Saurabh Kumar | Computer Science | Best Researcher Award

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Mr. Saurabh Kumar | Computer Science | Best Researcher Award

Shri Ramswaroop Memorial University, India

Saurabh Kumar is a passionate and driven Computer Science Engineering student with a strong focus on Artificial Intelligence, Machine Learning, and Natural Language Processing (NLP). With a deep interest in solving complex real-world challenges, Saurabh has worked extensively on AI-driven projects, including fine-tuning state-of-the-art models, developing computer vision applications, and enhancing NLP systems. His expertise spans multiple domains, including deep learning, speech synthesis, and autonomous systems. Saurabh actively contributes to the tech community through open-source projects and research-driven initiatives. His commitment to continuous learning, innovation, and collaboration sets him apart as a dedicated researcher in AI.

Professional Profile

Education

Saurabh Kumar is currently pursuing a degree in Computer Science Engineering, specializing in Artificial Intelligence and Machine Learning. Throughout his academic journey, he has developed a strong foundation in data science, deep learning, and cloud computing. His coursework includes advanced machine learning algorithms, computer vision, NLP, and big data analysis. In addition to academic learning, he has actively participated in AI-focused bootcamps, hackathons, and online certifications to enhance his technical knowledge. His commitment to education is evident through his consistent efforts to bridge theoretical knowledge with practical applications in AI-driven research.

Professional Experience

Saurabh has gained hands-on experience through various AI-based projects and internships. His work includes developing a Vehicle Classification Model using deep learning and computer vision, creating an advanced Text-to-Speech (TTS) model, and building multiple real-time computer vision applications. Additionally, he has experience working with cloud platforms like IBM Cloud and using tools such as SQL, Tableau, and Docker for AI deployment. His ability to work with cutting-edge AI models and optimize them for real-world use cases highlights his technical acumen. Saurabh’s professional experience reflects a strong ability to innovate, research, and implement AI solutions effectively.

Research Interests

Saurabh Kumar’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, and Natural Language Processing. He is particularly passionate about Conversational AI, Reinforcement Learning, Explainable AI, and Generative AI. His work focuses on optimizing AI models for practical applications, enhancing NLP-based speech synthesis, and improving AI-driven automation. He is also interested in exploring AI ethics, fairness in machine learning, and the development of AI-driven assistive technologies. His continuous learning in AI research methodologies and practical deployment strategies showcases his commitment to pushing the boundaries of AI innovation.

Research Skills

Saurabh possesses a strong set of research skills, including data analysis, deep learning model optimization, and AI-driven problem-solving. He is proficient in Python, PyTorch, TensorFlow, OpenCV, and NLP frameworks such as Hugging Face. His expertise in AI extends to cloud computing, SQL-based data management, and deployment of machine learning models. He has hands-on experience with real-world AI challenges, including speech synthesis, computer vision applications, and text-based AI solutions. His ability to develop, fine-tune, and deploy AI models efficiently highlights his strong research-oriented approach.

Awards and Honors

Saurabh Kumar has been recognized for his contributions to AI and research. He has successfully completed the OpenCV Bootcamp, demonstrating expertise in Computer Vision and Deep Learning. His AI-driven projects have received recognition within the tech community, and his work in fine-tuning AI models has been acknowledged on various platforms. His commitment to advancing AI research is evident through his achievements in open-source contributions and AI development. These accolades showcase his dedication to continuous learning and impactful research in Artificial Intelligence.

Conclusion

Saurabh Kumar is a dedicated AI researcher and technology enthusiast committed to innovation, research, and problem-solving. His expertise in Artificial Intelligence, Machine Learning, and NLP, combined with his passion for AI-driven solutions, makes him a strong candidate for the Best Researcher Award. His extensive work in AI model development, contributions to open-source projects, and commitment to continuous learning set him apart as a future leader in AI research. By further expanding his research publications and collaborative efforts, he is well-positioned to make significant contributions to the field of AI.

Publications Top Notes

  1. Title: Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management
    Authors: T Maurya, S Kumar, M Rai, AK Saxena, N Goel, G Gupta
    Year: 2025

 

Tejasva Maurya | Computer Science | Best Researcher Award

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Mr. Tejasva Maurya | Computer Science | Best Researcher Award

Shri Ramswaroop Memorial University, India

Tejasva Maurya is a dedicated researcher specializing in artificial intelligence, deep learning, and data science. With a strong academic background in computer science and engineering, he has made significant contributions to AI-driven solutions in smart traffic management, healthcare applications, and natural language processing. His work focuses on applying advanced machine learning models to real-world challenges, particularly in image processing, sentiment analysis, and human-computer interaction. Tejasva has published research in reputable journals and book chapters, showcasing his expertise in AI and its interdisciplinary applications. He has also gained valuable industry experience through internships in data science and analytics, working on projects that optimize machine learning models and enhance data-driven decision-making. His technical proficiency includes programming in Python, deep learning frameworks like PyTorch, and working with Hugging Face models for NLP and computer vision tasks. With multiple achievements in AI research, including a Scopus-indexed publication and competition awards, Tejasva continues to push the boundaries of innovation in artificial intelligence. His long-term goal is to contribute groundbreaking research in AI while bridging the gap between theoretical advancements and practical implementations.

Professional Profile

Education

Tejasva Maurya is currently pursuing a Bachelor of Technology in Computer Science and Engineering at Shri Ramswaroop Memorial University, where he has developed a strong foundation in programming, machine learning, and AI-driven applications. His coursework has provided extensive exposure to algorithms, data structures, deep learning, and computer vision techniques. Prior to his undergraduate studies, he completed his Intermediate education under the CBSE Board in 2021, securing an impressive 88.88%, which highlights his academic excellence and analytical abilities. His passion for artificial intelligence and research was evident early on, leading him to explore AI-related projects and specialized training in machine learning. Throughout his education, he has engaged in practical AI applications, contributing to his ability to develop innovative solutions in deep learning, NLP, and computer vision. His university studies have been complemented by self-driven research initiatives and internships, allowing him to apply theoretical knowledge to real-world problems. Tejasva’s continuous learning approach and commitment to AI research position him as an emerging talent in the field of artificial intelligence.

Professional Experience

Tejasva Maurya has gained substantial industry experience through internships and research projects in data science and machine learning. As a Data Scientist Intern at DevTown (June 2023 – December 2023), he worked on developing and optimizing deep learning models using PyTorch for real-world applications, focusing on NLP, image classification, and generative adversarial networks (GANs). He was responsible for designing data pipelines, preprocessing data, and conducting exploratory data analysis, ensuring the models were efficient and accurate. Additionally, Tejasva worked as a Data Analyst Trainee at MedTourEasy (August 2023 – August 2023), where he specialized in data visualization and statistical analysis. His role involved extracting actionable insights from large datasets using Python and Tableau and collaborating with different teams to implement data-driven strategies. His professional experience has strengthened his ability to apply AI techniques to practical problems, enhancing his understanding of machine learning implementation in different sectors. Through these roles, he has built strong analytical skills and technical expertise, preparing him for more advanced research in artificial intelligence and data science.

Research Interests

Tejasva Maurya’s research interests lie in artificial intelligence, deep learning, natural language processing, and computer vision. His primary focus is on developing AI-driven solutions for real-world applications, including smart traffic management, healthcare technology, and human-computer interaction. His work in vehicle classification using deep learning demonstrates his expertise in YOLO-based object detection models and their application in traffic surveillance and smart city planning. Additionally, he is keen on sentiment analysis and speech processing, contributing to AI models that improve text-to-speech (TTS) synthesis and NLP-based insights. His interest in federated learning for agricultural applications highlights his commitment to interdisciplinary research, exploring AI’s role in optimizing farming techniques and market stability. Tejasva is also exploring artificial emotional intelligence for psychological and mental health assessments, aiming to create AI models that assist in mental health diagnosis and emotional analysis. With a strong foundation in machine learning and AI, he aims to bridge the gap between theoretical advancements and practical AI implementations, driving innovation in multiple domains.

Research Skills

Tejasva Maurya possesses advanced research skills in machine learning, deep learning, and AI model development. His technical expertise includes Python programming, with proficiency in PyTorch, scikit-learn, NumPy, and OpenCV for implementing AI-based solutions. He has hands-on experience in computer vision techniques, including real-time object detection, image segmentation, and gesture-based human-computer interaction, leveraging tools like Mediapipe and Haar Cascades. In natural language processing (NLP), he is skilled in text processing, speech-to-text, and fine-tuning transformer models using Hugging Face frameworks. His research methodology includes data preprocessing, model fine-tuning, hyperparameter optimization, and performance evaluation using metrics like mAP and F1-score. He is proficient in working with large-scale datasets and has successfully published research on vehicle classification, federated learning, and AI-based healthcare applications. Additionally, he has experience in GANs and diffusion models, focusing on synthetic media generation and speech dataset augmentation. His ability to integrate AI solutions across different fields demonstrates his versatility as a researcher and innovator.

Awards and Honors

Tejasva Maurya has received multiple accolades for his contributions to AI research and innovation. One of his most notable achievements is publishing a Scopus-indexed journal article, “Real-Time Vehicle Classification Using Deep Learning—Smart Traffic Management,” in Engineering Reports (Wiley), which underscores the real-world impact of his research. He has also co-authored multiple book chapters in prestigious publishers like Nova Science, Wiley, and Bentham Science, covering AI applications in healthcare, federated learning, and artificial emotional intelligence. His research has been recognized for its contribution to intelligent traffic systems, patient-centric healthcare, and AI-powered decision-making. In addition to his research achievements, he secured 1st position in KIMO’s-Edge’ 23 Technology Competition, a testament to his problem-solving skills and technical expertise. His consistent excellence in AI research and project development has positioned him as an emerging leader in the field of artificial intelligence, with a strong track record of achievements.

Conclusion

Tejasva Maurya is a promising researcher in artificial intelligence, with expertise in deep learning, NLP, and computer vision. His strong academic foundation, technical proficiency, and impactful research make him a strong contender for recognition as a leading researcher in AI. With multiple publications, real-world AI applications, and industry experience, he has demonstrated both theoretical knowledge and practical problem-solving abilities. While he has made significant contributions, focusing on publishing in high-impact AI conferences, securing patents, and expanding interdisciplinary collaborations would further enhance his research portfolio. His dedication to bridging AI theory with real-world applications highlights his potential to contribute groundbreaking advancements in artificial intelligence.

Publications Top Notes

  1. Title: Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management
    Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K., Goel, N., and Gupta, G.
    Publication: Engineering Reports, 7: e70082 (2025)
    DOI: https://doi.org/10.1002/eng2.70082

  2. Title: Patient Centric Healthcare
    Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K.
    Book: Harnessing the Power of IoT-Enabled Machine Learning in Healthcare Applications
    Editors: Mritunjay Rai, Ravindra Kumar Yadav, Neha Goel, and Maheshkumar H. Kolekar

  3. Title: Integrating Artificial Intelligence and Deep Learning in Classification and Taking Care of DFU
    Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K., Pandey, J.K.
    Book: Machine Learning-Based Decision Support Systems for Diabetic Foot Ulcer Care
    Editors: Mritunjay Rai, Jay Kumar Pandey, and Abhishek Kumar Saxena

  4. Title: Federated Learning-Based Approach for Crop Recommendation and Market Stability in Agriculture
    Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
    Book: Federated Learning for Smart Agriculture and Food Quality Enhancement
    Editors: Padmesh Tripathi, Bhanumati Panda, Shanthi Makka, Reeta Mishra, S. Balamurugan, and Sheng-Lung Peng

  5. Title: Artificial Emotional Intelligence for Psychological State and Mental Health Assessment
    Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
    Book: Artificial Emotional Intelligence: Fundamentals, Challenges and Applications
    Editors: Padmesh Tripathi, Krishna Kumar Paroha, Reeta Mishra, and S. Balamurugan

André Guimarães | Computer Science | Best Researcher Award

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Mr. André Guimarães | Computer Science | Best Researcher Award

Researcher at University of Beira Interior, Portugal

André Guimarães is a distinguished mechanical engineer and academic, renowned for his extensive contributions to mechanical engineering, industrial management, and digital transformation. With over a decade of professional experience in the manufacturing industry, he has seamlessly integrated practical expertise with academic pursuits. Currently, as a Ph.D. candidate in Industrial Engineering and Management at the University of Beira Interior, André is delving into advanced research areas, particularly focusing on Industry 4.0 and its implications for modern manufacturing processes. His role as a Guest Lecturer at the Polytechnic Institute of Viseu underscores his commitment to education and knowledge dissemination. André’s scholarly contributions include several scientific publications that explore the intersections of polymeric materials, lean management, and asset management. His active participation in various research projects highlights his dedication to advancing engineering practices and promoting digital transformation within the industry. André’s multifaceted career reflects a harmonious blend of industry experience, academic excellence, and a passion for fostering innovation in engineering.

Professional Profile

Education

André’s academic journey commenced with a Bachelor’s degree in Mechanical Engineering, laying a robust foundation in engineering principles. He further augmented his expertise by obtaining a Master’s degree in Mechanical Engineering and Industrial Management, where he engaged in research focusing on the development of novel adhesive joints utilizing fiber-metal laminates. Demonstrating a commitment to continuous learning, André pursued a postgraduate degree in Industry 4.0 and Digital Transformation from the Instituto Superior de Engenharia do Porto. This advanced training equipped him with contemporary insights into the integration of digital technologies within industrial frameworks. Currently, as a doctoral candidate at the University of Beira Interior, supported by a scholarship from the Foundation for Science and Technology, André is investigating the transformative impacts of digitalization on industrial processes. His diverse educational background reflects a dedication to both theoretical understanding and practical application, positioning him at the forefront of engineering innovation and digital advancement.

Professional Experience

André’s professional trajectory encompasses significant roles in both industry and academia. He dedicated over ten years to the manufacturing sector, notably serving as a Production Manager at IPROM – Indústria de Produtos Metálicos Lda. In this capacity, he honed his skills in production optimization, quality control, and team leadership, directly overseeing manufacturing operations and implementing process improvements. Transitioning to academia, André has been a Guest Lecturer at the Polytechnic Institute of Viseu since 2019, where he imparts knowledge in mechanical engineering and industrial management. His teaching methodology is enriched by his industry experience, providing students with practical perspectives on theoretical concepts. Additionally, André has contributed to various research initiatives, collaborating with institutions such as the University of Beira Interior’s Electromechatronic Systems Research Centre (CISE) and the Research Centre for Digital Services (CISeD) at the Polytechnic Institute of Viseu. His dual engagement in industry and academia underscores a comprehensive understanding of engineering challenges and solutions.

Research Interests

André’s research interests are centered around the integration of advanced technologies within industrial systems. He is particularly focused on Industry 4.0, exploring how digital transformation can enhance manufacturing efficiency and competitiveness. His work delves into the application of lean management principles in conjunction with digital tools to streamline production processes and reduce waste. André is also invested in the study of polymeric materials, investigating their properties and potential applications in modern engineering solutions. Another facet of his research involves asset management, where he examines strategies for optimizing the lifecycle and performance of industrial assets through predictive maintenance and data analytics. By bridging the gap between traditional engineering practices and contemporary technological advancements, André aims to contribute to the development of sustainable and efficient industrial systems.

Research Skills

André possesses a diverse skill set that encompasses both technical and analytical proficiencies. He is adept at conducting comprehensive data analysis, utilizing statistical tools to interpret complex datasets and inform decision-making processes. His expertise in numerical modeling and simulation enables him to predict system behaviors and optimize engineering designs. André is proficient in hydrodynamic modeling, particularly within the context of coastal engineering, allowing for accurate assessments of environmental impacts on engineering projects. His experience in project management is evidenced by his coordination of research initiatives, where he oversees project development, resource allocation, and team collaboration. Additionally, André’s teaching experience has honed his ability to communicate complex concepts effectively, both in written and oral formats, facilitating knowledge transfer and fostering educational growth.

Awards and Honors

Throughout his career, André has been recognized for his academic and professional excellence. He was awarded a doctoral scholarship by the Foundation for Science and Technology, acknowledging his potential to contribute significantly to research in Industrial Engineering and Management. His scholarly work has been featured in reputable journals and conferences, reflecting peer recognition of his contributions to the fields of Industry 4.0, lean management, and polymeric materials. André’s commitment to education and research has also been acknowledged through invitations to present at international conferences, where he has shared his insights on digital transformation and industrial optimization. These accolades underscore his dedication to advancing engineering practices and his impact on both academic and industrial communities.

Conclusion

In summary, André Guimarães exemplifies a professional who seamlessly integrates industry experience with academic prowess. His extensive background in mechanical engineering and industrial management, coupled with a strong focus on digital transformation, positions him as a leader in modern engineering practices. André’s dedication to research is evident through his diverse interests and active participation in projects that bridge the gap between traditional engineering and contemporary technological advancements. His commitment to education, demonstrated by his role as a Guest Lecturer, reflects a passion for fostering the next generation of engineers. As he continues his doctoral research, André is poised to make further significant contributions to the fields of industrial efficiency and digital innovation, driving progress in both academic and practical domains.

Publication Top Notes

  • Development of a Polymer Filament Extruder: Recycling 3D Printer Waste

    • Authors: André Guimarães, Samuel Messias, João Lopes, José Salgueiro, Daniel Gaspar
    • Year: 2025
    • Journal: Kexue Tongbao/Chinese Science Bulletin

  • Effects of Lean Tools and Industry 4.0 Technology on Productivity: An Empirical Study

    • Authors: André Guimarães, Eduardo e Oliveira, Marisa Oliveira, Teresa Pereira
    • Year: 2025
    • Journal: Journal of Industrial Information Integration

  • Implementation of Autonomous Mobile Robots in Intralogistics: Simulations in a Case Study

    • Authors: André Guimarães, A. Silva, J. Teixeira, F. Gomes, S. Martins
    • Year: 2025
    • Journal: Kexue Tongbao/Chinese Science Bulletin

  • The Influence of Consumer, Manager, and Investor Mood and Sentiment on Excess Market Returns

    • Authors: Pedro Nogueira Reis, António Pedro Soares Pinto, André Guimarães
    • Year: 2025
    • Journal: Investment Management and Financial Innovations

  • A Hybrid Strategy for Paint Greenhouse Optimization in Aerospace Manufacturing: Lean Principles and Mathematical Modelling

    • Authors: Maria Teresa Pereira, Marisa Pereira, Fernanda Ferreira, Francisco Silva, André Guimarães
    • Year: 2025
    • Conference: FAIM 25 – The 34th International Conference on Flexible Automation and Intelligent Manufacturing

  • Digital Transformation in Costing for Third-Part Logistics: A Case Study

    • Authors: Maria Teresa Pereira, Nuno Gabriel, Marisa Pereira, Filipe Ramos, André Guimarães
    • Year: 2025
    • Conference: DSMIE – 8th International Conference on Design, Simulation, Manufacturing: The Innovation Exchange

  • Effects of Lean Tools and Industry 4.0 Technology on Productivity: An Empirical Study

    • Authors: André Guimarães, Eduardo e Oliveira, Marisa Oliveira, Teresa Pereira
    • Year: 2025
    • Journal: Journal of Industrial Information Integration
    • DOI: 10.1016/j.jii.2025.100787

  • The Influence of Consumer, Manager, and Investor Sentiment on US Stock Market Returns

    • Authors: Pedro Manuel Nogueira Reis, Antonio Pedro Soares Pinto, André Guimarães
    • Year: 2025
    • Journal: Investment Management and Financial Innovations
    • DOI: 10.21511/imfi.22(1).2025.18

  • A Integração da Transformação Digital na Gestão de Ativos nas Empresas Nacionais

    • Authors: Samuel Messias, André Guimarães, Hugo Raposo, Daniel Gaspar
    • Year: 2024
    • Conference: 11.º ENEGI, Encontro Nacional de Engenharia e Gestão Industrial

  • Asset Management and the Digital Transformation of Companies in Portugal: A Thematic Literature Review

    • Authors: Samuel Messias, André Guimarães, Hugo Raposo, Daniel Gaspar
    • Year: 2024
    • Journal: Journal of Management Science and Engineering

 

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