Ali Motie Nasrabadi | Biomedical Engineering | Best Researcher Award Posted on 11/09/202411/09/2024 by ScienceFather 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 Google Scholar 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
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 Google Scholar 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
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
Yasamin Haririan | Biomedical Engineering | Best Researcher Award Posted on 11/09/202413/09/2024 by ScienceFather Ms. Yasamin Haririan | Biomedical Engineering | Best Researcher Award Research Assistant at Science and Research branch of Azad University, Iran Yasamin Haririan is a distinguished researcher with a Master’s degree in Medical Engineering (Biomaterials) from Science and Research University and a Bachelor’s in Textile Science Engineering from Amirkabir University of Technology. She has made significant contributions to the field through her patent on advanced wound dressings and multiple research papers in prominent journals. Her research focuses on stem cell engineering, peptide hydrogels, and wound healing technologies. Yasamin’s experience spans roles as a Research Assistant, Teaching Assistant, and Project Assistant, showcasing her hands-on skills and instructional capabilities. Her awards include grants from the Iran Nanotechnology Innovation Council and accolades for her master’s thesis. With a strong foundation in both technical and soft skills, Yasamin demonstrates a solid commitment to her field. To further enhance her profile, increasing her international research impact and improving her English proficiency could be beneficial. Profile Scopus Profile Education Yasamin Haririan has a robust educational background in the field of biomaterials and textile science. She completed her M.Sc. in Medical Engineering (Biomaterials) at Science and Research University in Tehran, Iran, from September 2020 to September 2022, graduating with distinction and an impressive GPA of 3.7/4. Her academic performance was further highlighted by a degree classification of 1st. Prior to this, Yasamin earned her B.Sc. in Textile Science Engineering (Textile Technology) from Amirkabir University of Technology (AUT) in Tehran, where she studied from September 2015 to May 2020. Her undergraduate studies included a significant improvement in her last two semesters, achieving a GPA of 3.15/4, reflecting her growing expertise and dedication to her field. This strong academic foundation provided her with the skills and knowledge essential for her research and professional endeavors. Professional Experience Yasamin Haririan has demonstrated substantial expertise through her diverse professional experiences. As a Research Assistant since January 2022, she has focused on fabricating electro-spun chitosan-based wound dressings and conducting in vivo tests. She also served as an Instructor in April 2024, teaching Academic Photoshop to graduate and Ph.D. students at Tarbiat Modares University. Her role as an Author Assistant and Editor from February 2021 to April 2023 involved translating and editing scientific content for a book on polyurethanes in medicine. Additionally, Yasamin worked as a Teaching Assistant, managing class projects and homework related to controlled drug release systems and hydrogels. Her project assistantship in May-July 2022 included coordinating a startup on novel skin substitute scaffolds. Furthermore, her internship as a Medical Engineer in 2021 provided hands-on experience in monitoring and maintaining medical devices. Research Interest Yasamin Haririan’s research interests primarily focus on advancing biomaterials and regenerative medicine. Her work in stem cell engineering, particularly with mesenchymal stem cells, aims to explore their potential for tissue repair and regeneration. Yasamin is deeply involved in developing peptide hydrogels for bone regeneration, which involves designing and optimizing these materials to enhance their effectiveness in supporting bone growth. Additionally, her research encompasses surface modification techniques and hybrid microparticle/gel systems, which are crucial for improving the performance and functionality of biomaterials. By investigating these areas, Yasamin seeks to contribute to the creation of innovative solutions for wound healing and tissue engineering. Her interdisciplinary approach combines expertise in biomaterials, nanotechnology, and regenerative medicine, reflecting a commitment to addressing complex challenges in these fields and advancing the understanding and application of cutting-edge biomedical technologies. Research Skills Yasamin Haririan demonstrates exceptional research skills across multiple areas of biomaterials and medical engineering. Her technical expertise encompasses the preparation and characterization of hydrogels and polymeric scaffolds, advanced cell culture techniques, and comprehensive analysis using methods such as MTT assays, UV-vis spectroscopy, FTIR, and SEM. Yasamin is proficient in designing and fabricating electro-spun wound dressings and bio-composite materials, with a particular focus on integrating natural extracts for enhanced wound healing. Her research contributions are underscored by her work on carboxymethyl chitosan-gelatin-mesoporous silica nanoparticles and the development of novel wound dressings. Yasamin’s skills extend to software proficiency, including Microsoft Office, Adobe Photoshop, and statistical tools like SPSS and GraphPad Prism. Additionally, her ability to manage and implement research projects, combined with effective communication and teamwork, underscores her comprehensive approach to research and development in her field. Award and Recognition Yasamin Haririan has garnered notable awards and recognition for her outstanding contributions to the field of biomaterials and medical engineering. She was honored with the “Prominent Published Research Paper” grant from the Iran Nanotechnology Innovation Council in May 2024, acknowledging her impactful research. Yasamin also received the “Top Master’s Thesis” prize during Research Week at Science and Research University in December 2023, celebrating her exceptional master’s thesis work. Additionally, she was awarded the “Prominent Defended Master’s Thesis” grant from the Iran Nanotechnology Innovation Council in October 2023, further recognizing her innovative research. Yasamin’s achievements include being selected as a top Ph.D. candidate in the national entrance exam of Iran for Biomaterials at the Material and Energy Research Center in August 2023. These accolades reflect her significant contributions and dedication to advancing research in her field. Conclusion Yasamin Haririan is a highly promising candidate for the “Best Researcher Award.” Her strong academic performance, impressive research contributions, relevant expertise, and recognition through awards highlight her as a dedicated and impactful researcher. Addressing the areas for improvement, such as increasing her research impact and enhancing language proficiency, could further strengthen her candidacy and elevate her profile in the global research community. Overall, Yasamin’s qualifications and achievements make her a compelling candidate for this prestigious award. Publications Top Notes Carboxymethyl Chitosan-Gelatin-Mesoporous Silica Nanoparticles Containing Myrtus communis L. Extract as a Novel Transparent Film Wound Dressing Authors: Y. Haririan, A. Asefnejad, H. Hamishehkar, M.R. Farahpour Journal: International Journal of Biological Macromolecules Year: 2023 Volume: 253 Article Number: 127081
Yasamin Haririan is a distinguished researcher with a Master’s degree in Medical Engineering (Biomaterials) from Science and Research University and a Bachelor’s in Textile Science Engineering from Amirkabir University of Technology. She has made significant contributions to the field through her patent on advanced wound dressings and multiple research papers in prominent journals. Her research focuses on stem cell engineering, peptide hydrogels, and wound healing technologies. Yasamin’s experience spans roles as a Research Assistant, Teaching Assistant, and Project Assistant, showcasing her hands-on skills and instructional capabilities. Her awards include grants from the Iran Nanotechnology Innovation Council and accolades for her master’s thesis. With a strong foundation in both technical and soft skills, Yasamin demonstrates a solid commitment to her field. To further enhance her profile, increasing her international research impact and improving her English proficiency could be beneficial. Profile Scopus Profile Education Yasamin Haririan has a robust educational background in the field of biomaterials and textile science. She completed her M.Sc. in Medical Engineering (Biomaterials) at Science and Research University in Tehran, Iran, from September 2020 to September 2022, graduating with distinction and an impressive GPA of 3.7/4. Her academic performance was further highlighted by a degree classification of 1st. Prior to this, Yasamin earned her B.Sc. in Textile Science Engineering (Textile Technology) from Amirkabir University of Technology (AUT) in Tehran, where she studied from September 2015 to May 2020. Her undergraduate studies included a significant improvement in her last two semesters, achieving a GPA of 3.15/4, reflecting her growing expertise and dedication to her field. This strong academic foundation provided her with the skills and knowledge essential for her research and professional endeavors. Professional Experience Yasamin Haririan has demonstrated substantial expertise through her diverse professional experiences. As a Research Assistant since January 2022, she has focused on fabricating electro-spun chitosan-based wound dressings and conducting in vivo tests. She also served as an Instructor in April 2024, teaching Academic Photoshop to graduate and Ph.D. students at Tarbiat Modares University. Her role as an Author Assistant and Editor from February 2021 to April 2023 involved translating and editing scientific content for a book on polyurethanes in medicine. Additionally, Yasamin worked as a Teaching Assistant, managing class projects and homework related to controlled drug release systems and hydrogels. Her project assistantship in May-July 2022 included coordinating a startup on novel skin substitute scaffolds. Furthermore, her internship as a Medical Engineer in 2021 provided hands-on experience in monitoring and maintaining medical devices. Research Interest Yasamin Haririan’s research interests primarily focus on advancing biomaterials and regenerative medicine. Her work in stem cell engineering, particularly with mesenchymal stem cells, aims to explore their potential for tissue repair and regeneration. Yasamin is deeply involved in developing peptide hydrogels for bone regeneration, which involves designing and optimizing these materials to enhance their effectiveness in supporting bone growth. Additionally, her research encompasses surface modification techniques and hybrid microparticle/gel systems, which are crucial for improving the performance and functionality of biomaterials. By investigating these areas, Yasamin seeks to contribute to the creation of innovative solutions for wound healing and tissue engineering. Her interdisciplinary approach combines expertise in biomaterials, nanotechnology, and regenerative medicine, reflecting a commitment to addressing complex challenges in these fields and advancing the understanding and application of cutting-edge biomedical technologies. Research Skills Yasamin Haririan demonstrates exceptional research skills across multiple areas of biomaterials and medical engineering. Her technical expertise encompasses the preparation and characterization of hydrogels and polymeric scaffolds, advanced cell culture techniques, and comprehensive analysis using methods such as MTT assays, UV-vis spectroscopy, FTIR, and SEM. Yasamin is proficient in designing and fabricating electro-spun wound dressings and bio-composite materials, with a particular focus on integrating natural extracts for enhanced wound healing. Her research contributions are underscored by her work on carboxymethyl chitosan-gelatin-mesoporous silica nanoparticles and the development of novel wound dressings. Yasamin’s skills extend to software proficiency, including Microsoft Office, Adobe Photoshop, and statistical tools like SPSS and GraphPad Prism. Additionally, her ability to manage and implement research projects, combined with effective communication and teamwork, underscores her comprehensive approach to research and development in her field. Award and Recognition Yasamin Haririan has garnered notable awards and recognition for her outstanding contributions to the field of biomaterials and medical engineering. She was honored with the “Prominent Published Research Paper” grant from the Iran Nanotechnology Innovation Council in May 2024, acknowledging her impactful research. Yasamin also received the “Top Master’s Thesis” prize during Research Week at Science and Research University in December 2023, celebrating her exceptional master’s thesis work. Additionally, she was awarded the “Prominent Defended Master’s Thesis” grant from the Iran Nanotechnology Innovation Council in October 2023, further recognizing her innovative research. Yasamin’s achievements include being selected as a top Ph.D. candidate in the national entrance exam of Iran for Biomaterials at the Material and Energy Research Center in August 2023. These accolades reflect her significant contributions and dedication to advancing research in her field. Conclusion Yasamin Haririan is a highly promising candidate for the “Best Researcher Award.” Her strong academic performance, impressive research contributions, relevant expertise, and recognition through awards highlight her as a dedicated and impactful researcher. Addressing the areas for improvement, such as increasing her research impact and enhancing language proficiency, could further strengthen her candidacy and elevate her profile in the global research community. Overall, Yasamin’s qualifications and achievements make her a compelling candidate for this prestigious award. Publications Top Notes Carboxymethyl Chitosan-Gelatin-Mesoporous Silica Nanoparticles Containing Myrtus communis L. Extract as a Novel Transparent Film Wound Dressing Authors: Y. Haririan, A. Asefnejad, H. Hamishehkar, M.R. Farahpour Journal: International Journal of Biological Macromolecules Year: 2023 Volume: 253 Article Number: 127081