Ahmed Elnashar | Medicine and Dentistry | Best Researcher Award

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Dr. Ahmed Elnashar | Medicine and Dentistry | Best Researcher Award

Mansoura University, Egypt.

Mohamed Mabrouk Ahmed Mohamed Elnashar is a dedicated medical professional specializing in pediatric surgery, with a focus on advancing healthcare for children through both clinical practice and research. He holds a solid academic background in medicine, combined with practical experience, which allows him to integrate theory with hands-on expertise. Mohamed’s commitment to pediatric surgery is evident in his pursuit of a doctorate in the field, aiming to expand his knowledge and contribute to improving surgical practices. His dedication to continuous learning and research makes him a valuable asset in the medical community. Additionally, his skills in digital tools and proficiency in English enable him to engage with global medical research and collaborate effectively with international peers.

Professional Profile

Education

Mohamed completed his Bachelor’s degree in Medicine from Mansoura University, Egypt, with an impressive academic record, achieving an 85.29% score. Building on this foundation, he pursued a Master’s degree in Surgery, also from Mansoura University, where he gained a deeper understanding of surgical procedures and techniques. Currently, Mohamed is working toward his Doctorate in Pediatric Surgery, aiming to further his specialization and expertise in this critical area of medicine. His ongoing academic journey underscores his passion for learning and commitment to becoming a leader in pediatric surgical research, preparing him to contribute to advancements in this specialized field.

Professional Experience

Mohamed has extensive clinical experience, particularly in the field of pediatric surgery. He completed a three-year residency at the Children’s Hospital in Mansoura University, where he honed his skills in performing complex pediatric surgeries and managing a wide range of surgical cases. This residency allowed him to gain hands-on experience in a high-pressure medical environment, providing critical care to young patients. His professional journey has been characterized by a dedication to improving patient outcomes through meticulous surgical techniques and a deep understanding of pediatric care. This experience has not only equipped him with practical skills but also reinforced his commitment to the well-being of children through advanced medical care.

Research Interest

Mohamed’s research interests are deeply rooted in advancing pediatric surgery through evidence-based practices and innovative techniques. He is particularly interested in exploring new surgical methods that can improve recovery times and outcomes for pediatric patients. Additionally, his ongoing doctoral studies have sparked a passion for contributing to clinical research, aiming to address critical challenges in pediatric surgery. Mohamed is keen to explore topics such as minimally invasive surgical techniques, postoperative care optimization, and the development of pediatric surgical guidelines. His research efforts are focused on bridging the gap between clinical practice and research, ensuring that the latest findings in pediatric surgery translate into improved patient care.

Research Skills

Mohamed possesses a strong set of research skills, particularly in clinical data analysis and surgical research methodologies. His training includes the ability to design and conduct studies that explore new surgical techniques and patient care protocols. He is skilled in using digital tools, as evidenced by his ICDL (International Computer Driving License) certification, which aids in data management and analysis. Mohamed’s proficiency in English, demonstrated by his TOEFL ITP qualification, allows him to engage with international research literature and collaborate effectively with researchers worldwide. His analytical mindset and commitment to thorough research methodologies make him capable of contributing valuable insights to the field of pediatric surgery.

Awards and Honors

Throughout his academic and professional journey, Mohamed has earned recognition for his dedication and achievements. His high academic performance during his undergraduate studies, where he graduated with an 85.29% score, is a testament to his commitment to excellence. Although much of his career has focused on clinical practice, his ongoing doctoral studies have positioned him as a promising researcher in the field of pediatric surgery. As he continues to advance in his research, Mohamed is poised to receive further accolades for his contributions to surgical innovation and child health. His pursuit of excellence and passion for improving patient outcomes make him a strong candidate for future awards in medical research.

Conclusion

Mohamed Mabrouk Ahmed Mohamed Elnashar possesses a robust medical and surgical foundation, with a notable specialization in pediatric surgery. His pursuit of a doctorate underscores his potential for future contributions to the field. To further strengthen his candidacy for a Best Researcher Award, it would be beneficial for him to focus on expanding his research output, actively engage in scientific publications, and seek opportunities for collaborative research. With these enhancements, Mohamed is well-positioned to excel in the field of medical research and make significant contributions to pediatric surgery.

Publication Top Noted

  • Comparative Study between Autologous Platelet-Rich Fibrin Membrane and Local Flaps as Intervening Layer in Management of Distal Hypospadias
    Authors: Ahmed M. Elnashar, Mohamed Albishbishy, Hesham Sheir, Moustafa Elayyouti, Mohamed Elsherbiny, Mohamed Elzohiri, Mohamed El-Ghazaly, Adham Elsaied
    Year: 2024

 

Ali Motie Nasrabadi | Biomedical Engineering | Best Researcher Award

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Prof. Ali Motie Nasrabadi | Biomedical Engineering | Best Researcher Award

Professor at Shahed University, Iran

Prof. Ali Motie Nasrabadi is a renowned academic and researcher in the field of Biomedical Engineering, specializing in the intelligent processing of EEG signals, computational neuroscience, and artificial intelligence in healthcare applications. He earned his Ph.D. in Biomedical Engineering from Amirkabir University of Technology in 2004, where his research focused on evaluating consciousness and hypnosis depth through EEG signal analysis. With a career spanning decades, Prof. Nasrabadi has contributed extensively to EEG/ERP signal processing, nonlinear and chaotic systems, and physiological modeling. He has published over 100 peer-reviewed papers and continues to influence the fields of biomedical signal processing and neuroscience.

Profile

Education

Prof. Ali Motie Nasrabadi has a distinguished academic background in Biomedical Engineering, with his education centered at the Amirkabir University of Technology in Tehran, Iran. He earned his Ph.D. in Biomedical Engineering in March 2004, with a dissertation titled “Quantitative and Qualitative Evaluation of Consciousness Variation and Depth of Hypnosis through Intelligent Processing of EEG Signals.” His doctoral research focused on advanced signal processing techniques applied to biomedical data. Prior to that, he completed his M.Sc. in Biomedical Engineering in September 1998, where he specialized in the “Design and Implementation of an 8-channel PC-Based Electroencephalograph.” This work demonstrated his early interest in biomedical instrumentation and signal analysis. Prof. Nasrabadi began his academic journey with a B.Sc. in Electronic Engineering in February 1994, focusing on the “Design and Implementation of Control of Satellite Dish to Get Better Signal.” His strong foundation in electronic engineering and biomedical systems has been integral to his success in applying engineering principles to healthcare challenges.

Professional Experience

Prof. Ali Motie Nasrabadi has had a distinguished career across both academic and industrial sectors. He has served as the Vice Chancellor for Support and Resource Management at Shahed University from 2017 to 2021, where he played a pivotal role in overseeing resource management. Prior to this, he was the Director General of Equipment at Shahed University, a position he held from 2004 to 2021. His expertise in biomedical signal processing has led to consultancy roles, including being an EEG Signal Processing Consultant at the National Brain Mapping Laboratory (NBML) since 2016. In this capacity, he has also designed and organized brain signal processing workshops at NBML. Prof. Nasrabadi has been actively involved in industrial and technology consulting as well. Since 2014, he has been a Technology and E-commerce Consultant at Shenasa Venture Capital and Trigup Accelerator. Earlier in his career, he worked as a researcher at the Research Center for Intelligent Signal Processing (RCISP) from 2001 to 2006 and the Laser and Optical Group at the Research Center for Science and Technology in Medicine (RCSTIM) from 1998 to 2004. His wide-ranging experience reflects his strong influence in both academia and industry, particularly in the fields of biomedical engineering and signal processing.

Research Interest

Prof. Ali Motie Nasrabadi’s research interests are deeply rooted in the intersection of biomedical engineering and signal processing. His primary focus is on artificial intelligence in healthcare applications, where he explores the potential of AI to enhance medical diagnostics and treatments. He is also heavily involved in computational neuroscience, studying the brain’s complex systems through computational models. Prof. Nasrabadi specializes in chaotic and nonlinear signal processing, applying advanced techniques to understand irregular biological signals. A significant portion of his research is dedicated to the recording and processing of EEG/ERP/LFP/ECoG signals, where he analyzes brain activity patterns for medical and cognitive insights. Additionally, he is interested in the modeling of physiological systems, where he creates mathematical representations of biological processes to better understand and predict their behavior. This broad array of research areas positions Prof. Nasrabadi as a leading figure in applying advanced computational methods to solve complex challenges in healthcare and neuroscience.

Research Skills

Prof. Ali Motie Nasrabadi possesses a diverse set of skills that span across various domains of biomedical engineering and computational analysis. He is an expert in MATLAB and C programming, which he uses for designing and implementing algorithms for signal processing and neural network modeling. His proficiency with EEGLAB and SPM software makes him adept at processing and analyzing EEG and brain signals, essential for neuroscience research. Additionally, Prof. Nasrabadi is skilled in SPSS, which he uses for statistical data analysis, allowing him to interpret complex biomedical data. His deep understanding of chaos theory and nonlinear dynamics further complements his expertise, enabling him to analyze and quantify irregular physiological signals. These technical and computational skills are integral to his contributions in fields such as artificial intelligence, signal processing, and healthcare.

Award and Recognition

Prof. Ali Motie Nasrabadi has received several awards and recognitions throughout his distinguished academic and research career. He achieved First Rank in his B.Sc. program from the Department of Electrical Engineering at Amirkabir University of Technology, with an impressive average score of 18.16 out of 20. Similarly, he was awarded First Rank in his M.Sc. program from the Department of Biomedical Engineering at Amirkabir University of Technology, with an outstanding average score of 18.63 out of 20. His significant contributions to the field of biomedical engineering, particularly in signal processing and artificial intelligence applications, are reflected in his high H-index of 31 in Google Scholar and H-index of 23 in Scopus, underscoring the impact of his research in the global scientific community.

Conclusion

Considering Prof. Ali Motie Nasrabadi’s extensive academic achievements, innovative research in biomedical signal processing, significant publication record, industry-related activities, and leadership roles, he is highly suitable for the Research for Best Researcher Award. His work has had a profound impact on the field of biomedical engineering, particularly in the analysis and processing of EEG signals, making him a deserving candidate for this prestigious recognition.

Publications Top Notes

  • Title: EEG Classification of ADHD and Normal Children Using Non-linear Features and Neural Network
    • Citations: 220
    • Year: 2016
  • Title: Detecting Driver Mental Fatigue Based on EEG Alpha Power Changes During Simulated Driving
    • Citations: 153
    • Year: 2015
  • Title: A New Automatic Sleep Staging System Based on Statistical Behavior of Local Extrema Using Single Channel EEG Signal
    • Citations: 110
    • Year: 2018
  • Title: Determining Fault’s Type and Accurate Location in Distribution Systems with DG Using MLP Neural Networks
    • Citations: 105
    • Year: 2009
  • Title: A Review on EEG Signals Based Emotion Recognition
    • Citations: 103*
    • Year: 2018
  • Title: The Emotion Recognition System Based on Autoregressive Model and Sequential Forward Feature Selection of Electroencephalogram Signals
    • Citations: 83
    • Year: 2014
  • Title: EEG-based Mental Task Classification: Linear and Nonlinear Classification of Movement Imagery
    • Citations: 69
    • Year: 2006
  • Title: Emotion Classification Through Nonlinear EEG Analysis Using Machine Learning Methods
    • Citations: 68
    • Year: 2018