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.

Sandeep Kumar Dasa | Computer Science | Best Innovator Award

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Mr. Sandeep Kumar Dasa | Computer Science | Best Innovator Award

Sr Engineer, Enterprise Data Privacy & Data Protection from Raymond James & Associates, United States

Mr. Sandeep Kumar Dasa is an accomplished technology professional with nearly nine years of experience in the IT sector. He specializes in Enterprise Data Privacy, Data Protection, and Artificial Intelligence (AI) and Machine Learning (ML). As a Senior Engineer, he plays a pivotal role in designing and implementing cutting-edge solutions that enhance data security and drive innovation. His expertise extends to thought leadership, with a strong intellectual property portfolio, including two patents. Additionally, he is an author and researcher, having published a book on AI/ML and multiple journal articles on deep learning and neural networks. Mr. Dasa is deeply invested in academic research and industry advancements, with a keen interest in reviewing papers on emerging technologies. His contributions to the field reflect his commitment to innovation and excellence, making him a valuable asset in both industry and academia.

Professional Profile

Education

Mr. Sandeep Kumar Dasa has a strong academic background that forms the foundation of his expertise in AI, ML, and data privacy. He holds a degree in Computer Science or a related field, equipping him with the necessary technical and analytical skills to excel in his profession. His education has provided him with a deep understanding of algorithm development, software engineering, and data security. Additionally, he has pursued continuous learning through certifications and specialized courses in AI, ML, and data privacy to stay at the forefront of technological advancements. His academic journey has been instrumental in shaping his innovative approach to problem-solving and research, further reinforcing his ability to contribute effectively to the field.

Professional Experience

With nearly a decade of experience in the IT industry, Mr. Sandeep Kumar Dasa has established himself as a leading expert in data privacy and AI/ML. As a Senior Engineer, he has been instrumental in designing and deploying enterprise-level solutions that enhance data protection and security. His expertise spans AI-driven automation, compliance frameworks, and advanced encryption techniques. His role involves consulting organizations on integrating AI/ML technologies to optimize efficiency and security. His professional journey includes collaborating with cross-functional teams, leading research-driven projects, and implementing patented innovations. His ability to merge theoretical knowledge with practical applications has enabled him to make a significant impact in the field.

Research Interest

Mr. Sandeep Kumar Dasa is deeply passionate about research in AI, ML, and data privacy. His primary focus lies in developing advanced AI models that enhance data security while ensuring regulatory compliance. He is particularly interested in deep learning, neural networks, and their applications in data protection. His research explores ways to leverage AI for secure data handling, risk mitigation, and automation. Additionally, he is keen on understanding the ethical implications of AI and ensuring responsible AI deployment. His commitment to research is reflected in his publications, patents, and active involvement in scholarly discussions. He seeks to contribute to the field by exploring novel AI-driven solutions for industry challenges.

Research Skills

Mr. Sandeep Kumar Dasa possesses a robust set of research skills that make him an effective innovator and thought leader in AI, ML, and data privacy. His expertise includes AI model development, deep learning, statistical analysis, and algorithm optimization. He is proficient in data protection methodologies, cryptographic techniques, and regulatory compliance standards. His technical skills encompass programming in Python, R, and other AI-focused languages, along with experience in cloud computing and big data analytics. Additionally, his ability to critically analyze emerging trends and apply research methodologies enables him to contribute valuable insights to the industry. His strong research acumen allows him to bridge the gap between theoretical advancements and practical applications.

Awards and Honors

Mr. Sandeep Kumar Dasa’s contributions to AI, ML, and data privacy have earned him notable recognition. He holds two patents that highlight his innovative capabilities in technology development. His book on AI/ML and multiple journal publications have established him as a thought leader in the field. He has been invited to review research papers on emerging technologies, demonstrating his expertise and credibility. Throughout his career, he has received accolades for his impactful work, including industry awards and acknowledgments for excellence in innovation. His dedication to research and technology has positioned him as a respected professional in his domain.

Conclusion

Mr. Sandeep Kumar Dasa is a distinguished professional with a strong background in AI, ML, and data privacy. His extensive experience, combined with his research contributions and innovative mindset, make him a valuable leader in the technology industry. His patents, publications, and professional expertise showcase his commitment to advancing the field. While he has already achieved significant milestones, continued collaboration, real-world implementation of his innovations, and further recognition in the industry could enhance his impact. His passion for research, dedication to knowledge-sharing, and technical proficiency make him a deserving candidate for awards and honors in technology and innovation.

Publications Top Notes

  • Optimizing Object Detection in Dynamic Environments With Low-Visibility Conditions

    • Authors: S. Belidhe, S.K. Dasa, S. Jaini

    • Citations: 3

  • Explainable AI and Deep Neural Networks for Continuous PCI DSS Compliance Monitoring

    • Authors: S.K.D. Sandeep Belidhe, Phani Monogya Katikireddi

    • Year: 2024

  • Proactive Database Health Management with Machine Learning-Based Predictive Maintenance

    • Authors: S.K. Dasa

    • Year: 2023

  • Graph-Based Deep Learning and NLP for Proactive Cybersecurity Risk Analysis

    • Authors: S.K. Dasa

    • Year: 2022

  • Securing Database Integrity: Anomaly Detection in Transactional Data Using Autoencoders

    • Authors: S.K. Dasa

    • Year: 2022

  • Autonomous Robot Control through Adaptive Deep Reinforcement Learning

    • Authors: S.K. Dasa

    • Year: 2022

  • Using Deep Reinforcement Learning to Defend Conversational AI Against Adversarial Threats

    • Authors: S.K.D. Phani Monogya Katikireddi, Sandeep Belidhe

    • Year: 2021

  • Machine Learning Approaches for Optimal Resource Allocation in Kubernetes Environments

    • Authors: S.B. Sandeep Kumar Dasa, Phani Monogya Katikireddi

    • Year: 2021

  • Intelligent Cybersecurity: Enhancing Threat Detection through Hybrid Anomaly Detection Techniques

    • Authors: S.B. Phani Monogya Katikireddi, Sandeep Kumar Dasa

    • Year: 2021

 

 

 

 

 

 

Qichuan Tian | Computer Science | Best Researcher Award

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Prof. Dr. Qichuan Tian | Computer Science | Best Researcher Award

Prof. Dr. at  Beijing University of Civil Engineering and Architecture, China

Qichuan Tian, born in 1971, is a distinguished professor and technical expert specializing in artificial intelligence, pattern recognition, and computer vision. He holds a Ph.D. in Engineering from Northwestern Polytechnical University (2006) and currently serves as a professor and master’s supervisor at Beijing University of Civil Engineering and Architecture (BUCEA). As the Director of the Department of Artificial Intelligence at the School of Intelligent Science and Technology, he leads research in biometrics, human-computer interaction, and deep learning. He is a member of multiple prestigious organizations, including the National Information Technology Standardization Technical Committee and the Chinese Society of Biomedical Engineering. His career spans academia and industry, with significant contributions in developing national standards, publishing books, and mentoring graduate students. Tian has also played a key role in over 20 research projects funded by national and provincial foundations, solidifying his reputation as a thought leader in AI and computational sciences.

Professional Profile

Education

Qichuan Tian has an extensive academic background in engineering. He obtained his Bachelor of Engineering (1993) and Master of Engineering (1996) from Taiyuan University of Science and Technology. In 2006, he completed his Doctor of Engineering at Northwestern Polytechnical University, specializing in artificial intelligence and computer vision. His academic training laid a strong foundation for his later contributions to AI, biometrics, and deep learning. His studies focused on integrating computational intelligence into practical applications, a theme that continues to define his research and professional endeavors.

Professional Experience

Tian has a diverse career in academia and research. Since 2012, he has served as the Head of the Department of Artificial Intelligence at BUCEA, where he spearheads innovative AI programs. From 2009 to 2010, he was a Visiting Scholar at Auburn University, USA, gaining international exposure in computer science. Between 2006 and 2008, he conducted postdoctoral research at Tianjin University. Previously, he held various roles at Taiyuan University of Science and Technology (1993–2012), where he advanced from Assistant Professor to Associate Professor and later became the Chief Leader of Circuits and Systems. His leadership has been instrumental in shaping AI research and education in China.

Research Interests

Tian’s research interests focus on artificial intelligence, pattern recognition, image processing, and deep learning. He specializes in biometric recognition, computer vision, and human-computer natural interaction. His work extends to security authentication, big data analysis, and IoT-based embedded systems. Tian has published over 100 journal and conference papers, authored six books, and contributed significantly to national standards in AI applications. His interdisciplinary research bridges theoretical advancements with practical AI implementations, making substantial contributions to the field.

Research Skills

With expertise in artificial intelligence and computer vision, Tian possesses strong research skills in deep learning algorithms, biometric recognition systems, and real-time image processing. He has successfully led projects in autonomous driving, green building AI integration, and complex object detection. His experience includes handling large-scale datasets, implementing machine learning frameworks, and designing AI-driven applications. Additionally, he has obtained over 50 invention patents and software copyrights, showcasing his ability to translate theoretical research into impactful technological innovations.

Awards and Honors

Tian’s contributions to academia and AI research have earned him multiple accolades. In 2024, he was recognized among CNKI’s Highly Cited Scholars (Top 5). He received the First Prize for Teaching Achievements at BUCEA in 2021 and was honored for developing a National First-Class Blended Online and Offline Course in 2020. Additionally, he was awarded the Outstanding Master’s Thesis Advisor Award in 2012. His accolades highlight his commitment to education, research, and AI-driven innovations, reinforcing his influence in the field of intelligent science and technology.

Conclusion

Qichuan Tian is a prominent scholar and AI expert dedicated to advancing artificial intelligence and biometric research. His leadership in academia, combined with his extensive research portfolio, underscores his impact on technological advancements in pattern recognition, computer vision, and human-computer interaction. With a career spanning over two decades, Tian has played a pivotal role in shaping AI education, national standards, and industry collaborations. His legacy continues to influence emerging AI technologies and inspire the next generation of researchers in intelligent computing.

Publications Top Notes

  • Title: An improved framework for breast ultrasound image segmentation with multiple branches depth perception and layer compression residual module

    • Authors: K. Cui, Qichuan Tian, Haoji Wang, Chuan Ma
    • Year: 2025

  • Title: Mobile Robot Path Planning Algorithm Based on NSGA-II

    • Authors: Sitong Liu, Qichuan Tian, Chaolin Tang
    • Year: 2024
    • Citations: 1

  • Title: OcularSeg: Accurate and Efficient Multi-Modal Ocular Segmentation in Non-Constrained Scenarios

    • Authors: Yixin Zhang, Caiyong Wang, Haiqing Li, Qichuan Tian, Guangzhe Zhao
    • Year: 2024

  • Title: Convolutional Neural Network–Bidirectional Gated Recurrent Unit Facial Expression Recognition Method Fused with Attention Mechanism

    • Authors: Chaolin Tang, Dong Zhang, Qichuan Tian
    • Year: 2023
    • Citations: 4

 

 

 

Navid Ghaffarzadeh | Engineering | Best Researcher Award

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Assoc Prof Dr. Navid Ghaffarzadeh | Engineering | Best Researcher Award

Assoc Prof Dr. Navid Ghaffarzadeh, Imam Khomeini International University, Iran

Assoc Prof Dr. Navid Ghaffarzadeh is an accomplished engineer recognized for his innovative contributions to the field of engineering. With a focus on [specific area of expertise], he has been instrumental in advancing research and development initiatives. His dedication and impactful work earned him the prestigious Best Researcher Award, highlighting his commitment to excellence and collaboration. Navid continues to inspire through his research, aiming to drive advancements that benefit both industry and society.

 

Profile:

Education

Navid Ghaffarzadeh earned his PhD in Electrical Engineering from Iran University of Science and Technology in Tehran, completing his studies from September 2007 to April 2011. Prior to that, he obtained his Master of Science in Electrical Engineering from Amirkabir University of Technology (Tehran Polytechnic) between September 2005 and August 2007. He also holds a Bachelor of Science in Electrical Engineering from Zanjan University, where he studied from September 2001 to June 2005.

Professional Activities

Navid Ghaffarzadeh is actively engaged in the academic community as a reviewer for numerous prestigious journals in the field of electrical engineering. His reviewing contributions span a wide array of publications, including Renewable and Sustainable Energy Reviews, Applied Energy, Journal of Energy Storage, and IEEE Transactions on Power Systems, among others, with impact factors ranging from 1.276 to 16.799. With over 100 reviewed journal papers, Navid plays a vital role in advancing research quality and integrity in the field. His extensive experience demonstrates his commitment to fostering innovation and excellence in engineering research.

Research Interests

Navid Ghaffarzadeh’s research interests encompass a wide range of cutting-edge topics in electrical engineering. He focuses on renewable energy, exploring innovative solutions in battery energy storage systems and electric vehicles. His work in microgrid and smart grid design aims to enhance the efficiency and reliability of power systems. Navid is particularly interested in the application of artificial intelligence in renewable energy systems, as well as power systems protection and transients. Additionally, he investigates intelligent systems and optimization techniques to improve power systems, with a strong emphasis on ensuring power quality.

Honors and Awards: ‌

Navid Ghaffarzadeh has received numerous honors and awards throughout his academic and professional career. In 2012, he was honored with the IET Science, Measurement and Technology Premium Award for his outstanding paper on power quality disturbances, recognized as one of the best published in the journal. He has been named Outstanding Researcher at I.K International University multiple times, in 2013, 2014, 2016, and 2020, and has also received the Outstanding Professor award in 2017, 2019, 2020, 2021, and 2023. Additionally, he was awarded the Best Iranian PhD Dissertation in power system protection, highlighting his significant contributions to the field. Navid achieved top rankings in his studies, finishing first among PhD electrical power engineering students at Iran University of Science and Technology with a GPA of 18.72 out of 20, first among M.Sc. students at Amirkabir University of Technology with a GPA of 19.18 out of 20, and first among B.Sc. students at Zanjan University with a GPA of 18.36 out of 20.

 

Publication Top Note

A. Bamshad, N. Ghaffarzadeh, “A novel smart overcurrent protection scheme for renewables-dominated distribution feeders based on quadratic-level multi-agent system (Q-MAS),” Electrical Engineering, vol. 105, pp. 1497–1539, February 2023.

S. Ansari, N. Ghaffarzadeh, “A Novel Superimposed Component-Based Protection Method for Multi Terminal Transmission Lines Using Phaselet Transform,” IET Generation, Transmission & Distribution, vol. 17, no. 1, pp. 469–485, January 2023.

A. HN. Tajani, A. Bamshad, N. Ghaffarzadeh, “A novel differential protection scheme for AC microgrids based on discrete wavelet transform,” Electric Power Systems Research, vol. 220, pp. 1-12, July 2023.

A. Zarei, N. Ghaffarzadeh, “Optimal Demand Response-based AC OPF Over Smart Grid Platform Considering Solar and Wind Power Plants and ESSs with Short-term Load Forecasts using LSTM,” Journal of Solar Energy Research, vol. 8, no. 2, pp. 1367-1379, April 2023.

M. Dodangeh, N. Ghaffarzadeh, “A New Protection Method for MTDC Solar Microgrids using on-line Phaselet, Mathematical Morphology, and Signal Energy Analysis,” Energy Engineering & Management, vol. 13, no. 1, pp. 40-53, March 2023 (in Persian).

M. Dodangeh, N. Ghaffarzadeh, “An Intelligent Protection Method for Multi-terminal DC Microgrids Using On-line Phaselet, Mathematical Morphology, and Fuzzy Inference Systems,” Energy Engineering & Management, vol. 12, no. 2, pp. 12-25, August 2022 (in Persian).

M. Dodangeh, N. Ghaffarzadeh, “Optimal Location of HTS-FCLs Considering Security, Stability, and Coordination of Overcurrent Relays and Intelligent Selection of Overcurrent Relay Characteristics in DFIG Connected Networks Using Differential Evolution Algorithm,” Energy Engineering & Management, vol. 10, no. 2, pp. 14-25, May 2020 (in Persian).

A. Inanloo Salehi, N. Ghaffarzadeh, “Fault detection and classification of VSC-HVDC transmission lines using a deep intelligent algorithm,” International Journal of Research and Technology in Electricity Industry, vol. 1, no. 2, pp. 161-170, September 2022.

N. Ghaffarzadeh, H. Faramarzi, “Optimal Solar plant placement using holomorphic embedded power flow considering the clustering technique in uncertainty analysis,” Journal of Solar Energy Research, vol. 7, no. 1, pp. 997-1007, Winter 2022.

N. Ghaffarzadeh, A. Bamshad, “A new approach to AC microgrids protection using a bi-level multi-agent system,” International Journal of Research and Technology in Electricity Industry, vol. 1, no. 1, pp. 66-74, March 2022.

Amel SAHLI | Computer Science | Best Researcher Award

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MS. Amel SAHLI | Computer Science | Best Researcher Award

École Nationale des Sciences de l’Informatique , Tunisia

Amel Sahli is a dedicated researcher pursuing her PhD in computer science at the École Nationale des Sciences de l’Informatique in Tunisia, focusing on optimizing e-learning processes through AI and key performance indicators. She holds a Master’s degree in information systems and has published significant work on performance measurement in education. Sahli’s diverse professional background includes roles as a contract lecturer and various internships, providing her with practical insights and teaching experience. Her technical skills in programming and web development, coupled with her proficiency in Arabic, French, and English, enhance her ability to engage with the international research community. Amel Sahli’s commitment to advancing educational methodologies through her research makes her a strong candidate for the Best Researcher Award, highlighting her potential to contribute meaningfully to the field of education technology.

 

Profile:

Education

Amel Sahli is currently pursuing her PhD in computer science at the École Nationale des Sciences de l’Informatique (ENSI) in Tunisia. Her doctoral research focuses on developing an integrated approach that leverages artificial intelligence (AI) and key performance indicators (KPIs) to optimize e-learning processes. Prior to her PhD, she earned a Master’s degree in information systems and web technologies, where she studied performance measurement in educational settings. This followed her Bachelor’s degree in computer science, during which she designed and implemented web applications for educational management. Sahli’s academic journey has been marked by consistent excellence, earning distinctions in her studies and developing a strong foundation in both theoretical and practical aspects of computer science. Her educational background not only highlights her technical competencies but also underscores her commitment to advancing the field of education through innovative research.

Professional Experiences

Amel Sahli has gained diverse professional experience that enriches her academic pursuits. She began her career as a bank intern and a counter agent, where she honed her customer service and operational skills. Following these roles, she interned at the Institut Supérieur d’Informatique du Kef, further deepening her understanding of information technology in educational contexts. In 2023, she transitioned into academia as a part-time lecturer, sharing her expertise in computer science with students. Currently, Sahli is engaged in research at the RIADI laboratory at the Université de la Manouba, where she applies her knowledge of artificial intelligence and KPIs to enhance e-learning processes. This combination of practical experience and academic engagement positions her as a well-rounded professional, capable of bridging theory and practice effectively. Sahli’s journey reflects her commitment to continuous learning and development in both research and teaching.

Research Skills

Amel Sahli possesses a robust set of research skills that are essential for her academic pursuits. Her expertise in quantitative and qualitative research methodologies allows her to design comprehensive studies that yield meaningful insights. Proficient in data analysis, Sahli employs statistical tools to interpret complex datasets, ensuring her findings are both reliable and impactful. Additionally, her experience in academic writing and publication equips her to effectively communicate her research outcomes to diverse audiences. Sahli’s ability to critically evaluate existing literature enables her to identify gaps in knowledge, guiding her own research questions. Her strong organizational skills facilitate the management of research projects, from initial conception to final execution. Moreover, her proficiency in various programming languages and web development enhances her capability to create innovative solutions within her research, particularly in optimizing e-learning processes. Overall, Sahli’s comprehensive research skill set positions her as a valuable contributor to the field of computer science and education technology.

Award and Recognition

Amel Sahli has been recognized for her outstanding contributions to the field of computer science and education. Notably, she participated in the “Inspiring Research & Innovation Using IEEE Publications” event, demonstrating her commitment to advancing research practices. Additionally, she attended the “23rd International Conference on Intelligent Systems Design and Applications,” where she engaged with leading experts and shared her insights. Her certifications from prestigious organizations, including Google and Microsoft, further attest to her dedication to continuous learning and professional development. Moreover, Sahli’s article on performance measurement in educational processes has been published in Procedia Computer Science, enhancing her visibility in academic circles. These recognitions not only reflect her hard work and innovation but also position her as a rising star in her field, earning her respect among peers and contributing to her eligibility for the Best Researcher Award.

Conclusion

In conclusion, Amel Sahli exemplifies the qualities sought in a candidate for the Best Researcher Award. Her academic journey, characterized by a robust educational background in computer science and information systems, has equipped her with the necessary tools to conduct meaningful research. Her focus on optimizing e-learning processes through the integration of AI and KPIs showcases her innovative approach to addressing contemporary educational challenges. Furthermore, her contributions to peer-reviewed journals and participation in international conferences illustrate her commitment to advancing knowledge in her field. Sahli’s diverse professional experiences, ranging from teaching to research, highlight her multifaceted skill set and adaptability. With her proficiency in multiple languages and technical expertise, she stands out as a collaborative researcher poised to make a lasting impact in education technology. Thus, Amel Sahli is not only a deserving nominee but also a potential leader in shaping the future of educational practices.

Publication Top Note

  • Conference Paper in Procedia Computer Science
    • Title: Performance Measurement of Reading Teaching-Learning Business Processes: Case of Whole-Word and Syllabic Reading Methods in Primary Schools
    • Authors: Amel Sahli, A. Mejri, A. Louati
    • Year: 2024
    • Citations: 0
  • Conference Paper in Lecture Notes in Networks and Systems
    • Title: Performance Measurement of Reading Teaching-Learning Business Processes: Case of Whole-Word and Syllabic Reading Methods in Primary Schools
    • Authors: Amel Sahli, A. Mejri, A. Louati
    • Year: 2024
    • Citations: 0