Associate professor, Ph.D. in information technologies at West Ukrainian National University, Ukraine

Khrystyna Lipianina-Honcharenko is a promising candidate for the Young Scientist Award due to her strong academic background and substantial contributions to research in information technology, machine learning, and socio-economic modeling. Holding a PhD in Technical Sciences and serving as an Associate Professor at the West Ukrainian National University, she has extensive experience in both teaching and research. Khrystyna is involved in high-impact international projects, such as TruScanAI and Erasmus+ initiatives, demonstrating her leadership and collaboration in cutting-edge technological advancements. Her research on data analysis, simulation, and machine learning positions her at the forefront of modern scientific inquiry. While her proficiency in English and publication presence are notable, further enhancement of her language skills and expanding her network in global research circles could increase her influence. Overall, Khrystyna’s innovative research and leadership make her a strong contender for the award, with significant potential for future contributions to the scientific community.

Professional Profile

Education🎓

Khrystyna Lipianina-Honcharenko has an extensive educational background, primarily from West Ukrainian National University, where she has completed multiple degrees. She holds a Bachelor’s degree in Economic Cybernetics (2007–2011), followed by a Master’s in Information Technologies in Economics (2011–2012). Khrystyna continued her academic journey as a postgraduate student at the Department of Economic Cybernetics and Informatics, earning a PhD in Technical Sciences in Information Technology (2019). Her academic pursuits are ongoing, as she is currently working towards her Doctor of Technical Sciences degree in the Department of Information Computer Systems and Control at the same university, which she is expected to complete in 2025. Her education reflects a strong foundation in both the technical and economic aspects of information systems, further enhanced by her focus on machine learning and data analysis. This solid academic background has significantly contributed to her research and teaching expertise.

Professional Experience📝

Khrystyna Lipianina-Honcharenko has a rich professional experience in academia, primarily at West Ukrainian National University (WNU). She began her career as a Laboratory Assistant in the Department of Economic Cybernetics and Informatics from 2012 to 2014, where she gained foundational experience in research and teaching. Khrystyna then advanced to the role of Lecturer in the same department from 2013 to 2020, and later became a Senior Lecturer in the Department of Information Computer Systems and Control from 2020 to 2021. Her expertise was further recognized when she was promoted to Associate Professor in 2021, a position she holds currently. Throughout her career, Khrystyna has not only contributed to teaching but has also been actively involved in research, particularly in areas such as machine learning, data analysis, and socio-economic modeling. Her experience spans both academic instruction and hands-on involvement in high-impact international research projects, highlighting her leadership and expertise.

Research Interest🔎

Khrystyna Lipianina-Honcharenko’s research interests lie at the intersection of information technology, machine learning, and socio-economic modeling. She is particularly focused on data analysis, simulation, and the application of artificial intelligence methods in cyber-physical systems. Her work explores the use of machine learning techniques to model and forecast socio-economic processes, aiming to improve decision-making in various fields, including economics and technology. Khrystyna has also contributed to innovative projects like TruScanAI, which uses AI to detect fake information, and Auralisation of Acoustic Heritage Sites, which combines augmented and virtual reality to preserve cultural heritage. Her research interests extend to structural and statistical identification of hierarchical objects, as well as the development of tools for analyzing complex systems. Through these endeavors, Khrystyna seeks to advance the integration of technology and data-driven methods in solving real-world challenges, particularly in the context of socio-economic systems and information technologies.

Award and Honor🏆

Khrystyna Lipianina-Honcharenko has been recognized for her significant contributions to research and education, particularly in the fields of information technology and machine learning. While specific awards and honors are not detailed in the available information, her involvement in prestigious international projects such as Erasmus+ and her participation in high-impact research initiatives like TruScanAI and Auralisation of Acoustic Heritage Sites underscore her academic and professional recognition. These projects highlight her leadership and innovation, earning her respect within the academic community. Additionally, her active role in the Erasmus+ KA2 Work4CE program demonstrates her commitment to advancing higher education and interdisciplinary collaboration. Khrystyna’s extensive publication record and contributions to scientific advancements further demonstrate her growing influence in her field. As she continues to contribute to international collaborations and projects, it is likely that her efforts will lead to more formal recognitions and awards, further solidifying her place as a leader in her research domain.

Research Skill🔬

Khrystyna Lipianina-Honcharenko possesses a diverse and robust set of research skills, particularly in the areas of data analysis, machine learning, and modeling of socio-economic processes. She is proficient in programming languages such as R and Python, which are essential for data processing, algorithm development, and machine learning applications. Her expertise extends to using various application packages like MS Excel, Mathcad, AnyLogic, and GeoDa, allowing her to model complex systems and analyze large datasets effectively. Khrystyna is well-versed in both qualitative and quantitative research methodologies, including structural and statistical identification of hierarchical objects, a skill she applied in projects related to cyber-physical systems. Her ability to combine technical knowledge with socio-economic modeling enables her to tackle interdisciplinary research challenges. Moreover, her involvement in international projects showcases her capacity for collaborative, cross-cultural research, further enhancing her adaptability and competence in applying advanced research techniques in diverse contexts.

Conclusion💡

Khrystyna Lipianina-Honcharenko is a strong candidate for the Young Scientist Award, thanks to her academic accomplishments, innovative research projects, and leadership in international collaborations. Her dedication to the field of information technology, machine learning, and socio-economic modeling positions her as an emerging scientist with significant potential for future contributions. With continued professional development in areas such as language proficiency and broader networking, Khrystyna could enhance her impact and further distinguish herself in her field.

Publications Top Noted✍️

Title: Decision tree based targeting model of customer interaction with business page
Authors: H Lipyanina, A Sachenko, T Lendyuk, S Nadvynychny, S Grodskyi
Year: 2020
Citations: 37
Title: Economic Crime Detection Using Support Vector Machine Classification
Authors: A Krysovatyy, H Lipyanina-Goncharenko, S Sachenko, O Desyatnyuk
Year: 2021
Citations: 25
Title: Assessing the investment risk of virtual IT company based on machine learning
Authors: H Lipyanina, V Maksymovych, A Sachenko, T Lendyuk, A Fomenko, I Kit
Year: 2020
Citations: 24
Title: Targeting Model of HEI Video Marketing based on Classification Tree
Authors: H Lipyanina, S Sachenko, T Lendyuk, A Sachenko
Year: 2020
Citations: 22
Title: Concept of the intelligent guide with AR support
Authors: K Lipianina-Honcharenko, R Savchyshyn, A Sachenko, A Chaban, I Kit
Year: 2022
Citations: 19
Title: Intelligent Method of a Competitive Product Choosing based on the Emotional Feedbacks Coloring
Authors: R Gramyak, H Lipyanina-Goncharenko, A Sachenko, T Lendyuk
Year: 2021
Citations: 19
Title: Method of detecting a fictitious company on the machine learning base
Authors: H Lipyanina, S Sachenko, T Lendyuk, V Brych, V Yatskiv, O Osolinskiy
Year: 2021
Citations: 17
Title: Multiple regression method for analyzing the tourist demand considering the influence factors
Authors: V Krylov, A Sachenko, P Strubytskyi, D Lendiuk, H Lipyanina
Year: 2019
Citations: 13
Title: Recognizing the Fictitious Business Entity on Logistic Regression Base
Authors: A Krysovatyy, K Lipianina-Honcharenko, S Sachenko, O Desyatnyuk
Year: 2022
Citations: 9
Title: Сучасні інформаційні технології
Authors: ОВ Вовкодав, ХВ Ліп’яніна
Year: 2017
Citations: 9
Title: Classification Method of Fictitious Enterprises Based on Gaussian Naive Bayes
Authors: A Krysovatyy, H Lipyanina-Goncharenko, O Desyatnyuk, S Sachenko
Year: 2021
Citations: 8
Title: Intelligent information system for product promotion in internet market
Authors: K Lipianina-Honcharenko, C Wolff, A Sachenko, O Desyatnyuk
Year: 2023
Citations: 7
Title: An intelligent method for forming the advertising content of higher education institutions based on semantic analysis
Authors: K Lipianina-Honcharenko, T Lendiuk, A Sachenko, O Osolinskyi
Year: 2021
Citations: 7
Title: Intelligent waste-volume management method in the smart city concept
Authors: K Lipianina-Honcharenko, M Komar, O Osolinskyi, V Shymanskyi
Year: 2023
Citations: 6
Title: Intelligent method for classifying the level of anthropogenic disasters
Authors: K Lipianina-Honcharenko, C Wolff, A Sachenko, I Kit, D Zahorodnia
Year: 2023
Citations: 6

Volodymyr Polishchuk | Computer Science | Best Researcher Award

Posted on 01/02/202501/02/2025 by ScienceFather

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

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
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
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
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
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
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
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
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
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
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

Rajeev Ratna Vallabhuni | Computer Science | Young Scientist Award

Posted on 30/01/202530/01/2025 by ScienceFather

Mr. Rajeev Ratna Vallabhuni | Computer Science | Young Scientist Award

Application Developer at Texans IT Services Inc., India

Rajeev Ratna Vallabhuni is an accomplished Application Developer with a rich background in computer science, technology, and engineering. He has contributed significantly to the field through several innovative patents in areas such as blockchain-based cloud applications, machine learning, and IoT security. His work spans various domains including AI/ML, image processing, and network management, with numerous research publications in international journals and conferences. With experience at Bayview Asset Management, LLC, he has a strong track record of applying cutting-edge technologies to real-world applications. His expertise in both academic and professional settings makes him a leading figure in the field of information technology and software development.

Professional Profile

Education

Rajeev Ratna Vallabhuni holds a Master of Science in Information Technology Management from Campbellsville University, Kentucky, and a Master of Science in Computer Science Engineering from Northwestern Polytechnic University, California, USA. He also completed his Bachelor of Technology in Information and Technology at Vignan University, India. His educational foundation has equipped him with a diverse skill set, allowing him to specialize in software development, computer engineering, and cutting-edge technological innovations.

Professional Experience

Rajeev currently works as an Application Developer at Bayview Asset Management, LLC, where he plays a key role in developing and optimizing software applications. His previous professional experience includes working on various projects related to AI/ML, blockchain, and IoT security. He has contributed to numerous patents, book chapters, and international journal publications. Rajeev’s expertise spans both technical development and leadership, and his ability to integrate machine learning and deep learning techniques into practical solutions has made him a valuable asset in the tech industry.

Research Interest

Rajeev Ratna Vallabhuni’s research interests lie at the intersection of artificial intelligence, machine learning, cloud computing, and Internet of Things (IoT) technologies. His work primarily focuses on enhancing the security of IoT networks, leveraging blockchain for decentralized application architectures, and utilizing deep learning models for image and signal processing. Rajeev is also interested in exploring advanced computational methods for improving network management, resource allocation, and real-time data processing in cloud environments. His innovative research aims to develop scalable, efficient, and secure solutions for modern computing challenges, bridging the gap between theoretical algorithms and real-world applications.

Awards and Honors

Rajeev Ratna Vallabhuni has received numerous accolades for his contributions to the fields of software development, machine learning, and IoT security. Notable recognitions include multiple patents for his innovations in blockchain-based applications, AI/ML, and security systems. He has been awarded fellowships and scholarships during his academic career, showcasing his dedication to pushing the boundaries of technology. Additionally, Rajeev’s research has been published in prestigious international journals and recognized at numerous conferences, further cementing his reputation as a leading figure in his field.

Publications Top Noted

Smart cart shopping system with an RFID interface for human assistance
Authors: RR Vallabhuni, S Lakshmanachari, G Avanthi, V Vijay
Year: 2020
Citation: 92
Performance analysis: D-Latch modules designed using 18nm FinFET Technology
Authors: RR Vallabhuni, G Yamini, T Vinitha, SS Reddy
Year: 2020
Citation: 85
Disease prediction based retinal segmentation using bi-directional ConvLSTMU-Net
Authors: BMS Rani, VR Ratna, VP Srinivasan, S Thenmalar, R Kanimozhi
Year: 2021
Citation: 68
ECG performance validation using operational transconductance amplifier with bias current
Authors: V Vijay, CVSK Reddy, CS Pittala, RR Vallabhuni, M Saritha, M Lavanya, …
Year: 2021
Citation: 63
A Review On N-Bit Ripple-Carry Adder, Carry-Select Adder And Carry-Skip Adder
Authors: V Vijay, M Sreevani, EM Rekha, K Moses, CS Pittala, KAS Shaik, …
Year: 2022
Citation: 62
Speech Emotion Recognition System With Librosa
Authors: PA babu, VS Nagaraju, RR Vallabhuni
Year: 2021
Citation: 62
6Transistor SRAM cell designed using 18nm FinFET technology
Authors: RR Vallabhuni, P Shruthi, G Kavya, SS Chandana
Year: 2020
Citation: 60
Universal Shift Register Designed at Low Supply Voltages in 20nm FinFET Using Multiplexer
Authors: RR Vallabhuni, J Sravana, CS Pittala, M Divya, BMS Rani, S Chikkapally, …
Year: 2021
Citation: 58
Numerical analysis of various plasmonic MIM/MDM slot waveguide structures
Authors: CS Pittala, RR Vallabhuni, V Vijay, UR Anam, K Chaitanya
Year: 2022
Citation: 57
Design of Comparator using 18nm FinFET Technology for Analog to Digital Converters
Authors: RR Vallabhuni, DVL Sravya, MS Shalini, GU Maheshwararao
Year: 2020
Citation: 55
High Speed Energy Efficient Multiplier Using 20nm FinFET Technology
Authors: VR Ratna, S M, S N, V V, PC Shaker, D M, S Sadulla
Year: 2021
Citation: 53
Physically unclonable functions using two-level finite state machine
Authors: V Vijay, K Chaitanya, CS Pittala, SS Susmitha, J Tanusha, …
Year: 2022
Citation: 48
Realization and comparative analysis of thermometer code based 4-bit encoder using 18 nm FinFET technology for analog to digital converters
Authors: CS Pittala, V Parameswaran, M Srikanth, V Vijay, V Siva Nagaraju, …
Year: 2021
Citation: 45
Comparative validation of SRAM cells designed using 18nm FinFET for memory storing applications
Authors: RR Vallabhuni, KC Koteswaramma, B Sadgurbabu, A Gowthamireddy
Year: 2020
Citation: 45

Bader Alsharif | Computer Science | Best Innovation Award

Posted on 27/12/202427/12/2024 by ScienceFather

Dr. Bader Alsharif | Computer Science | Best Innovation Award

Florida Atlantic University, United States

Dr. Bader Alsharif is an accomplished PhD candidate in Computer Engineering with a strong background in teaching, technical support, and curriculum development. He has led innovative projects, including the first CISCO simulation lab in Saudi Arabia, and has managed over 300 devices, optimizing performance and security. With a focus on AI, Cybersecurity, and IoT, particularly in healthcare, Dr. Alsharif has published over 7 peer-reviewed papers. He has demonstrated leadership in both academic and technical spheres, guiding over 200 students and advocating for special needs education, ensuring their academic success. His expertise extends to training professionals, having conducted comprehensive courses for Saudi Telecom employees. Dr. Alsharif has shown a profound commitment to advancing technology and fostering inclusivity, particularly through his work with individuals with special needs. His work bridges technological innovation with social impact, positioning him as a forward-thinking leader in computer engineering and healthcare.

Professional Profile

Education

Dr. Bader Alsharif has an extensive academic background, beginning with a Bachelor of Science in Computer Engineering from the College of Technology in Riyadh, Saudi Arabia, where he graduated in 2008. He further advanced his studies with a Master of Science in Computer Engineering from the Florida Institute of Technology, completing his degree in 2017. Currently, Dr. Alsharif is pursuing a Doctor of Computer Engineering at Florida Atlantic University in Boca Raton, USA, with an expected graduation date of 2025. His academic journey has been marked by a strong focus on integrating Artificial Intelligence (AI), Cybersecurity, and Internet of Things (IoT) technologies, particularly in healthcare applications. This multidisciplinary education has provided Dr. Alsharif with the expertise to contribute meaningfully to both research and practical innovations in these fields, bridging the gap between technology and real-world healthcare challenges.

Professional Experience

Dr. Bader Alsharif has a diverse professional background with extensive experience in both academia and technical roles. He currently serves as a Teaching Assistant at Florida Atlantic University, where he guides and evaluates over 30 students on engineering design projects and assists more than 200 students with project development and technical issues. Prior to this, Dr. Alsharif held a prominent role as a Lecturer at the Communications and Information College in Riyadh, Saudi Arabia, where he managed and maintained over 300 devices and led the installation of the first CISCO simulation lab in the country. This project, a significant innovation, involved the deployment of over 30 devices and routers. He also trained 100 employees from Saudi Telecom and designed assessments for instructors working with special needs students. Dr. Alsharif’s professional experience reflects a strong blend of technical expertise, leadership, and a commitment to education and inclusivity.

Research Interest

Dr. Bader Alsharif’s research interests lie at the intersection of Artificial Intelligence (AI), Cybersecurity, and the Internet of Things (IoT), with a particular focus on their applications in healthcare. He is deeply committed to exploring how these advanced technologies can be integrated to enhance patient outcomes and improve healthcare systems. His work aims to leverage AI algorithms to optimize medical data analysis, while also addressing critical security concerns in the rapidly growing field of IoT healthcare devices. Dr. Alsharif’s research also extends to the development of innovative solutions for securing healthcare networks and ensuring the privacy of sensitive patient information. With a strong academic foundation and several peer-reviewed publications, he is dedicated to advancing knowledge in these areas and exploring how cutting-edge technologies can be applied to solve real-world challenges in healthcare. His work demonstrates a commitment to both technological innovation and social impact, especially in the realm of health and well-being.

Award and Honor

Dr. Bader Alsharif has received numerous accolades for his contributions to academia and technology. His achievements include successfully leading the installation of the first CISCO simulation lab in Saudi Arabia, which became a groundbreaking project in the region, significantly enhancing the educational infrastructure for telecommunications. In recognition of his exceptional performance in teaching and technical support, he consistently achieved high job performance ratings, including scores no less than 99/100. Dr. Alsharif has also been honored for his commitment to inclusive education, particularly in advocating for and supporting students with special needs, ensuring their academic excellence. His research in AI, Cybersecurity, and IoT, particularly in the healthcare sector, has earned him recognition as a published researcher with over 7 peer-reviewed papers. Through his work, Dr. Alsharif has received recognition from academic institutions and industry professionals for his innovative contributions, leadership, and commitment to fostering technological advancements with social impact.

Conclusion

Bader Alsharif has demonstrated significant innovation across several key areas of AI, Cybersecurity, and IoT, particularly in healthcare. His leadership in education and advocacy for special needs individuals also reflects a deep commitment to both technological advancement and social impact. His ability to lead high-profile projects and publish extensively in relevant fields positions him as a strong candidate for the Best Innovation Award. However, expanding his research impact and involvement in larger-scale, cross-disciplinary projects could further elevate his candidacy. Overall, he has the potential to be an exceptional award recipient based on his innovative contributions and impact.

Publications Top Noted

Title: Deep learning technology to recognize American Sign Language alphabet
Authors: B Alsharif, AS Altaher, A Altaher, M Ilyas, E Alalwany
Year: 2023
Citations: 14
Title: Internet of things technologies in healthcare for people with hearing impairments
Authors: B Alsharif, M Ilyas
Year: 2022
Citations: 8
Title: Deep Learning Technology to Recognize American Sign Language Alphabet Using Multi-Focus Image Fusion Technique
Authors: B Alsharif, M Alanazi, AS Altaher, A Altaher, M Ilyas
Year: 2023
Citations: 6
Title: Machine Learning Technology to Recognize American Sign Language Alphabet
Authors: B Alsharif, M Alanazi, M Ilyas
Year: 2023
Citations: 4
Title: Enhancing cybersecurity in healthcare: Evaluating ensemble learning models for intrusion detection in the internet of medical things
Authors: T Alsolami, B Alsharif, M Ilyas
Year: 2024
Citations: 3
Title: Multi-Dataset Human Activity Recognition: Leveraging Fusion for Enhanced Performance
Authors: M Alanazi, B Alsharif, AS Altaher, A Altaher, M Ilyas
Year: 2023
Citations: 3
Title: Transfer learning with YOLOV8 for real-time recognition system of American Sign Language Alphabet
Authors: B Alsharif, E Alalwany, M Ilyas
Year: 2024
Citations: 1
Title: Franklin Open
Authors: B Alsharif, E Alalwany, M Ilyas
Year: 2024
Citations: Not available yet

Hossein Nematzadeh | Computer Science | Best Researcher Award

Posted on 24/12/202424/12/2024 by ScienceFather

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

Nunzio Alberto Borghese | Computer Science | Best Researcher Award

Posted on 12/12/202412/12/2024 by ScienceFather

Prof. Nunzio Alberto Borghese | Computer Science | Best Researcher Award

Full professor at Università degli Studi di MIlano, Italy

Professor N. Alberto Borghese is a renowned researcher in computational intelligence and its application to real-world problems. He graduated magna cum laude in Electrical Engineering from Politecnico di Milan and has held significant academic positions, including Full Professor at the University of Milan. His research focuses on innovative methods such as multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with particular emphasis on limited processing time. He has made notable contributions to e-Health and robotics, integrating AI, service robots, virtual communities, and smart objects to improve healthcare and welfare systems. With over 90 journal papers, 140+ conference papers, and 16 international patents, he has a strong academic and industrial impact. He has led several high-profile projects funded by the European Commission and Italian government, including REWIRE, MOVECARE, and AIRCA. His work continues to advance the intersection of AI, robotics, and healthcare, addressing critical societal needs.

Professional Profile

Education

Professor N. Alberto Borghese received his education in Electrical Engineering, graduating magna cum laude in 1986 from Politecnico di Milan, one of Italy’s leading institutions. This strong academic foundation laid the groundwork for his extensive research career. His academic journey furthered through his role as a tenured researcher at the National Research Council (CNR) from 1987 to 2000, where he began developing his expertise in computational intelligence. This led to his appointment as an Associate and later Full Professor at the Department of Computer Science, University of Milan (UNIMI). At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he has mentored students and led cutting-edge research projects. Professor Borghese’s education and professional development have been marked by continuous innovation, research leadership, and a commitment to applying his knowledge to real-world challenges, particularly in e-Health, robotics, and AI.

Professional Experience

Professor N. Alberto Borghese has had a distinguished professional career, beginning as a tenured researcher at the National Research Council (CNR) from 1987 to 2000. During this time, he built a strong foundation in computational intelligence. He then transitioned to the University of Milan (UNIMI), where he became an Associate Professor and later a Full Professor in the Department of Computer Science. At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he leads innovative research projects focused on AI, robotics, and e-Health. Throughout his career, he has contributed to over 90 journal papers, more than 140 conference papers, and holds 16 international patents. Professor Borghese has led several major research projects funded by the European Commission, including REWIRE, MOVECARE, and FITREHAB, and has been involved in multiple Italian government-funded initiatives. His work bridges academia and industry, addressing pressing societal needs in healthcare and welfare through technological advancements.

Research Interest

Professor N. Alberto Borghese’s research interests lie primarily in the field of computational intelligence, focusing on the development and application of advanced algorithms to solve real-world problems. He specializes in multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with an emphasis on optimizing solutions for limited processing time. His work extends to the integration of Artificial Intelligence (AI) and robotics, particularly in the domains of e-Health and e-Welfare. Professor Borghese has pioneered the use of service robots, virtual communities, and smart objects, creating innovative platforms that enhance healthcare and welfare systems. His research also explores the intersection of AI with healthcare technologies such as exer-games, aiming to improve accessibility and promote well-being. Additionally, he has a strong focus on interdisciplinary collaboration, leading several European and Italian research projects that combine AI, robotics, and human-centered design to address societal challenges in health, aging, and rehabilitation.

Award and Honor

Professor N. Alberto Borghese has received numerous awards and honors throughout his distinguished academic and research career. His recognition stems from his innovative contributions to computational intelligence, AI, and robotics, particularly in the fields of e-Health and e-Welfare. With over 90 journal papers and 140+ conference papers, his research has garnered widespread acclaim, reflected in his h-index of 42. He has also been honored for his extensive intellectual property contributions, holding 16 international patents. His leadership in research has been recognized through his involvement in high-profile projects funded by the European Commission and Italian government, such as REWIRE (FP7), MOVECARE (H2020), and AIRCA (2023-2025). These honors not only underline his academic excellence but also highlight his impact on advancing technology in healthcare and welfare systems. His continued success in securing major funding and his role in shaping interdisciplinary research make him a highly respected figure in his field.

Conclusion

Based on his exceptional academic qualifications, pioneering research in computational intelligence and e-Health, leadership in high-profile projects, and impressive publication and patent record, N. Alberto Borghese is a highly suitable candidate for the Best Researcher Award. Addressing minor improvements in public engagement and cross-disciplinary impact could further strengthen his candidacy. Nonetheless, his proven expertise and contributions make him a deserving nominee.

Publications Top Noted

Kinematic determinants of human locomotion
- Authors: N. Alberto Borghese, L. Bianchi, F. Lacquaniti
- Year: 1996
- Citations: 553
Different brain correlates for watching real and virtual hand actions
- Authors: D. Perani, F. Fazio, N. A. Borghese, M. Tettamanti, S. Ferrari, J. Decety, …
- Year: 2001
- Citations: 402
Autocalibration of MEMS accelerometers
- Authors: I. Frosio, F. Pedersini, N. A. Borghese
- Year: 2008
- Citations: 261
Time-varying mechanical behavior of multijointed arm in man
- Authors: F. Lacquaniti, M. Carrozzo, N. A. Borghese
- Year: 1993
- Citations: 202
Internal models of limb geometry in the control of hand compliance
- Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
- Year: 1992
- Citations: 197
Reading the reading brain: a new meta-analysis of functional imaging data on reading
- Authors: I. Cattinelli, N. A. Borghese, M. Gallucci, E. Paulesu
- Year: 2013
- Citations: 188
A functional-anatomical model for lipreading
- Authors: E. Paulesu, D. Perani, V. Blasi, G. Silani, N. A. Borghese, U. De Giovanni, …
- Year: 2003
- Citations: 163
The role of vision in tuning anticipatory motor responses of the limbs
- Authors: F. Lacquaniti
- Year: 1993
- Citations: 151
Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames
- Authors: M. Pirovano, E. Surer, R. Mainetti, P. L. Lanzi, N. A. Borghese
- Year: 2016
- Citations: 148
Self-adaptive games for rehabilitation at home
- Authors: M. Pirovano, R. Mainetti, G. Baud-Bovy, P. L. Lanzi, N. A. Borghese
- Year: 2012
- Citations: 146
Transient reversal of the stretch reflex in human arm muscles
- Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
- Year: 1991
- Citations: 144
Computational intelligence and game design for effective at-home stroke rehabilitation
- Authors: N. A. Borghese, M. Pirovano, P. L. Lanzi, S. Wüest, E. D. de Bruin
- Year: 2013
- Citations: 139
Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity
- Authors: R. Oberti, M. Marchi, P. Tirelli, A. Calcante, M. Iriti, A. N. Borghese
- Year: 2014
- Citations: 128
Usability and effects of an exergame-based balance training program
- Authors: S. Wüest, N. A. Borghese, M. Pirovano, R. Mainetti, R. van de Langenberg, …
- Year: 2014
- Citations: 121
Pattern recognition in 3D automatic human motion analysis
- Authors: G. Ferrigno, N. A. Borghese, A. Pedotti
- Year: 1990
- Citations: 121

Peixian Zhuang | Computer Science | Best Researcher Award

Posted on 25/10/202425/10/2024 by ScienceFather

Assoc. Prof. Dr. Peixian Zhuang | Computer Science | Best Researcher Award

Associate Professor at University of Science and Technology Beijing, China

Assoc. Prof. Dr. Peixian Zhuang is a distinguished researcher in computer vision, machine learning, and underwater image processing. Currently an Associate Professor at the University of Science and Technology Beijing, he earned his Ph.D. from Xiamen University in 2016. With over 50 published papers, including 9 ESI Highly Cited/Hot Papers and over 2800 Google Scholar citations, his work has garnered significant academic influence. Dr. Zhuang has led four national projects, holds six patents, and authored a book, showcasing his commitment to advancing technological innovation. His contributions have been recognized globally, as he was listed among the “World’s Top 2% Scientists” in 2023 and 2024. In addition to his research, he serves as an editor for various esteemed journals and has reviewed over 100 international journals and conferences. His collaborations with institutions like Tsinghua University further underscore his dedication to expanding the boundaries of AI and image processing.

Professional profile

Google Scholar

Education

Assoc. Prof. Dr. Peixian Zhuang completed his Ph.D. in 2016 at Xiamen University, where he laid the foundation for his research expertise in computer vision, underwater image processing, and machine learning. Following his doctoral studies, he began his academic career as a Lecturer at Nanjing University of Information Science & Technology (2017-2020), where he further honed his skills and contributed to his fields of study. To deepen his research, Dr. Zhuang undertook postdoctoral training at Tsinghua University (2020-2022), engaging in advanced projects and expanding his expertise in innovative AI technologies. His educational journey has been marked by significant contributions to his field, earning him recognition as a “World’s Top 2% Scientist” in recent years. Dr. Zhuang’s robust academic background has established him as a leading researcher and educator, influencing both national and international advancements in machine learning and image processing.

Professional Experience

Assoc. Prof. Dr. Peixian Zhuang has a diverse professional background in academia and research. Currently serving as an Associate Professor at the University of Science and Technology Beijing, he has made significant contributions to the fields of underwater image processing and machine learning. Prior to this role, he was a Lecturer at Nanjing University of Information Science & Technology from 2017 to 2020, where he developed and delivered courses while conducting impactful research. Following this, Dr. Zhuang completed a postdoctoral fellowship at Tsinghua University (2020-2022), where he engaged in advanced research projects and collaborations with leading scientists. He has led four national research projects and has authored over 50 papers, showcasing his commitment to scientific advancement. In addition to his academic roles, he serves as an area editor and guest editor for various reputable journals, reflecting his expertise and active engagement in the global research community.

Research Interest

Assoc. Prof. Dr. Peixian Zhuang specializes in several cutting-edge areas within the fields of computer vision and machine learning. His primary research interests include underwater image processing, where he focuses on improving the quality and usability of images captured in challenging underwater environments. He employs advanced algorithms and techniques to enhance image clarity and object recognition. Additionally, Dr. Zhuang is deeply invested in Bayesian machine learning, exploring probabilistic models that can improve decision-making processes in uncertain environments. His work on signal sparse representation and deep neural networks further highlights his commitment to developing innovative solutions for complex problems in artificial intelligence. By integrating these methodologies, Dr. Zhuang aims to advance the understanding and application of AI in real-world scenarios. His research not only contributes to theoretical advancements but also has practical implications in fields such as marine science, environmental monitoring, and robotics, making a significant impact on technology and research.

Awards and Honors

Assoc. Prof. Dr. Peixian Zhuang has received numerous awards and honors throughout his academic career, reflecting his significant contributions to research and innovation. He was recognized as one of the “World’s Top 2% Scientists” in both 2023 and 2024, an accolade that highlights his impact and influence in the field of computer vision and machine learning. In 2023, he received the IFAC EAAI Paper Prize Award, underscoring the excellence of his research publications. Additionally, his doctoral dissertation was awarded the Outstanding Doctoral Dissertations of Fujian Province in 2017, recognizing the quality and originality of his work during his Ph.D. studies. Dr. Zhuang has also been involved in various editorial roles for reputable journals, enhancing his recognition as a leading researcher in his field. These awards and honors reflect his dedication to advancing scientific knowledge and his commitment to excellence in research and education.

Conclusion

Peixian Zhuang’s profile makes him a strong candidate for the Best Researcher Award. His influential research, substantial publication record, recognition in global scientific rankings, and engagement in scholarly activities demonstrate his commitment and impact in the field of computer vision and underwater image processing. Addressing the outlined areas of improvement could enhance his profile further, positioning him as a leading researcher capable of impacting both academia and industry.

Publications top noted📜

Title: A retinex-based enhancing approach for single underwater image
Authors: X Fu, P Zhuang, Y Huang, Y Liao, XP Zhang, X Ding
Year: 2014
Citations: 566
Title: Underwater image enhancement using a multiscale dense generative adversarial network
Authors: Y Guo, H Li, P Zhuang
Year: 2019
Citations: 420
Title: Underwater image enhancement via minimal color loss and locally adaptive contrast enhancement
Authors: W Zhang, P Zhuang, HH Sun, G Li, S Kwong, C Li
Year: 2022
Citations: 373
Title: Bayesian retinex underwater image enhancement
Authors: P Zhuang, C Li, J Wu
Year: 2021
Citations: 255
Title: Underwater image enhancement with hyper-laplacian reflectance priors
Authors: P Zhuang, J Wu, F Porikli, C Li
Year: 2022
Citations: 250
Title: Underwater image enhancement using an edge-preserving filtering retinex algorithm
Authors: P Zhuang, X Ding
Year: 2020
Citations: 93
Title: Underwater image enhancement via weighted wavelet visual perception fusion
Authors: W Zhang, L Zhou, P Zhuang, G Li, X Pan, W Zhao, C Li
Year: 2023
Citations: 86
Title: Removing stripe noise from infrared cloud images via deep convolutional networks
Authors: P Xiao, Y Guo, P Zhuang
Year: 2018
Citations: 80
Title: Underwater image enhancement via piecewise color correction and dual prior optimized contrast enhancement
Authors: W Zhang, S Jin, P Zhuang, Z Liang, C Li
Year: 2023
Citations: 77
Title: Non-uniform illumination underwater image restoration via illumination channel sparsity prior
Authors: G Hou, N Li, P Zhuang, K Li, H Sun, C Li
Year: 2023
Citations: 54
Title: CVANet: Cascaded visual attention network for single image super-resolution
Authors: W Zhang, W Zhao, J Li, P Zhuang, H Sun, Y Xu, C Li
Year: 2024
Citations: 49
Title: DewaterNet: A fusion adversarial real underwater image enhancement network
Authors: H Li, P Zhuang
Year: 2021
Citations: 49
Title: SSTNet: Spatial, spectral, and texture aware attention network using hyperspectral image for corn variety identification
Authors: W Zhang, Z Li, HH Sun, Q Zhang, P Zhuang, C Li
Year: 2022
Citations: 45
Title: Bayesian pan-sharpening with multiorder gradient-based deep network constraints
Authors: P Guo, P Zhuang, Y Guo
Year: 2020
Citations: 41
Title: GIFM: An image restoration method with generalized image formation model for poor visible conditions
Authors: Z Liang, W Zhang, R Ruan, P Zhuang, C Li
Year: 2022
Citations: 37

Imtiaz Ahmad | Computer Science | Best Researcher Award

Posted on 07/10/202407/10/2024 by ScienceFather

Mr. Imtiaz Ahmad | Computer Science | Best Researcher Award

Visiting lecturer at Hazara University Mansehra, Pakistan

Imtiaz Ahmad, a dedicated researcher and educator from Pakistan, holds a Master’s degree in Computer Science from Hazara University, with a focus on wireless sensor networks. His thesis, titled “Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Networks,” reflects his expertise in optimizing data transmission for modern networks. Imtiaz has published research in reputable journals, including Knowledge-Based Systems and VFAST Transactions on Software, focusing on wireless sensor networks and mobile edge computing. With several years of teaching experience at institutions like Hazara University, he has mentored students and contributed to academic growth. His achievements include the Best Researcher Award and several student accolades. Additionally, he holds certifications like Microsoft Office Specialist and vocational training in computers. Imtiaz is a promising researcher with strengths in data aggregation, mobile computing, and teaching, and he continues to make valuable contributions to the field of computer science.

Professional profile

ORCID Profile

Education

Imtiaz Ahmad holds a Master’s degree in Computer Science from Hazara University Mansehra, which he completed in March 2021 with a commendable CGPA of 3.71/4.00. His master’s thesis focused on developing an “Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Networks,” showcasing his expertise in advanced computing concepts. Prior to this, he earned a Bachelor of Science in Information Technology from the University of Malakand in March 2015, achieving a CGPA of 2.95/4.00. His undergraduate thesis was centered on creating an “Online Hospital Management System,” which streamlined patient reservations and record management. Imtiaz also gained valuable experience through an internship at Hazara University, where he addressed technical issues related to system and application software. His educational background reflects a strong foundation in computer science and information technology, emphasizing both theoretical knowledge and practical application.

Professional Experience

Mr. Imtiaz Ahmad has accumulated valuable professional experience in academia and technical roles. Currently, he serves as a Visiting Lecturer at Hazara University Mansehra, where he is responsible for planning and delivering lectures, supervising final year projects, and assessing student progress. Previously, he held positions as a Computer Science Lecturer at Abaseen Public School and College and New Shaheen College of Commerce, where he implemented computer education programs and provided hands-on training in programming languages.

Additionally, during his internship at Hazara University, he gained practical experience in resolving technical issues, installing software, and setting up multimedia for national conferences. His diverse roles demonstrate his commitment to education and his ability to convey complex concepts to students, while also highlighting his technical skills in information technology. This blend of teaching and technical expertise positions him as a promising educator and researcher in the field of computer science.

Research Interest

Mr. Imtiaz Ahmad’s research interests lie primarily in the fields of wireless sensor networks, mobile edge computing, and data aggregation methodologies. His work focuses on developing adaptive and priority-based models that enhance the efficiency and reliability of data transmission in sensor networks. By optimizing scheduling techniques, Imtiaz aims to improve the performance of wireless systems, making them more resilient to data loss and delays. He is also interested in mobility prediction and task migration within mobile edge computing environments, exploring innovative solutions that facilitate seamless connectivity and resource management. Through his research, Imtiaz seeks to contribute to the advancement of smart technologies and the Internet of Things (IoT), addressing critical challenges in data management and network performance. His commitment to applying theoretical knowledge to real-world applications underscores his desire to drive impactful innovations in computer science.

Awards and Honors

Mr. Imtiaz Ahmad, a dedicated researcher and educator in computer science, has garnered several prestigious awards and honors throughout his academic journey. In 2024, he received the Best Researcher Award at the International Academic Awards, recognizing his impactful research on adaptive data aggregation models in wireless sensor networks. Previously, in 2020, he was honored with the Best Student Researcher Award from the Department of Computer Science at Hazara University, highlighting his exceptional contributions during his studies. Additionally, he was named the Student of the Year at Hazara University in 2019, further showcasing his academic excellence. Imtiaz was also awarded a laptop under the Prime Minister’s Laptop Scheme for High Achievers by the Higher Education Commission of Pakistan in 2018. These accolades reflect his commitment to research and education, marking him as a prominent figure in his field.

Conclusion

Imtiaz Ahmad has demonstrated a solid academic and research profile with notable strengths in computer science, particularly in wireless sensor networks and mobile edge computing. His publications in respected journals, combined with his teaching and professional certifications, make him a strong contender for the Best Researcher Award. However, to further solidify his candidacy, he could focus on enhancing the visibility and impact of his research through broader collaborations and more high-impact publications. Overall, his achievements suggest that he is well-suited for the award and poised to make significant contributions to his field in the future.

Publications top noted📜

Title: Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Networks
Authors: Imtiaz Ahmad, Muhammad Adnan, Noor ul Amin, Asif Umer, Adnan Khurshid, Khursheed Aurangzeb, Muhammad Gulistan
Journal: Knowledge-Based Systems
Year: 2024
DOI: 10.1016/j.knosys.2024.112393
ISSN: 0950-7051
Title: A Mobility Prediction-Based Adaptive Task Migration in Mobile Edge Computing
Authors: Jawad Arshed, Mehtab Afzal, Muhammad Hashim, Imtiaz Ahmad, Hasnat Ali, Ghulam Hussain
Journal: VFAST Transactions on Software Engineering
Year: 2024
DOI: 10.21015/vtse.v12i2.1768
ISSN: 2309-3978, 2411-6246

Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

Posted on 10/09/202410/09/2024 by ScienceFather

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

ORCID 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 📊🔬

Ruotao Xu | Computer Science | Best Researcher Award

Posted on 04/09/202404/09/2024 by ScienceFather

Dr. Ruotao Xu | Computer Science | Best Researcher Award

Associate Researcher at Institute of Super Robotics(Huangpu), China

Ruotao Xu is a dedicated researcher specializing in robotics, computer vision, and image processing. As a Postdoctoral Researcher and Associate Researcher, he is at the forefront of exploring advanced techniques in deep learning and image analysis. 🚀

Professional profile

Education📚

Ruotao Xu earned his Ph.D. in Electrical Engineering, where he focused on image processing and robotics. His educational background provides a solid foundation for his research endeavors and contributions to the field. 🎓📚

Professional Experience🏛️

Currently serving as a Postdoctoral Researcher at the Institute of Robotics and Automatic Information Systems, Xu has led several significant research projects. His role includes managing projects funded by national and provincial science foundations and contributing to various high-impact publications. 🛠️📈

Research Interest🌐

Xu’s research interests lie in deep learning, image processing, defocus deblurring, image inpainting, and texture representation. He is particularly focused on developing innovative solutions and technologies in these areas to advance the field of computer vision. 🧠🔍

Awards and Honors🎓

Principal Investigator for multiple high-profile projects funded by the National Natural Science Foundation of China. 🏆
Contributor to leading journals such as IEEE Transactions on Image Processing and IEEE/CVF International Conference on Computer Vision. 🥇📜

Achievements🏅

Principal Investigator for multiple high-profile projects funded by the National Natural Science Foundation of China. 🏆
Lead Author on influential papers in top journals such as IEEE Transactions on Image Processing and IEEE/CVF International Conference on Computer Vision. 📜
Innovator in Image Processing with a focus on deep learning, defocus deblurring, image inpainting, and texture representation. 🧠
Received Grants from provincial and national science foundations for cutting-edge research projects. 💵
Contributed to High-Impact Publications with significant citations, reflecting the impact of research on the field. 📚
Collaborated with Leading Researchers and institutions, enhancing the reach and application of his research findings. 🤝

Publications top noted📜

“Multi-view 3D shape recognition via correspondence-aware deep learning”
Authors: Y Xu, C Zheng, R Xu, Y Quan, H Ling
Journal: IEEE Transactions on Image Processing
Year: 2021
Citations: 40 📈
“Structure-texture image decomposition using discriminative patch recurrence”
Authors: R Xu, Y Xu, Y Quan
Journal: IEEE Transactions on Image Processing
Year: 2020
Citations: 20 📈
“Attention with structure regularization for action recognition”
Authors: Y Quan, Y Chen, R Xu, H Ji
Journal: Computer Vision and Image Understanding
Year: 2019
Citations: 19 📈
“Removing reflection from a single image with ghosting effect”
Authors: Y Huang, Y Quan, Y Xu, R Xu, H Ji
Journal: IEEE Transactions on Computational Imaging
Year: 2019
Citations: 19 📈
“Factorized tensor dictionary learning for visual tensor data completion”
Authors: R Xu, Y Xu, Y Quan
Journal: IEEE Transactions on Multimedia
Year: 2021
Citations: 17 📈
“Image quality assessment using kernel sparse coding”
Authors: Z Zhou, J Li, Y Quan, R Xu
Journal: IEEE Transactions on Multimedia
Year: 2020
Citations: 13 📈
“Cartoon-texture image decomposition using orientation characteristics in patch recurrence”
Authors: R Xu, Y Xu, Y Quan, H Ji
Journal: SIAM Journal on Imaging Sciences
Year: 2020
Citations: 10 📈
“Deep scale-aware image smoothing”
Authors: J Li, K Qin, R Xu, H Ji
Conference: ICASSP 2022
Year: 2022
Citations: 7 📈
“Enhancing texture representation with deep tracing pattern encoding”
Authors: Z Chen, Y Quan, R Xu, L Jin, Y Xu
Journal: Pattern Recognition
Year: 2024
Citations: 6 📈
“No-reference image quality assessment using dynamic complex-valued neural model”
Authors: Z Zhou, Y Xu, R Xu, Y Quan
Conference: 30th ACM International Conference on Multimedia
Year: 2022
Citations: 4 📈
“Deeply exploiting long-term view dependency for 3D shape recognition”
Authors: Y Xu, C Zheng, R Xu, Y Quan
Journal: IEEE Access
Year: 2019
Citations: 4 📈
“Deep blind image quality assessment using dual-order statistics”
Authors: Z Zhou, Y Xu, Y Quan, R Xu
Conference: IEEE International Conference on Multimedia and Expo (ICME)
Year: 2022
Citations: 3 📈
“Wavelet analysis model inspired convolutional neural networks for image denoising”
Authors: R Xu, Y Xu, X Yang, H Huang, Z Lei, Y Quan
Journal: Applied Mathematical Modelling
Year: 2024
Citations: 2 📈