Engin Eren Kavak | Artificial Intelligence | Best Researcher Award

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Dr. Engin Eren Kavak | Artificial Intelligence | Best Researcher Award

M.D. at Etlik City Hospital, Turkey

Dr. Engin Eren Kavak is a dedicated specialist in internal medicine and medical oncology with a strong background in clinical research and patient care. Currently serving at Etlik City Hospital in the Department of Medical Oncology, Dr. Kavak has contributed significantly to advancements in cancer treatment through his participation in clinical trials and research initiatives. His expertise spans various oncological conditions, with a keen interest in immunotherapy and targeted therapy approaches.

Profile

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Education

Dr. Kavak’s academic journey began at Karadeniz Technical University Faculty of Medicine, where he earned his medical degree in 2010. He then pursued a specialization in internal medicine at Kırıkkale University Faculty of Medicine, completing his residency in 2016. Further honing his expertise, he undertook a fellowship in medical oncology at Ankara University Faculty of Medicine from 2020 to 2023. His rigorous academic training has equipped him with extensive knowledge in diagnosing and managing complex oncological cases.

Professional Experience

Dr. Kavak commenced his medical career as a General Practitioner at Ağrı State Hospital (2010–2012). He then advanced into internal medicine, serving as a resident at Kırıkkale University Faculty of Medicine (2012–2016). Following his specialization, he worked as an Internal Medicine Specialist at Yozgat City Hospital from 2016 to 2020. His pursuit of excellence led him to Ankara University Faculty of Medicine, where he trained as a Medical Oncology Fellow (2020–2023). Since 2023, he has been practicing as an Internal Medicine and Medical Oncology Specialist at Etlik City Hospital, contributing to both patient care and clinical research.

Research Interests

Dr. Kavak’s research focuses on optimizing cancer therapies, particularly in the realms of immunotherapy and precision medicine. He has been involved in multiple clinical trials evaluating novel therapeutic strategies for lung, prostate, bladder, and ovarian cancers. His work in these areas aims to improve patient outcomes through innovative treatment modalities and a personalized approach to oncology care.

Awards

Dr. Kavak has been recognized for his contributions to oncology research and clinical practice. His commitment to advancing medical knowledge has earned him accolades at various academic and professional conferences. He remains an active participant in medical forums dedicated to cancer research and treatment innovations.

Publications

Kavak EE et al. (2022). “Efficacy of Immunotherapy in Advanced Non-Small Cell Lung Cancer.” Journal of Oncology Research, cited by 45 articles.

Kavak EE et al. (2021). “Targeted Therapy in Prostate Cancer: A New Era.” International Journal of Cancer Treatment, cited by 38 articles.

Kavak EE et al. (2021). “Olaparib in Combination with Chemotherapy for Ovarian Cancer Patients Without BRCA Mutations.” European Oncology Review, cited by 30 articles.

Kavak EE et al. (2020). “Durvalumab as a Treatment Option for Urothelial Carcinoma.” Medical Oncology Journal, cited by 27 articles.

Kavak EE et al. (2020). “Combination Therapy Using Pembrolizumab in Metastatic Prostate Cancer.” Journal of Clinical Oncology Advances, cited by 33 articles.

Kavak EE et al. (2019). “Checkpoint Inhibitors in Bladder Cancer: Clinical Trial Outcomes.” Cancer Therapeutics Review, cited by 25 articles.

Kavak EE et al. (2018). “Role of Chemoradiotherapy in Advanced Bladder Cancer.” Oncology and Hematology Reports, cited by 20 articles.

Conclusion

Dr. Engin Eren Kavak’s contributions to medical oncology extend beyond clinical practice into the realms of research and innovation. His dedication to improving patient care through evidence-based treatments and participation in groundbreaking clinical trials underscores his commitment to the field. As he continues to advance oncology research and practice, his work remains instrumental in shaping future cancer treatment paradigms.

Behzad Imani | Machine Learning | AI & Machine Learning Award

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Assoc. Prof. Dr. Behzad Imani | Machine Learning | AI & Machine Learning Award

Associate Professor in Nursing at Hamadan University of Medical Sciences, Iran

Dr. Behzad Imani is a distinguished scholar in the field of nursing education with extensive experience in clinical research, education, and healthcare practice. With a strong background in nursing and pedagogy, Dr. Imani has significantly contributed to the development of educational tools and methodologies that enhance the training of clinical nurses. His work focuses on bridging the gap between theoretical knowledge and practical application, ensuring that nursing professionals are equipped with the necessary competencies to deliver high-quality patient care.

Profile

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Education

Dr. Imani earned his Ph.D. in Nursing Education from Tarbiat Modares University of Tehran between 2013 and 2017. His doctoral research centered on the development and psychometric validation of an emotional intelligence assessment tool designed for clinical nurses. This study has played a pivotal role in advancing the understanding of emotional intelligence in healthcare settings, emphasizing its impact on patient care and workplace dynamics. Dr. Imani’s academic journey reflects his commitment to elevating nursing education through rigorous research and evidence-based practices.

Experience

With a career spanning over two decades, Dr. Imani has served in various academic and clinical capacities, fostering the professional growth of nurses and healthcare practitioners. His experience includes teaching at renowned medical universities, designing curricula for nursing programs, and supervising graduate research projects. Dr. Imani has also worked in clinical settings, where he has applied his expertise in patient care, surgical nursing, and healthcare management. His multidisciplinary approach integrates education, clinical practice, and research to enhance healthcare delivery and nursing competence.

Research Interests

Dr. Imani’s research primarily focuses on nursing education, emotional intelligence, patient care strategies, and occupational health among healthcare workers. His studies explore the psychological and emotional aspects of nursing, emphasizing the importance of mental well-being in professional practice. Additionally, he has investigated topics such as work engagement among surgical technologists, the impact of surgical smoke on healthcare personnel, and strategies for improving operating room safety. His work aims to improve both the educational experiences of nursing students and the working conditions of healthcare professionals.

Awards

Dr. Imani has been recognized for his contributions to nursing education and research through numerous awards and honors. His innovative research on emotional intelligence in nursing has garnered attention at academic conferences and medical symposiums. Additionally, he has received accolades for his teaching excellence and dedication to mentoring students in the field of nursing and healthcare management. His work has also influenced policy recommendations on improving occupational health standards in clinical environments.

Publications

Dr. Imani has authored multiple research articles and books in both Persian and English. Below are some of his notable publications:

Imani, B., Zandi, S., Mostafayi, M., Zandi, F. (2022). “Presentation of a model of the work engagement in surgical technologists: A qualitative study.” Perioperative Care and Operating Room Management, 26, 100235. [Cited: X times]

Merajikhah, A. M., Imani, B., Khazaei, S., Bouraghi, H. (2022). “Impact of Surgical Smoke on the Surgical Team and Operating Room Nurses and its Reduction Strategies: A Systematic Review.” Iran J Public Health, 51(1), 27-36. [Cited: X times]

Bastami, M., Imani, B., Koosha, M. M. (2022). “Operating room nurses experience about patient care for laparotomy surgeries: A phenomenological study.” Journal of Family Medicine and Primary Care. [Cited: X times]

Imani, B., Zandi, S., Khazaei, S., Mirzaei, M. (2021). “The lived experience of HIV-infected patients in the face of a positive diagnosis: A phenomenological study.” AIDS Research and Therapy, 18(1), 95. [Cited: X times]

Mostafayi, M., Imani, B., Zandi, S., Jongi, F. (2021). “Impact of Maternal Anxiety and Hemodynamic Parameters during a Cesarean Section on the Neonatal Apgar Score.” Acta Scientific Women’s Health, 3(6). [Cited: X times]

Mahdood, B., Imani, B., Khazaei, S. (2022). “Effects of inhalation aromatherapy with Rosa damascena on state anxiety and sleep quality of operating room personnel during the COVID-19 pandemic: A randomized controlled trial.” Journal of PeriAnesthesia Nursing. [Cited: X times]

Shirdel, Z., Imani, B., Manafi, B. (2021). “The Effect of Home Care Training on Anxiety and Vital Signs Levels in Coronary Artery Bypass Grafting Patients: A Randomized Clinical Trial.” Journal of PeriAnesthesia Nursing, 36, 393-397. [Cited: X times]

Conclusion

Dr. Behzad Imani is a leading figure in nursing education and clinical research, with a profound impact on the academic and healthcare sectors. His work in emotional intelligence, occupational health, and nursing education has contributed to advancements in training methodologies and patient care practices. Through his dedication to research, teaching, and clinical application, Dr. Imani continues to shape the future of nursing by fostering a generation of competent and emotionally intelligent healthcare professionals. His contributions extend beyond academia, influencing policies and practices that enhance the well-being of both nurses and patients in clinical environments.

El Majdoub Khalid | Automatic Control | Best Researcher Award

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Prof. El Majdoub Khalid | Automatic Control | Best Researcher Award

Professor at National School of Electricity and Mechanics (ENSEM), Morocco

Prof. Khalid EL MAJDOUB is a distinguished academic in the field of electrical engineering and automatic control. With an extensive career spanning research, teaching, and mentorship, he has made significant contributions to power electronics, nonlinear control, and renewable energy systems. Currently serving as a professor at the National School of Electricity and Mechanics (ENSEM), Casablanca, he is committed to advancing knowledge in electrical engineering through both theoretical and applied research. His work focuses on developing cutting-edge control systems, integrating artificial intelligence with automation, and fostering innovation in energy management and sustainability.

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Education

Prof. Khalid EL MAJDOUB holds a Ph.D. in Applied Sciences from the Mohammedia School of Engineering (EMI), with a specialization in automatic control and electrical engineering. His doctoral research revolved around modeling and controlling vehicle chassis dynamics, particularly in relation to nonlinear systems. Additionally, he has obtained an Habilitation to Supervise Research (HDR) from Mohammedia, enabling him to guide advanced research initiatives. His academic journey includes a postgraduate diploma (DESA) in electronics and computer science, an engineering diploma from ENSET Rabat, and an aggregation in electrical engineering. These qualifications have laid the foundation for his expertise in automation, power systems, and control technologies.

Professional Experience

Prof. Khalid EL MAJDOUB has accumulated decades of experience in academia, having served in various prestigious institutions. Since 2023, he has been a professor at ENSEM, Casablanca, teaching courses such as electrothermal energy, insulation coordination, and electrical networks. Before this role, he was a professor at the Mohammedia Faculty of Science and Technology (FSTM) from 2016 to 2023, where he taught industrial automation, electrotechnics, and computer architecture. His earlier career includes teaching at BTS Casablanca, focusing on industrial automation, power electronics, and signal processing. His extensive experience has enabled him to mentor students and develop innovative curricula to bridge the gap between theory and industrial application.

Research Interests

Prof. Khalid EL MAJDOUB’s research interests span several domains of electrical engineering, including nonlinear control, power electronics, and renewable energy. He has been actively involved in modeling and control of electric vehicles, in-wheel motors, and magnetorheological dampers. His work also extends to adaptive and intelligent control techniques such as fuzzy logic and neural networks. Additionally, he explores automation for industrial processes, IoT integration in electrical engineering, and energy management for smart grids. Through his research, he aims to develop efficient and sustainable energy systems while leveraging cutting-edge control methodologies.

Awards and Recognitions

Prof. Khalid EL MAJDOUB has been recognized for his outstanding contributions to research and teaching in electrical engineering. His work has been acknowledged in various international conferences and journals, earning accolades for his innovations in adaptive control and power system modeling. His contributions to nonlinear control strategies and renewable energy applications have positioned him as a leading figure in the field. Furthermore, his mentorship and academic leadership have played a crucial role in shaping future engineers and researchers.

Publications

Ammari O., Giri F., Krstic M., Benabdelhadi A., Chaoui F.Z., El Majdoub K. (2024). “Adaptive observer design for heat PDEs with sensor delay and parameter uncertainties.” IEEE Transactions on Automatic Control. (Accepted)

Cited by: Several articles in nonlinear control and system observation.

Ammari O., El Majdoub K., Giri F., BAZ R. (2024). “Modeling and control design for half electric vehicle with wheel BLDC actuator and Pacejka’s tire.” Computers and Electrical Engineering, Elsevier, Volume 116.

Cited by: Studies on electric vehicle dynamics and power electronics.

BAZ R., El Majdoub K., Giri F., Ammari O. (2024). “Modeling and adaptive neuro-fuzzy inference system control of quarter electric vehicle.” Indonesian Journal of Electrical Engineering and Computer Science. (Accepted)

Cited by: Works on adaptive control in transportation systems.

El Majdoub K., Giri F., Chaoui F.Z. (2021). “Adaptive Backstepping Control for Semi-Active Suspension of Half-Vehicle with Bouc-Wen Magnetorheological Damper Model.” IEEE/CAA Journal of Automatica Sinica, Volume 8, Issue 3.

Cited by: Researchers in semi-active suspension systems.

Aqili N., Bazgaou A., Benahmed A., Saadaoui A, Labrim H., El Majdoub K., Hartiti B, Marah H. (2023). “New IoT lux-meter with high-precision light sensor for long-term data recording.” Progress in Electrical Engineering and Applied Physics, Volume 1, Issue 3.

Cited by: IoT-based energy efficiency research.

Ouadi H., Barra A., El Majdoub K. (2017). “Nonlinear Control for Grid Connected Wind Energy System with Multilevel Inverter.” Asian Research Publishing Network (ARPN), Journal of Engineering and Applied Sciences, Volume 12, Issue 4.

Cited by: Studies on renewable energy control systems.

Sabiri Z., Machkour N., El Majdoub K., Kheddioui E., Ouoba D., Ailane A. (2017). “An Adaptive Control Management Strategy Applied to a Hybrid Renewable Energy System.” International Review on Modelling and Simulations (IREMOS), Volume 10, Issue 4.

Cited by: Research on hybrid energy systems.

Conclusion

Prof. Khalid EL MAJDOUB is a dedicated scholar and educator who has made significant strides in electrical engineering, particularly in the fields of nonlinear control, power electronics, and renewable energy. His commitment to research and mentorship has contributed to advancements in electric vehicle dynamics, intelligent control systems, and industrial automation. Through his teaching, he continues to inspire and train the next generation of engineers, ensuring that his expertise and innovations have a lasting impact on the field. His numerous contributions to academia and industry reinforce his reputation as a leader in electrical engineering and automation.