a case study
Authors: M Hasan, S Rafique, A Zafar, S Loomba, R Khan, SG Hassan, MW Khan, …
Citations: 47
Year: 2020

Title: Dissolved oxygen content prediction in crab culture using a hybrid intelligent method
Authors: H Yu, Y Chen, SG Hassan, D Li
Citations: 43
Year: 2016

Title: Cursive handwritten text recognition using bi-directional LSTMs: a case study on Urdu handwriting
Authors: S Hassan, A Irfan, A Mirza, I Siddiqi
Citations: 42
Year: 2019

Title: Green synthesized ZnO-Fe2O3-Co3O4 nanocomposite for antioxidant, microbial disinfection and degradation of pollutants from wastewater
Authors: S Batool, M Hasan, M Dilshad, A Zafar, T Tariq, A Shaheen, R Iqbal, Z Ali, …
Citations: 41
Year: 2022

Title: A hybrid model for short-term dissolved oxygen content prediction
Authors: J Huang, S Liu, SG Hassan, L Xu, C Huang
Citations: 39
Year: 2021

Title: Biological synthesis of bimetallic hybrid nanocomposite: a remarkable photocatalyst, adsorption/desorption and antimicrobial agent
Authors: X Huang, A Zafar, K Ahmad, M Hasan, T Tariq, S Gong, SG Hassan, …
Citations: 36
Year: 2023

Title: Nano-managing silver and zinc as bio-conservational approach against pathogens of the honey bee
Authors: R Hussain, M Hasan, KJ Iqbal, A Zafar, T Tariq, MS Saif, SG Hassan, …
Citations: 33
Year: 2023

 

 

Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

Published on by NESIN Awards

Mrs. Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

Assistant Professor at Dr Subhash University, India

Khyati Bhupta is a highly motivated and accomplished professor specializing in the field of pharmacy. She is dedicated to both teaching and research, with a passion for fostering student development using modern teaching methods and advanced pedagogy. Her work is defined by her dedication to innovation and academic excellence. Her experience and skills, particularly in the pharmaceutical sector, make her a valuable contributor to both academia and the industry.

Professional profile

Education 📚

Khyati holds a PhD in Pharmacy, which she earned in May 2013 from Dr. Subhash University, Gujarat. Prior to her PhD, she completed her Master’s in Pharmacy with a specialization in Quality Assurance from Gujarat Technological University in 2009, and her Bachelor’s in Pharmacy from Sardar Patel University in 2007. Her academic journey reflects a consistent focus on pharmaceutical sciences, with an emphasis on quality and research.

Professional Experience🎓

Over the years, Khyati has built extensive experience as a professor in pharmacy, contributing significantly to both teaching and research. She is skilled in handling pharmaceutical instruments and software, which has been vital in her research and practical work. Her expertise in communication and documentation further enhances her teaching capabilities, making her an effective educator who fosters learning through modern approaches and methodologies.

Research Interest🎓

Khyati’s research primarily focuses on pharmaceutical sciences, with significant work on benzothiazole derivatives, exploring their potential as antidiabetic and antiviral agents. She has published multiple papers on these topics in renowned journals such as MDPI and the Annals of the Romanian Society for Cell Biology. Her work also involves method development for pharmaceutical analysis, including titrimetric methods and RP-HPLC method development for drug estimation, reflecting her deep engagement in pharmaceutical research and innovation.

Awards and Honors 🏆

Khyati has received several recognitions for her contributions to research. In August 2022, she was granted a patent from the Government of India, demonstrating her innovative contributions to pharmaceutical science. Additionally, she received a grant from the SSIP (Student Startup and Innovation Policy) under the Gujarat Government in October 2023 for her work on a startup project, highlighting her potential in translating research into practical applications.

Publications top noted📜

  • BENZOTHIAZOLE: AS AN ANTIDIABETIC AGENT
    • Authors: Khyati Bhupta
    • Journal: Annals of the Romanian Society for Cell Biology
    • Year: 2021
    • Citations: N/A 📊💊
  • BENZOTHIAZOLE MOIETY AND ITS DERIVATIVES AS ANTIVIRAL AGENTS
    • Authors: Khyati Bhupta
    • Journal: MDPI
    • Year: 2021
    • Citations: N/A 🦠🔬
  • Biological Screening and Structure Activity Relationship of Benzothiazole
    • Authors: Khyati Bhupta
    • Journal: Research Journal of Pharmacy and Technology
    • Year: 2022
    • Citations: N/A 🧪📈
  • Development of Titrimetric Method for Estimation of Furosemide Tablets by Using Mixed Co-Solvency Process
    • Authors: Khyati Bhupta
    • Journal: International Journal of Biology, Pharmacy and Allied Sciences
    • Year: 2022
    • Citations: N/A ⚖️💊
  • RP-HPLC Method Development and Validation for Simultaneous Estimation of Ranitidine Hydrochloride and Domperidone in Combination
    • Authors: Khyati Bhupta
    • Journal: International Journal of Pharmacy, Biology and Allied Science
    • Year: 2023
    • Citations: N/A 📊🔬

Prof Dr. Mehlika Dilek Altıntop | Medicinal Chemistry | Women Researcher Award

Published on by NESIN Awards

Prof Dr. Mehlika Dilek Altıntop | Medicinal Chemistry | Women Researcher Award

Prof Dr. Anadolu University, Turkey

Dr. Mehlika Dilek Altıntop is a prominent Professor in Pharmaceutical Chemistry at Anadolu University. Her academic journey includes a Bachelor’s from Anadolu University, followed by a Master’s and Ph.D. in Pharmaceutical Chemistry from the same institution. She has served in various academic roles, including Research Assistant, Assistant Professor, and currently as a Professor. Her administrative roles include serving as Associate Director and Quality Coordinator at Anadolu University. Dr. Altıntop has received numerous awards for her research, including the Outstanding Woman Researcher Award and multiple Article Performance Awards. She is actively involved in editorial and guest editing roles in prestigious scientific journals and has supervised numerous master’s and doctoral dissertations in her field.

Professional profile

Scopus

Education 📚

Primary School: İkieylül Elementary School (1991-1996)Secondary School – High School: Eskişehir Anatolian High School (1996-2003)Undergraduate: Anadolu University, Faculty of Pharmacy (2003-2007)Master’s Degree (with Thesis): Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (2007-2009)Doctoral Degree: Anadolu University, Graduate School of Health Sciences, Department of Pharmaceutical Chemistry (2009-2012)Languages: English (Excellent)

Academic Titles 🎓

Research Assistant: Anadolu University, Faculty of Pharmacy (2010-2012)Research Assistant Doctor: Anadolu University, Faculty of Pharmacy (2012-2014)Assistant Professor Doctor: Anadolu University, Faculty of Pharmacy (2014-2015)Associate Professor Doctor: Anadolu University, Faculty of Pharmacy (2015-2020)Professor Doctor: Anadolu University, Faculty of Pharmacy (2020-Present)Administrative Roles 🏛️Erasmus/Farabi/Mevlana Assistant Coordinator: Anadolu University Faculty of Pharmacy (2013-2014)Associate Director: Anadolu University Graduate School of Health Sciences (2014-2017, 2023)Quality Coordinator: Anadolu University Graduate School of Health Sciences (2022-2023)

Awards and Honors 🏆

Anadolu University Faculty of Pharmacy Championship Award (2007)The Scientific and Technological Research Council of Turkey Graduate Scholarship (2007-2009)Anadolu University Science and Technology Encouragement Award (2014)Anadolu University Gold & Platinum Article Performance Awards (2015)Outstanding Reviewer, European Journal of Medicinal Chemistry (2016)Turkish Pharmacists’ Association Academy of Pharmacy Encouragement Award (2019)ISIF’21 Silver Medal for “Targeted Novel Triazolothiadiazine Derivatives for The Treatment of Lung Cancer” (2021)Award of Outstanding Woman Researcher in Pharmaceutical Chemistry, VIWA 2021

Publication📜

 

Design, Synthesis, and In Vivo Evaluation of a New Series of Indole-Chalcone Hybrids as Analgesic and Anti-Inflammatory Agents
Authors: Baramaki, I., Altıntop, M.D., Arslan, R., Hasan, A., Bektaş Türkmen, N.
Journal: ACS Omega, 2024, 9(10), pp. 12175–12183

Design, Synthesis, and Evaluation of a New Series of 2-Pyrazolines as Potential Antileukemic Agents
Authors: Altıntop, M.D., Cantürk, Z., Özdemir, A.
Journal: ACS Omega, 2023, 8(45), pp. 42867–42877

Design, Synthesis, and Evaluation of a New Series of Hydrazones as Small-Molecule Akt Inhibitors for NSCLC Therapy
Authors: Erdönmez, B., Altıntop, M.D., Akalın Çiftçi, G., Özdemir, A., Ece, A.
Journal: ACS Omega, 2023, 8(22), pp. 20056–20065

A New Series of Hydrazones as Small-Molecule Aldose Reductase Inhibitors
Authors: Altıntop, M.D., Demir, Y., Türkeş, C., Beydemir, Ş., Özdemir, A.
Journal: Archiv der Pharmazie, 2023, 356(4), 2200570

A New Series of Thiazole-Hydrazone Hybrids for Akt-Targeted Therapy of Non-Small Cell Lung Cancer
Authors: Orujova, T., Ece, A., Akalın Çiftçi, G., Özdemir, A., Altıntop, M.D.
Journal: Drug Development Research, 2023, 84(2), pp. 185–199

Synthesis, In Silico and In Vitro Evaluation of New 3,5-Disubstituted-1,2,4-Oxadiazole Derivatives as Carbonic Anhydrase Inhibitors and Cytotoxic Agents
Authors: Kucukoglu, K., Faydali, N., Bul, D., Ozturk, B., Guzel, I.
Journal: Journal of Molecular Structure, 2023, 1276, 134699

Discovery of Small Molecule COX-1 and Akt Inhibitors as Anti-NSCLC Agents Endowed with Anti-Inflammatory Action
Authors: Altıntop, M.D., Akalın Çiftçi, G., Yılmaz Savaş, N., Alataş, Ö., Özdemir, A.
Journal: International Journal of Molecular Sciences, 2023, 24(3), 2648

Microwave-Assisted Synthesis of a Series of 4,5-Dihydro-1H-Pyrazoles Endowed with Selective COX-1 Inhibitory Potency
Authors: Altıntop, M.D., Temel, H.E., Özdemir, A.
Journal: Journal of the Serbian Chemical Society, 2023, 88(4), pp. 355–365

Design, Synthesis, and Biological Evaluation of a New Series of Arylidene Indanones as Small Molecules for Targeted Therapy of Non-Small Cell Lung Carcinoma and Prostate Cancer
Authors: Altıntop, M.D., Özdemir, A., Temel, H.E., Kaplancıklı, Z.A., Akalın Çiftçi, G.
Journal: European Journal of Medicinal Chemistry, 2022, 244, 114851

A New Series of Thiosemicarbazone-Based Anti-Inflammatory Agents Exerting Their Action Through Cyclooxygenase Inhibition
Authors: Altıntop, M.D., Sever, B., Akalın Çiftçi, G., Alataş, Ö., Özdemir, A.
Journal: Archiv der Pharmazie, 2022, 355(9), 2200136