Tag: AI Ethics Award

Xiaohan Tu | Artificial Intelligence | Women Researcher Award

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Prof. Xiaohan Tu | Artificial Intelligence | Women Researcher Award

Zhengzhou Police University, China

Dr. Xiaohan Tu is an accomplished researcher and educator in computer science, currently serving as an Associate Professor at Zhengzhou Police University, China. She earned her M.Sc. (2017) and Ph.D. (2021) degrees in Computer Science and Technology from Hunan University, Changsha, China, where she developed strong expertise in cyber-physical systems, computer vision, and machine learning. In her professional career, Dr. Tu has demonstrated outstanding academic leadership, having successfully led four provincial and ministerial-level research projects and six departmental-level projects, while also contributing as a participant in the National Natural Science Foundation of China project on Smart Inspection Robots for catenary systems. Her research interests span applied artificial intelligence, deep learning, computer vision, robotics, and intelligent security technologies, with more than 23 publications indexed in IEEE and Scopus, earning 224 citations and an h-index of 9. She possesses strong research skills in algorithm optimization, feature extraction, LiDAR and point cloud analysis, monocular depth estimation, and real-time AI deployment on embedded and edge devices. Alongside research, she has compiled a provincial-level textbook and shown exceptional dedication to student mentorship, guiding her students to win 17 national awards, 58 provincial or ministerial awards, and 8 university-level awards in robotics, artificial intelligence, and Ministry of Education Category A competitions. Dr. Tu’s outstanding contributions have been recognized with multiple honors, including first prize in university-level teaching achievement, Outstanding Instructor awards for four consecutive years at the China Robot and Artificial Intelligence Competition, and the Outstanding Organization Award from the National Video Investigation Technology and Special Photography Professional Committee. Additionally, she serves as a reviewer for several prestigious IEEE journals, further underlining her professional recognition in the international research community. In conclusion, Dr. Xiaohan Tu’s exceptional academic qualifications, innovative research outputs, mentorship achievements, and professional honors establish her as a highly influential scholar with strong potential to advance AI-driven cyber-physical systems and intelligent security applications at both national and international levels.

Profile: Scopus

Featured Publication

  1. Tu, X., Yang, L. T., Liu, S., & Li, R. (2024). Accelerated feature extraction and refinement for improved aerial scene categorization. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–17.

  2. Tu, X., Zhang, C., Liu, S., Xu, C., & Li, R. (2023). Point cloud segmentation of overhead contact systems with deep learning in high-speed rails. Journal of Network and Computer Applications, 216, 103671.

  3. Tu, X., Zhang, C., Zhuang, H., Liu, S., & Li, R. (2024). Fast drone detection with optimized feature capture and modeling algorithms. IEEE Access, 12, 108374–108388.

  4. Liu, S., Tu, X., Xu, C., & Li, R. (2022). Deep neural networks with attention mechanism for monocular depth estimation on embedded devices. Future Generation Computer Systems, 131, 137–150.

  5. Liu, S., Yang, L. T., Tu, X., Li, R., & Xu, C. (2022). Lightweight monocular depth estimation on edge devices. IEEE Internet of Things Journal, 9(17), 16168–16180.

Nadeem Khanday | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Nadeem Khanday | Computer Science | Best Researcher Award

Assistant Professor from National Institute of Technology Srinagar, India

Dr. Nadeem Yousuf Khanday is an accomplished academic and researcher in Computer Science & Engineering, currently serving as an Assistant Professor at the School of Computer Science, UPES, Dehradun, India. With a strong academic foundation and a passion for advanced computing technologies, he has contributed extensively to the fields of artificial intelligence, machine learning, and deep visual learning. His research outputs include high-impact journal publications, international conference presentations, patents, and book chapters with globally recognized publishers. Dr. Khanday is deeply involved in exploring innovative AI techniques that address real-world challenges, including healthcare diagnostics, crop disease detection, cloud computing, and smart environments. He is also a certified GATE, UGC-NET, and JK-SET qualifier, emphasizing his academic excellence. Throughout his career, he has taught a variety of technical subjects and mentored students in core areas of computer science. He brings a balanced combination of research, teaching, and applied innovation to the academic domain. With a growing body of interdisciplinary work, Dr. Khanday continues to build his reputation as a future-oriented researcher contributing to both academia and industry. His deep commitment to scholarly excellence and emerging technologies positions him as a deserving candidate for recognition in prestigious research awards.

Professional Profile

Education

Dr. Nadeem Yousuf Khanday has pursued a rigorous academic trajectory in Computer Science & Engineering. He earned his Doctor of Philosophy (Ph.D.) from the prestigious National Institute of Technology (NIT), Srinagar, focusing on advanced computing technologies and artificial intelligence. Prior to his doctorate, he completed his Master of Technology (M.Tech) from Vivekananda Global University, Jaipur, where he achieved an outstanding CGPA of 9.69 in Computer Science & Engineering, demonstrating his academic strength and subject mastery. His undergraduate studies were conducted at Visvesvaraya Technological University (VTU), Belgaum, where he obtained a Bachelor of Engineering (B.E.) degree in Computer Science & Engineering with a commendable academic record. Dr. Khanday has also qualified national-level competitive exams including the Graduate Aptitude Test in Engineering (GATE) and University Grants Commission National Eligibility Test (UGC-NET), as well as JK-SET, qualifying him for Assistant Professorship roles in Indian universities. These qualifications reflect his high-level proficiency in the domain and commitment to continued academic growth. His academic background provides a strong foundation for his research endeavors, enabling him to tackle complex computing problems and advance the frontier of knowledge in artificial intelligence, machine learning, and computer vision.

Professional Experience

Dr. Nadeem Yousuf Khanday possesses diverse and dynamic professional experience across some of India’s reputed institutions. He is currently employed as a Regular Assistant Professor at the School of Computer Science (SoCS), UPES Dehradun since June 2023. Before this, he served as a Lecturer at the University of Kashmir, J&K, where he taught undergraduate and postgraduate computer science courses from March to June 2023. His earlier appointments include his tenure as an Assistant Professor (Contract) at NIT Srinagar from April 2017 to July 2018, and later as a Teaching Assistant (Research Scholar) from July 2018 to February 2023 at the same institute. These roles have helped him accumulate extensive experience in teaching core computer science courses such as Artificial Intelligence, Operating Systems, Data Structures, and Computer Architecture. Throughout his career, Dr. Khanday has skillfully blended teaching with hands-on research, working on projects related to visual learning, deep learning, and intelligent systems. His progressive journey from contract roles to full-time professorship demonstrates his steady academic development and increasing responsibilities. With significant academic leadership and research roles, he is well-positioned to lead innovative educational and research initiatives in AI and computing.

Research Interests

Dr. Nadeem Yousuf Khanday’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, and Computer Vision, with a particular focus on deep visual learning and few-shot learning models. He explores innovative solutions to computational challenges involving limited data samples, aiming to improve learning accuracy and cross-domain generalization. His research extends into practical domains such as healthcare diagnostics, agricultural disease prevention, cloud computing optimization, and smart IoT-based systems. Dr. Khanday has investigated topics including convolutional neural networks for COVID-19 prognosis, metric learning models for classification, and AI-driven smart farming using 5G networks. His recent work has integrated Large Language Models (LLMs) and Generative AI to enhance decision-making systems in medical and industrial contexts. His interdisciplinary approach combines theoretical models with real-world applications, contributing to sustainable development through intelligent computing. Dr. Khanday’s research aims not only to push academic boundaries but also to provide practical, scalable solutions for modern societal challenges. His continuous engagement with cutting-edge technologies and publication in top-tier journals solidify his status as a thought leader in visual intelligence and machine learning systems.

Research Skills

Dr. Nadeem Yousuf Khanday possesses a strong portfolio of research skills that span multiple domains in computing. He is proficient in developing machine learning algorithms, deep learning architectures, and advanced image processing models for varied applications. His expertise includes designing few-shot learning frameworks, enhancing cross-domain classification performance, and deploying convolutional neural networks for medical image analysis and smart diagnostics. He has hands-on experience with AI-based anomaly detection, visual segmentation systems, and cloud environment optimization using hybrid fuzzy and swarm intelligence methods. Dr. Khanday is also skilled in patent writing, having developed innovative systems for crop disease detection and motorcycle safety. His publication record reflects his ability to effectively communicate complex methodologies, backed by data-driven validation and practical implementation. Additionally, his collaboration in multi-author projects and book chapters indicates strong academic teamwork and interdisciplinary engagement. His teaching and research experiences across different institutions have also honed his ability to mentor students and lead academic discussions. Equipped with technical, analytical, and conceptual research skills, Dr. Khanday continues to contribute impactful and scalable innovations across emerging fields like generative AI, IoT systems, and smart computing.

Awards and Honors

Dr. Nadeem Yousuf Khanday has received various forms of recognition for his scholarly achievements and research excellence. Notably, he has qualified multiple national-level eligibility exams, such as GATE, UGC-NET, and JK-SET, highlighting his academic distinction and competency to teach at the university level. In 2023, he was awarded recognition for his impactful contributions to AI-driven visual understanding and applications, as reflected in his high-impact publications and patents. His patent work, including an apparatus for auto-detection of crop diseases and motorcycle safety systems, has been acknowledged for its potential technological and societal value. Dr. Khanday’s research has also gained visibility through SCOPUS- and SCI-indexed publications with top journals like Computer Science Review and Neural Computing and Applications. His invited book chapters published by Taylor and Francis, Springer Nature, and Cambridge University Press underline his reputation among international academic publishers. Furthermore, he has presented at international conferences in Europe and Asia, receiving acclaim for his work on machine vision, fuzzy systems, and cloud intelligence. These accolades reflect both his individual excellence and collaborative impact within the research community.

Conclusion

Dr. Nadeem Yousuf Khanday exemplifies the profile of a high-caliber academician and innovative researcher with notable achievements in the fields of artificial intelligence, deep learning, and computer vision. Through a strong foundation in computer science education and a wealth of research experience, he has consistently contributed to advancing both theory and practice. His multidisciplinary research in healthcare, smart agriculture, and intelligent systems, along with a growing list of high-impact publications, patents, and book contributions, sets him apart as a forward-thinking scholar. His teaching experience across reputed Indian institutions and his ability to combine pedagogy with practical applications further enhance his value to academia. Dr. Khanday’s commitment to solving real-world problems using machine learning and AI tools not only enhances academic discourse but also promotes sustainable innovation. His emerging collaborations, international conference participation, and national recognitions affirm his credibility and future potential. In light of his qualifications, scholarly output, and research relevance, he stands as a highly deserving candidate for the Best Researcher Award, with the capacity to influence the global research community and contribute significantly to technological advancement

  1. Covariance-based Metric Model for Cross-domain Few-shot Classification and Learning-to-generalization
    📘 Journal: Applied Intelligence, 2023
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  2. Learned Gaussian ProtoNet for Improved Cross-domain Few-shot Classification and Generalization
    📘 Journal: Neural Computing and Applications, 2023
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  3. Deep Insight: Convolutional Neural Network and Its Applications for COVID-19 Prognosis
    📘 Journal: Biomedical Signal Processing and Control, 2021
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  4. Taxonomy, State-of-the-art, Challenges and Applications of Visual Understanding: A Review
    📘 Journal: Computer Science Review, 2021
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

Abid Iqbal | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Abid Iqbal | Artificial Intelligence | Best Researcher Award

Assistant Professor at King Faisal University, Saudi Arabia

Dr. Abid Iqbal is an accomplished Assistant Professor at the University of Engineering and Technology Peshawar, specializing in Electrical Engineering and artificial intelligence. He earned his Ph.D. from Griffith University, Australia, where he researched piezoelectric energy harvesters. With a strong academic background, he ranked first in his Master’s program at Ghulam Ishaq Khan Institute, Pakistan. Dr. Iqbal has a diverse professional experience, including roles as an Electrical Design Engineer and Research Assistant. His expertise encompasses developing embedded devices and innovative teaching methodologies, mentoring students, and conducting impactful research. He has successfully secured funding for multiple projects in AI applications for health and agriculture. Dr. Iqbal’s publication record includes numerous papers in reputable journals, reflecting his commitment to advancing knowledge in his field. His technical skills in programming and software further enhance his research capabilities, making him a valuable asset to academia and industry.

Profile

Education

Dr. Abid Iqbal is a highly accomplished academic with a solid educational foundation in electrical and electronics engineering. He earned his Ph.D. from the Queensland Micro- and Nanotechnology Centre at Griffith University, Australia, from April 2013 to February 2017. His doctoral research focused on the design, fabrication, and analysis of aluminum nitride (AlN)/silicon carbide (SiC)-based piezoelectric energy harvesters, contributing significantly to renewable energy technologies. Prior to his Ph.D., Dr. Iqbal completed his Master’s degree in Electronics Engineering at the Ghulam Ishaq Khan Institute in Topi, Swabi, Pakistan, graduating with a remarkable GPA of 3.88/4 and securing the top position in his class. His academic journey began with a Bachelor’s degree in Electrical Engineering from the University of Engineering & Technology in Peshawar, Pakistan, where he was recognized as an outstanding student. Dr. Iqbal’s educational background reflects his dedication and expertise in his field, laying a strong foundation for his professional career.

Professional Experience

Dr. Abid Iqbal is an accomplished electrical engineer currently serving as an Assistant Professor at the University of Engineering and Technology Peshawar since August 2019. In this role, he has been instrumental in teaching undergraduate courses in Electrical Engineering, developing innovative teaching methods, and mentoring students on research projects. Prior to this position, he worked as an Electrical Design Engineer at Alliance Power and Data in Australia, focusing on ERGON and NBN projects. He also contributed to the development of embedded systems for individuals with disabilities while employed as an Electronic Engineer at Community Lifestyle Support. His research experience includes a significant role as a Research Assistant at Griffith University, where he worked on piezoelectric devices for harsh environments and gained expertise in various semiconductor fabrication processes. Additionally, he has served as a lecturer at Comsat Institute of Information Technology and worked as a research associate at the City University of Hong Kong, demonstrating a robust and diverse professional background in academia and industry.

Research Interest

Dr. Abid Iqbal’s research interests lie at the intersection of electrical engineering and artificial intelligence, focusing on the development of innovative technologies that enhance energy efficiency and improve healthcare outcomes. His work includes designing and fabricating advanced piezoelectric energy harvesters using AlN/SiC materials, aimed at harnessing renewable energy sources. Additionally, Dr. Iqbal is deeply involved in projects utilizing artificial intelligence for agricultural applications, such as real-time disease detection in crops, and developing telehealth systems that leverage IoT technology to monitor patient health remotely. He has a keen interest in embedded systems and the design of hardware for assistive technologies, including portable ventilators and muscle sensors for individuals with disabilities. Through his research, Dr. Iqbal aims to contribute to sustainable energy solutions and advancements in healthcare technology, fostering a multidisciplinary approach that integrates engineering principles with artificial intelligence for practical applications.

Research Skills

Dr. Abid Iqbal possesses a robust set of research skills that underscore his expertise in Electrical Engineering and artificial intelligence. His extensive experience in designing and fabricating piezoelectric energy harvesters highlights his proficiency in materials science and device characterization. Dr. Iqbal is adept at using advanced simulation tools such as COMSOL, Ansys, and Coventorware, which facilitate in-depth analysis and optimization of microelectromechanical systems (MEMS). His work on artificial intelligence applications in telehealth and agricultural systems showcases his ability to integrate machine learning techniques with practical engineering solutions. Additionally, Dr. Iqbal has a strong background in programming languages such as Python and MATLAB, enhancing his capability to develop innovative software solutions for complex engineering problems. His involvement in funded projects and numerous publications further illustrates his commitment to advancing research and contributing to knowledge in his field. Overall, Dr. Iqbal’s diverse skills position him as a valuable asset to any research team.

Award and Recognition

Dr. Abid Iqbal is a distinguished electrical engineer and academic known for his significant contributions to the field of electrical and electronics engineering. He has received multiple accolades for his research and academic excellence, including the IGNITE funding for four innovative projects focused on machine learning applications in health and agriculture. Dr. Iqbal was awarded publication scholarships and prestigious Griffith University PhD scholarships, recognizing his outstanding academic performance during his doctoral studies. Additionally, he ranked first among his peers in the Master’s program at Ghulam Ishaq Khan Institute, further demonstrating his commitment to excellence in engineering. His dedication to teaching and mentoring future engineers is evident in his role as an Assistant Professor at the University of Engineering and Technology Peshawar, where he has developed innovative curricula and guided numerous student research projects. Dr. Iqbal’s work has been widely published, contributing significantly to advancements in artificial intelligence, embedded systems, and renewable energy technologies.

Conclusion

Dr. Abid Iqbal is a highly qualified candidate for the Best Researcher Award, demonstrating exceptional expertise in Electrical Engineering and a strong commitment to research and education. His accomplishments in renewable energy research, successful project management, and dedication to mentoring future engineers make him a standout choice. While he has areas for growth, particularly in expanding collaborative networks and enhancing commercialization efforts, his current achievements and potential for future contributions position him as an inspiring figure in his field. This award would not only recognize his past efforts but also encourage his continued pursuit of excellence in research and education.

Publication Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Year: 2024
    • Journal: Results in Engineering
    • Volume/Page: 24, 102994
  2. Novel dual absorber configuration for eco-friendly perovskite solar cells: design, numerical investigations and performance of ITO-C60-MASnI3-RbGeI3-Cu2O-Au
    • Authors: Hasnain, S.M., Qasim, I., Iqbal, A., Amin Mir, M., Abu-Libdeh, N.
    • Year: 2024
    • Journal: Solar Energy
    • Volume/Page: 278, 112788

 

 

 

Ali Ghandi | Artificial intelligence | Best Researcher Award

Published on by Shen Awards

Ali Ghandi | Artificial intelligence | Best Researcher Award

PhD, Sharif University of Technology, Iran.

Ali Ghandi is an innovative researcher and educator specializing in Artificial Intelligence, particularly in reinforcement learning and generative AI. Currently pursuing his Ph.D. at Sharif University of Technology, he is known for his groundbreaking work that enhances reinforcement learning processes by leveraging side-channel data. Ali’s academic journey began with a B.Sc. in Digital System Design, followed by an M.Sc. in Machine Learning, where he excelled as one of the top students. He has taught courses in Neural Networks and Deep Generative Models, effectively sharing his knowledge with students. His research has been recognized through publications in reputable journals and presentations at significant conferences, such as the Iran Workshop on Communication and Information Theory. Ali’s accomplishments include a top rank in a national entrance exam and membership in Iran’s National Elites Foundation, underscoring his exceptional capabilities and contributions to the field of AI and his commitment to advancing technology for practical applications.

Profile:

 

Education

Ali Ghandi has an impressive academic background in electrical and computer engineering, with a particular focus on Artificial Intelligence. He is currently pursuing a Ph.D. at Sharif University of Technology (SUT) in Tehran, where he is conducting innovative research aimed at improving reinforcement learning processes using side-channel data. Prior to his doctoral studies, Ali earned his Master’s degree in Machine Learning from SUT, where his thesis focused on analyzing IoT systems through location-based data, effectively modeling traffic based on dynamic maps and registered commutes. He completed his Bachelor’s degree in Digital System Design at the same university, where he developed an online coordinate system for managing thermal loads in IoT applications. Throughout his educational journey, Ali has consistently demonstrated academic excellence, evidenced by his top rankings in national examinations and competitive academic events, establishing him as a leading figure among his peers in the field of electrical engineering and AI.

Professional Experiences

Ali Ghandi has an impressive academic background in electrical and computer engineering, with a particular focus on Artificial Intelligence. He is currently pursuing a Ph.D. at Sharif University of Technology (SUT) in Tehran, where he is conducting innovative research aimed at improving reinforcement learning processes using side-channel data. Prior to his doctoral studies, Ali earned his Master’s degree in Machine Learning from SUT, where his thesis focused on analyzing IoT systems through location-based data, effectively modeling traffic based on dynamic maps and registered commutes. He completed his Bachelor’s degree in Digital System Design at the same university, where he developed an online coordinate system for managing thermal loads in IoT applications. Throughout his educational journey, Ali has consistently demonstrated academic excellence, evidenced by his top rankings in national examinations and competitive academic events, establishing him as a leading figure among his peers in the field of electrical engineering and AI.

 

Research skills

Ali Ghandi possesses a strong set of research skills that position him as a leading figure in the field of Artificial Intelligence. His primary focus is on reinforcement learning, where he has developed innovative approaches, such as utilizing side-channel data to enhance the learning process. Ali’s expertise extends to deep generative models, where he explores the potential of generative AI in various applications. Additionally, he is adept at massive data mining, allowing him to extract valuable insights from large datasets, which is crucial in today’s data-driven world. His research also includes analyzing IoT systems, particularly in modeling traffic using location-based data. This multifaceted skill set enables Ali to approach complex problems with a comprehensive perspective, combining theoretical knowledge with practical applications. His ability to publish in reputable journals and present at conferences demonstrates his commitment to advancing the field and contributing to the academic community.

 

Awards And Recoginition

Ali Ghandi has received numerous accolades that underscore his academic excellence and contributions to the field of Artificial Intelligence. He achieved a remarkable 68th rank in a highly competitive university entrance exam, placing him among the top candidates out of 250,000 participants. His outstanding performance in the International A-lympiad, where he ranked third, showcases his proficiency in applied mathematics within a global context. Additionally, Ali has been a member of Iran’s National Elites Foundation since 2013, reflecting his recognition as a leading talent in his field. His academic journey at Sharif University of Technology has been marked by multiple distinctions, including first place among students in his Digital Systems minor and second place among all M.Sc. Electrical Engineering students. These honors highlight Ali’s commitment to excellence in research and education, positioning him as a promising contributor to the advancement of Artificial Intelligence.

Conclusion

In conclusion, Ali Ghandi possesses a solid foundation of academic excellence, innovative research, and early recognition in his field. His focus on advanced topics within AI positions him well for the Best Researcher Award. By addressing areas for improvement, such as increasing the practical impact of his work and expanding his collaborative efforts, Ali can further enhance his candidacy for this prestigious recognition. His commitment to advancing knowledge in AI and machine learning makes him a strong contender for the award.

Publication Top Notes

  • Title: Ex-RL: Experience-based Reinforcement Learning
    Authors: Ghandi, A., Shouraki, S.B., Gholampour, I., Kamranian, A., Riazati, M.
    Year: 2025
    Citation: Information Sciences, 689, 121479 📚🤖
  • Title: Deep ExRL: Experience-Driven Deep Reinforcement Learning in Control Problems
    Authors: Ghandi, A., Shouraki, S.B., Riazati, M.
    Year: 2024
    Citation: 12th Iran Workshop on Communication and Information Theory (IWCIT 2024) 📄🔍