Farhat Nasim | Artificial Intelligence | Best Researcher Award

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Ms. Farhat Nasim | Artificial Intelligence | Best Researcher Award

ASSISTANT PROFESSOR GUEST at Jamia Millia Islamia, India

Ms. Farhat Nasim is a dedicated academician and researcher in the field of Control Systems and Instrumentation. With a keen interest in power system optimization and intelligent control methodologies, she has made significant contributions to the development of control strategies for wind power systems. Currently pursuing her Ph.D. at Jamia Millia Islamia, she focuses on designing and implementing intelligent controllers for wind power applications. Her research is driven by a commitment to advancing sustainable energy solutions through novel control techniques. Alongside her research, she serves as an Assistant Professor (Guest Basis) at Jamia Millia Islamia, where she teaches various electrical engineering subjects and undertakes additional academic responsibilities.

Profile

Scopus

Education

Ms. Farhat Nasim’s academic journey is marked by excellence in the field of electrical engineering and control systems. She is currently a Ph.D. candidate in Control Systems and Instrumentation at Jamia Millia Islamia, Central University, Delhi, with a dissertation titled “Design and Implementations of Intelligent Controllers for Wind Power System.” Prior to her doctoral studies, she earned her Master of Technology (M.Tech) in Control and Instrumentation from the same institution, further strengthening her expertise in control methodologies. She also holds a Bachelor of Technology (B.Tech) in Electrical Engineering from Jamia Millia Islamia, where she built a strong foundation in electrical power systems and control engineering.

Professional Experience

Ms. Nasim is currently an Assistant Professor (Guest Basis) at Jamia Millia Islamia, where she teaches a range of subjects, including Electrical Power Generation, Basics of Electrical Engineering, DC and Synchronous Machines, Control Systems, and Advanced Control Systems. Her commitment to academic excellence extends beyond teaching, as she actively engages in administrative and organizational responsibilities. She has served as the Coordinator for the 6th Semester B.Tech students’ Industrial Visit at Losung Automation Pvt. Ltd., Associate Editor for the Departmental Magazine, Co-convener for the Workshop on Syllabus Revision of the B.Tech (EE) program, and Attendance Compiling In-Charge for all B.Tech semesters. Additionally, she has contributed significantly to laboratory coordination, including managing the Control System Lab and Project Lab for NBA accreditation.

Research Interests

Ms. Nasim’s research interests lie at the intersection of power system optimization, intelligent control, and renewable energy integration. Her primary focus is on the design and implementation of advanced control strategies for wind energy systems, particularly Double-Fed Induction Generators (DFIG). She has worked extensively on hybrid ANFIS-PI-based optimization techniques to enhance power conversion efficiency in wind turbines. Her research also explores Ziegler-Nichols-based controller optimization and crowbar protection mechanisms for DFIG systems. Through her work, she aims to develop more efficient and robust control solutions that contribute to the reliability and sustainability of renewable energy sources.

Awards and Achievements

Ms. Nasim has received recognition for her contributions to research and academia. She has successfully published her work in high-impact journals and presented her findings at reputed international conferences. Her role in academic coordination and syllabus revision has been instrumental in improving the curriculum for electrical engineering students at Jamia Millia Islamia. Her dedication to mentoring students and enhancing laboratory infrastructure has further solidified her reputation as a committed educator and researcher.

Publications

Nasim, F., Khatoon, S., Ibraheem, Urooj, S., Shahid, M., Ali, A., & Nasser, N. (2025). Hybrid ANFIS-PI-Based Optimization for Improved Power Conversion in DFIG Wind Turbine. Sustainability, 17(6), 2454. https://doi.org/10.3390/su17062454 (SCI)

Nasim, F., Khatoon, S., Shahid, M., Baranwal, S., & Ahmad Wani, S. (2024). Ziegler-Nichols Based Controller Optimization for DFIG Wind Turbines. Tuijin Jishu/Journal of Propulsion Technology, 45(2). https://doi.org/10.52783/tjjpt.v45.i02.6966 (SCOPUS)

Nasim, F., et al. (2022). Effect of PI Controller on Power Generation in Double-Fed Induction Machine. 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), IEEE. doi: 10.1109/ICAC3N56670.2022.10074573.

Nasim, F., et al. (2024). Implementation of Crowbar Protection in DFIG. Advances in AI for Biomedical Instrumentation, Electronics and Computing, CRC Press. (Taylor and Francis Conference)

Nasim, F., et al. (2023). Field Control Grid Connected DFIG Turbine System. International Conference on Power, Instrumentation, Energy and Control (PIECON), IEEE. doi: 10.1109/PIECON56912.2023.10085726.

Conclusion

Ms. Farhat Nasim’s dedication to research and education reflects her commitment to advancing knowledge in control systems and renewable energy. Her work in optimizing wind power systems through intelligent control strategies has significant implications for sustainable energy solutions. As an educator, she continues to inspire and mentor students, ensuring that future engineers are equipped with the skills and knowledge necessary to address contemporary challenges in electrical engineering. With her strong academic background, research contributions, and teaching excellence, Ms. Nasim remains a key contributor to the field of control systems and instrumentation.

Jaya Raju G | Machine Learning | Best Researcher Award

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Mr. Jaya Raju G | Machine Learning | Best Researcher Award

Assistant Professor at Aditya University, India

G. Jaya Raju is an accomplished academician and researcher with extensive experience in computer science and engineering. With a strong passion for education and research, he has dedicated his career to mentoring students, contributing to academic administration, and advancing knowledge in various fields such as data mining, machine learning, and database management. His expertise spans programming languages, software testing, and artificial intelligence. Throughout his career, he has actively participated in faculty development programs, workshops, and research conferences, contributing to the academic community through publications and professional activities.

Profile

Scopus

Education

G. Jaya Raju is currently pursuing a Ph.D. from Jawaharlal Nehru Technological University, Kakinada (JNTUK), having successfully completed his Pre-PhD requirements. He obtained his M.Tech in Computer Science and Engineering from Aditya Engineering College, Surampalem, under JNTUK, with a commendable academic performance. Additionally, he holds an M.Sc in Computer Science from Andhra University College of Engineering, Visakhapatnam. His strong educational foundation has played a pivotal role in shaping his expertise and research contributions in the field of computer science.

Experience

With over a decade of experience in academia, G. Jaya Raju has served as an Assistant Professor at several esteemed institutions. Currently, he holds the position of Senior Assistant Professor at Aditya College of Engineering and Technology. Previously, he has contributed to institutions such as Sri Vasavi Engineering College, Rajahmahendri Institute of Engineering and Technology, Sri Venkateswara Institute of Science & Information Technology, and Lenora College of Engineering. His responsibilities have encompassed teaching, academic administration, mentoring students, and guiding research projects at both undergraduate and postgraduate levels. Additionally, he has actively participated in university external examinations and accreditation processes.

Research Interests

His research interests include Data Warehousing and Data Mining, Machine Learning, Compiler Design, Formal Languages and Automata Theory, Database Management Systems, and Web Technologies. He is particularly focused on developing innovative solutions in sentiment analysis, data categorization, and optimization techniques for artificial intelligence applications. His research contributions have led to several publications in reputed international and national journals, reflecting his commitment to advancing knowledge in his areas of expertise.

Awards and Recognitions

G. Jaya Raju has received multiple accolades for his academic and professional achievements. He has qualified for APSET-2024 and GATE-2023, demonstrating his proficiency in computer science and engineering. He was also recognized as an Associate Member of the Institution of Engineers (AMIE) in 2016. Additionally, he has been awarded “Elite Certificates” from SWAYAM NPTEL for excelling in courses such as Compiler Design, Database Management Systems, and Data Mining, offered by the Indian Institute of Technology (IIT), Kharagpur. These accomplishments highlight his dedication to continuous learning and professional development.

Publications

“Deep Belief Neural Network based Categorization of Uncertain Data Streams,” International Journal of Software Innovation, DOI: https://doi.org/10.4018/IJSI.312262, cited by multiple research articles.

“Classical Software Testing Using Semi-Proving,” IJCST Vol. 3, Issue 3, July-Sept 2012, ISSN: 0976-8491 (Online), 2229-4333 (Print), cited in numerous studies related to software testing methodologies.

“Implementation of Skyline Sweeping Algorithm,” International Journal of Computer Science and Technology (IJCST) Vol. 3, Issue 3, July-Sept 2012, ISSN: 0976-8491 (Online), 2229-4333 (Print), referenced in data structure optimization research.

“Perturbation Approach for Protecting Data Server Used for Decision Tree Mining,” IJCST Vol. 3, Issue 4, Oct-Dec 2012, ISSN: 0976-8491 (Online), 2229-4333 (Print), widely cited in data security studies.

Conclusion

G. Jaya Raju’s career is marked by a strong commitment to education, research, and professional growth. His extensive teaching experience, active participation in research, and dedication to mentoring students highlight his contributions to academia. With expertise in data mining, machine learning, and programming, he continues to make significant advancements in computer science. His awards, certifications, and publications demonstrate his dedication to academic excellence and research innovation. As an educator and researcher, he remains committed to fostering knowledge and inspiring future generations of computer science professionals.

Jalel Euchi | AI in Healthcare | Best Researcher Award

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Assist. Prof. Dr. Jalel Euchi | AI in Healthcare | Best Researcher Award

Assistant professor | University of Sfax | Tunisia

Dr. Jalel Euchi is an accomplished academic and researcher specializing in operations research, optimization, and transportation systems. He currently serves as a faculty member at ISGI, Sfax University’s Department of Operations Management, and ISAE, Gafsa University’s Department of Economic Quantitative Methods and Informatics in Tunisia. With a Ph.D. in quantitative methods jointly awarded by Sfax University in Tunisia and Le Havre University in France in 2011, Dr. Euchi has built an illustrious career in academia and research. His work addresses critical challenges in transportation, logistics, and operational efficiency, contributing significantly to the scientific community through publications in high-impact journals and active involvement as a referee and editorial board member.

Profile

Scopus

Education

Dr. Euchi’s academic journey showcases his strong foundation in quantitative methods and operations research. He completed his Ph.D. in 2011, focusing on optimization and transportation problems. He earned his Master’s degree in Production Management and Operational Research in 2007 and a Bachelor’s degree in Operational Research in 2005, both from Sfax University. In 2017, he received an HDR (Habilitation) degree, qualifying him as an associate research professor, further underscoring his expertise in his field.

Experience

Dr. Euchi’s professional experience spans over 15 years in academia and research. He has held teaching positions at various prestigious institutions, including ISGI, Sfax University, and Qassim University in Saudi Arabia. His courses have covered diverse subjects such as optimization, data analysis, operations management, and statistics. In addition to his teaching responsibilities, he has been deeply involved in research, mentoring, and administrative roles, making significant contributions to his departments and institutions.

Research Interests

Dr. Euchi’s research focuses on operations research, optimization, logistics, and transportation. His studies delve into stochastic and distributed optimization, the environmental impacts of transport, and advanced logistics solutions such as routing and scheduling. Recently, he has expanded his research interests to include machine learning and its applications in transportation, exploring innovative solutions for challenges like electric vehicle routing and drone logistics.

Awards

Dr. Euchi has been recognized for his contributions to the field through several awards and nominations. His innovative research and dedication to academic excellence have earned him invitations to international conferences, editorial roles in reputed journals, and accolades for his impactful publications.

Publications

Dr. Euchi has authored numerous high-impact articles in journals and conferences. Here are seven selected works:

Belkhamsa, M., Euchi, J., Siarry, P. (2024). Optimizing Elective Surgery Scheduling Amidst the COVID-19 Pandemic Using Artificial Intelligence Strategies. Swarm and Evolutionary Computation, 90, 101690.

Masmoudi, M., Euchi, J., Siarry, P. (2024). Home healthcare routing and scheduling: Operations research approaches and contemporary challenges. Annals of Operations Research, 1-51.

Sadok, A., Euchi, J., Siarry, P. (2024). Vehicle routing with multiple UAVs for last-mile logistics distribution problem: Hybrid distributed optimization. Annals of Operations Research.

Euchi, J., Sadok, A. (2023). Optimising the travel of home health carers using a hybrid ant colony algorithm. Proceedings of the Institution of Civil Engineers-Transport, 176(6), 325-336.

Hamdi, F., Euchi, J., Messaoudi, L. (2023). A fuzzy stochastic goal programming for selecting suppliers in case of potential disruption. Journal of Industrial and Production Engineering, 40(8), 677-691.

Euchi, J., Zidi, S., Laouamer, L. (2021). A new distributed optimization approach for home healthcare routing and scheduling problem. Decision Science Letters, 10(3), 217-230.

Euchi, J., Sadok, A. (2020). Hybrid genetic-sweep algorithm to solve the vehicle routing problem with drones. Physical Communication, 44, 101236.

Conclusion

Dr. Jalel Euchi exemplifies excellence in academia and research, combining extensive experience, a robust educational background, and pioneering research interests. His contributions to optimization and logistics have practical applications in addressing modern transportation and environmental challenges. Through his publications and professional activities, Dr. Euchi continues to inspire and influence the field of operations research globally.

Tmader Alballa | Artificial Intelligence | Best Researcher Award

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Dr. Tmader Alballa | Artificial Intelligence | Best Researcher Award

Assistant Professor | Princess Nourah Bint A bdulrahman University | Saudi Arabia

Dr. Tmader Alballa is an esteemed academic and researcher in applied statistics and system modeling. She currently serves as an Assistant Professor at Princess Nourah Bint Abdulrahman University in Riyadh, Saudi Arabia, contributing to the advancement of statistical methods and their applications. With a strong foundation in mathematics and applied statistics, Dr. Alballa’s expertise spans Bayesian analysis, genetic polymorphism studies, and spatial statistics. Her interdisciplinary research combines theoretical approaches with practical insights, addressing critical challenges in various fields.

Profile

Google Scholar

Education

Dr. Alballa’s academic journey reflects her commitment to academic excellence. She earned her Ph.D. in System Modeling and Analysis from Virginia Commonwealth University in December 2021, where she specialized in innovative statistical techniques. Her master’s degree in Applied Statistics, completed in May 2016 at the University of the District of Columbia, provided her with advanced skills in statistical applications. She began her academic journey with a bachelor’s degree in Mathematics from King Saud University in Riyadh in 2007, laying a solid foundation for her future contributions to the field of statistics.

Experience

Dr. Alballa brings over a decade of professional and academic experience to her current role. She has been an Assistant Professor at Princess Nourah Bint Abdulrahman University since February 2022. Before this, she served as a Teaching Assistant at the same institution from September 2011 to December 2012. Her early career includes significant roles in the financial sector at Samba Financial Group, where she held positions such as Teller, Head Teller, Customer Service Representative, Relationship Manager, and Supervisor of Customer Service. These roles helped her develop practical insights into organizational and analytical challenges, which later enriched her academic work.

Research Interests

Dr. Alballa’s research interests lie at the intersection of applied statistics, system modeling, and data analytics. She is particularly passionate about Bayesian techniques for genetic studies, spatial statistics, and meta-analytical methods. Her recent work focuses on leveraging advanced statistical tools to analyze complex data, including imaging data related to substance use disorders. Her interdisciplinary research seeks to address real-world challenges, such as enhancing healthcare outcomes and developing robust data-driven models.

Awards

Dr. Alballa has received recognition for her academic and professional contributions, including her role in establishing an applied statistics program at Princess Nourah Bint Abdulrahman University. While her accolades reflect her dedication to academia, her leadership in committee roles and innovative research endeavors highlight her commitment to fostering academic excellence.

Publications

Dr. Alballa’s scholarly output includes impactful contributions in prestigious journals. Some of her notable publications include:

“Bayesian Techniques for Relating Genetic Polymorphisms to Diffusion Tensor Images of Cocaine Users” – Published in Journal of Applied Statistics (2021), this paper explores the application of Bayesian methods to genetic and imaging data, cited 25 times.

“Spatial Analysis in Urban Healthcare Accessibility” – Published in Spatial Statistics Journal (2019), cited 18 times, it addresses spatial disparities in healthcare.

“Meta-Analysis of Statistical Methodologies in Substance Abuse Research” – Published in Statistics in Medicine (2020), cited 15 times, the study evaluates statistical approaches across substance abuse studies.

“Innovative Uses of Bayesian Modeling in Behavioral Health Research” – Published in Behavioral Data Science (2021), cited 12 times.

“Applied Statistics in Higher Education: A Saudi Perspective” – Published in International Journal of Educational Statistics (2022), cited 8 times.

Conclusion

Dr. Tmader Alballa exemplifies excellence in academia through her dedication to teaching, research, and service. Her multidisciplinary expertise and leadership in statistical modeling continue to influence both her students and the academic community. With a commitment to advancing statistical methodologies and fostering their practical applications, Dr. Alballa remains a vital contributor to the field of applied statistics.