Dr. Inam Illahi | Software Engineering | Best Researcher Award

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Dr. Inam Illahi | Software Engineering | Best Researcher Award

Dr. Inam Illahi, Emerson University Mutlan, Pakistan

Inam Illahi is an accomplished Assistant Professor at Emerson University Multan, Pakistan. With a rich academic background and over a decade of teaching experience, he has made significant contributions to the field of computer science. Inam holds a PhD in Computer Science and Technology from the Beijing Institute of Technology, where he focused on Assistant Technologies for Crowdsourcing Software Development. His research encompasses machine learning, deep learning, and software development, yielding several publications in prestigious journals. In addition to his academic pursuits, Inam has worked in various educational institutions, enhancing the quality of education and fostering student engagement. His dedication to research and teaching reflects a passion for advancing knowledge and technology, making him a respected figure in his field. Inam’s commitment to improving educational practices and research outcomes highlights his role as a leader in academia.

Professioanl Profile

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Summary of Suitability for the Research for Best Researcher Award

Inam Illahi is a highly qualified candidate for the Research for Best Researcher Award, showcasing a solid academic and professional background in computer science, particularly in the field of software development and machine learning. His extensive teaching experience at various reputable universities, including his current role as an Assistant Professor at Emerson University Multan, highlights his commitment to academia and his ability to contribute significantly to the educational sector.

🎓  Education

Inam Illahi’s educational journey is marked by notable achievements and a commitment to excellence. He earned his PhD in Computer Science and Technology from the Beijing Institute of Technology, China, between 2016 and 2022. His research during this time focused on Assistant Technologies for Crowdsourcing Software Development, resulting in impactful publications. Prior to his PhD, Inam completed his Master’s in Software Engineering and Management from Chalmers University of Technology, Sweden, in 2010, where he gained insights into software development practices. He also holds a Master of Computer Science from the University of Sargodha, Pakistan, which he completed in 2007. His educational foundation is complemented by a Bachelor of Arts in Computer Science and Economics from the same institution. Inam’s diverse academic experiences, along with his international exposure in Sweden and Denmark, have equipped him with a global perspective and a strong skill set in technology and education.

💼   Experience 

Inam Illahi possesses extensive experience in academia, contributing to various educational institutions over the past decade. Since March 2024, he has been serving as an Assistant Professor at Emerson University Multan, where he is involved in teaching and research activities. Before that, he held a Tenure Track Assistant Professor position at the University of Education, Lahore, Multan Campus, from August 2023 to March 2024. His earlier roles include Assistant Professor at the Institute of Southern Punjab and Lecturer positions at National Textile University, Faisalabad, and Riphah International University. Inam has also served as an Academic Coordinator at COMSATS Institute of Technology, where he played a crucial role in teaching and administration. His experience as a Deputy Director at the Quality Enhancement Cell at The University of Faisalabad further underscores his leadership abilities. Inam’s diverse roles highlight his commitment to enhancing the educational landscape through effective teaching and administrative practices.

🏅  Awards and Honors 

Inam Illahi’s commitment to excellence in research and education has earned him several accolades throughout his career. Notably, his innovative work in crowdsourcing software development and machine learning has resulted in multiple publications in reputable journals, receiving recognition from his peers. His research on the “Dr. Wheat” web-based expert system for diagnosing diseases in Pakistani wheat was presented at the International Conference of Information Security and Internet Engineering in London in 2008, showcasing his contributions to agricultural technology. In addition to research-related recognition, Inam has been actively involved in various academic committees and organizations, where his leadership skills have been acknowledged. His role as Deputy Director at The Quality Enhancement Cell highlighted his commitment to improving educational quality, further solidifying his reputation in academia. Inam’s dedication to research and education continues to inspire students and colleagues alike, contributing to his growing list of honors and achievements.

🌍  Research Focus

Inam Illahi’s research focuses primarily on the intersection of software development and artificial intelligence, with a particular emphasis on crowdsourcing and machine learning. His PhD thesis explored Assistant Technologies for Crowdsourcing Software Development, where he analyzed motivating and inhibiting factors for developers and success prediction in competitive crowdsourcing projects. His innovative contributions include the application of machine learning techniques for resolution prediction, enhancing the success rates of software development initiatives. Inam has published several influential papers in leading journals, examining various aspects of software project management and quality assurance. Notable works include studies on bug report prioritization using convolutional neural networks and severity prediction models. Through his research, Inam aims to bridge the gap between theory and practice in software development, providing valuable insights and tools for industry practitioners. His commitment to advancing knowledge in this rapidly evolving field makes him a key player in the research community.

📖 Publications Top Notes

  • Title: Deep neural network-based severity prediction of bug reports
    Cited by: 94
  • Title: CNN-based automatic prioritization of bug reports
    Cited by: 85
  • Title: Dr. Wheat: a Web-based expert system for diagnosis of diseases and pests in Pakistani wheat
    Cited by: 79
  • Title: Serum tumor necrosis factor-alpha as a competent biomarker for evaluation of disease activity in early rheumatoid arthritis
    Cited by: 19
  • Title: An empirical study on competitive crowdsource software development: motivating and inhibiting factors
    Cited by: 13

Assoc. Prof. Dr. Hui Zhang | Artificial Intelligence | Industry Achievement Award

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Assoc. Prof. Dr. Hui Zhang | Artificial Intelligence | Industry Achievement Award

Assoc. Prof. Dr. Hui Zhang, Guizhou University of Finance and Economics, China

Hui Zhang is a distinguished senior engineer and associate professor at the School of Information, Guizhou University of Finance and Economics, China. With a Ph.D. in Computational Mathematics from Guizhou Normal University, Zhang has a diverse background spanning both academia and industry. His expertise ranges from computational mathematics to big data and cloud computing, having held prominent roles in R&D departments in China’s tech industry. Additionally, Zhang has served as a reviewer for prestigious journals, contributed to key projects, and holds multiple patents in data science and technology. His ongoing research and professional services make him a well-recognized expert in his field.

Professional Profile

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Summary of Suitability for the Research for Industry Achievement Award

Dr. Hui Zhang demonstrates a unique combination of academic and industrial achievements, making him a strong candidate for the Research for Industry Achievement Award. His background in computational mathematics and computer science, coupled with his experience in R&D and leadership roles in the big data industry, aligns well with the award’s focus on impactful industrial contributions.

🎓    Education

Hui Zhang completed his Bachelor’s in Information and Computational Science from Guizhou Normal University in 2010, alongside a Bachelor’s in English Education. He pursued a Master’s in Computational Mathematics at the same institution from 2010 to 2013. Hui continued his academic journey by earning a Ph.D. in Computational Mathematics, focusing on innovative computational methods. His educational experience highlights a strong foundation in both mathematics and interdisciplinary learning, setting the stage for his research and teaching career at Guizhou University of Finance and Economics.

💼   Experience

Hui Zhang’s career includes a range of positions in both academia and industry. After completing his master’s degree, he worked as a Business Manager at the Postal Savings Bank of China. He then transitioned to academic research while pursuing his Ph.D., contributing to key projects at the Guizhou Key Laboratory of Information and Computing Science. In industry, Zhang served as a Senior R&D Engineer and later General Manager of the R&D Department at Guizhou-Cloud Big Data Industry Development Co. Since 2022, he has been an associate professor at Guizhou University of Finance and Economics and a postdoctoral researcher, continuing to innovate in computer science and data science fields.

🏅  Awards and Honors

Hui Zhang’s numerous recognitions include being a Review Expert for multiple academic and governmental bodies, such as the Guizhou Provincial Department of Science and Technology. His technical contributions have earned him industry accolades, and he was invited to join the Big Data Expert Committee of the China Computer Federation. Zhang has also been honored as an Industrial Mentor in Guizhou Province and contributed as an expert reviewer for the prestigious Alexandria Engineering Journal. His expertise in computational mathematics and data science has made him a sought-after advisor and collaborator.

🌍  Research Focus

Hui Zhang’s research focuses on computational mathematics, big data, and information systems, particularly in developing algorithms and systems for data processing and analysis. He has worked extensively on Pulsar Data Processing, contributing to the design and implementation of comparative analysis and visualization systems. His research extends into numerical analysis, with a focus on finite element methods for solving complex mathematical problems. Zhang’s interdisciplinary approach combines theoretical mathematics with practical applications in data science, making significant advances in these fields.

📖 Publication Top Notes

  1. Generalized picture fuzzy Frank aggregation operators and their applications
  2. A second-order accurate and unconditionally energy stable numerical scheme for nonlinear sine-Gordon equation
  3. Asymmetrical interactions driven by strategic persistence effectively alleviate social dilemmas
  4. A Certificateless Verifiable Bilinear Pair-Free Conjunctive Keyword Search Encryption Scheme for IoMT
  5. Deformations and Extensions of Modified λ-Differential 3-Lie Algebras

Mr. Daniel Morariu | Resilience | Best Researcher Award

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Mr. Daniel Morariu | Resilience | Best Researcher Award

Mr. Daniel Morariu, Lucian Blaga University of Sibiu, Romania

Morariu Ionel Daniel is an esteemed associate professor at “Lucian Blaga” University of Sibiu, Romania, with expertise in computer science, automatic systems, data mining, and machine learning. Born on September 17, 1974, in Sighisoara, he has dedicated over two decades to education and research. He holds a Bachelor’s and Master’s degree in Computer Science from “Lucian Blaga” University and completed his PhD in Computer Science with a focus on “Automatic Knowledge Extraction from Unstructured Data” in 2007. Daniel has been a consistent contributor to advanced research, particularly in data mining, neural networks, and natural language processing. With a robust portfolio of software engineering and academic experience, his career includes impactful projects in automation systems, energy control solutions, and numerous published research papers. His dedication to knowledge dissemination and technological advancements has earned him respect in both academic and industrial circles.

Professional Profile

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Summary of Suitability for the Award

Dr. Morariu Ionel Daniel stands out as a highly qualified candidate for the Research for Best Researcher Award, particularly due to his extensive academic background, research experience, and contributions in the field of Computer Science. His educational path, including a PhD focused on automatic knowledge extraction from unstructured data, demonstrates his depth in data mining and machine learning, areas that are essential in today’s technological landscape. Furthermore, his PhD was supported by SIEMENS Corporate Technology, highlighting the practical relevance of his work.

 🎓  Education 

Daniel Morariu completed his secondary education at “Mircea Eliade” Theoretic High School, Sighisoara, between 1989-1993. He pursued higher education at “Lucian Blaga” University of Sibiu’s Engineering Faculty, earning a Bachelor’s degree in Computer Science and Automatic Systems in 1998. His academic journey continued with a Master’s degree in Computer Science in 1999, specializing in “Parallel and Distribute Processing Systems” from the same university. His thirst for knowledge culminated in a PhD in Computer Science, awarded in April 2007. His PhD research focused on “Contributions to Automatic Knowledge Extraction from Unstructured Data,” under the supervision of Professor Lucian N. Vințan. Supported by SIEMENS Corporate Technology from Munich, his doctoral research provided significant insights into data mining and natural language processing. This strong educational foundation has positioned him as a distinguished academic in the field of computer science.

💼     Experience 

Daniel Morariu has held a variety of academic positions throughout his career. He began as a teaching assistant at “Lucian Blaga” University in 1998, contributing to courses such as Microprocessors and Object-Oriented Programming. From 2003 to 2007, he served as a lecturer, teaching advanced courses in Neural Networks and Data Mining. In 2007, he became an associate professor, focusing on courses like Data Mining, Machine Learning, and Interfaces and Communication Protocols. Outside academia, Morariu gained valuable industry experience. He worked with SC Consultens Informationstechnik SRL, a German software company, as a software engineer from 2001 to 2002. He also worked as an engineer at SC IRMES SA Sibiu from 1998 to 2000, developing software for monitoring generators and controlling gas supply in thermoelectric power stations. His career reflects a strong blend of academic expertise and practical industry experience, especially in computer science and automation systems.

🏅  Awards and Honors

Throughout his career, Daniel Morariu has been recognized for his contributions to computer science and engineering. His PhD research, supported by SIEMENS Corporate Technology from Munich, was a notable achievement, reflecting both scientific and financial backing from a prestigious institution. Over the years, his dedication to teaching and research has earned him accolades within the academic community at “Lucian Blaga” University, including recognition for his innovative approach to data mining and machine learning education. His work in automation systems, particularly in the energy sector, has also been praised for its practical applications, further solidifying his status as a leading figure in the intersection of academia and industry. Though specific awards are not listed, his consistent professional growth and contributions speak to a career filled with academic accomplishments and recognition.

 🌍  Research Focus

Daniel Morariu’s research primarily revolves around data mining, machine learning, and natural language processing. His academic focus is on extracting meaningful knowledge from unstructured data using advanced techniques such as Support Vector Machines (SVM) and neural networks. His PhD dissertation on “Contributions to Automatic Knowledge Extraction from Unstructured Data” set the foundation for his continuing research into text document processing and computational linguistics. Additionally, he explores the applications of these technologies in real-world problems, particularly in automation systems and energy sector monitoring. His work on computational linguistics helps bridge the gap between machine learning models and language understanding, while his research in data mining enhances predictive models across industries. Morariu’s blend of theoretical research and practical applications has made him a valuable contributor to advancements in these fields, influencing both academic research and industrial applications.

📖 Publication Top Notes

  • Feature selection methods for an improved SVM classifier
    • Cited by: 31
  • Meta-Classification using SVM Classifiers for Text Documents
    • Cited by: 27
  • The WEKA Multilayer Perceptron Classifier
    • Cited by: 22
  • Text Mining Methods Based on Support Vector Machine
    • Cited by: 22
  • Evolutionary Feature Selection for Text Documents Using the SVM
    • Cited by: 22

Dr. Soheila Kookalani | Construction | Best Researcher Award

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Dr. Soheila Kookalani | Construction | Best Researcher Award

Dr. Soheila Kookalani, Cambridge University, United Kingdom

Soheila Kookalani is a distinguished Research Associate at the University of Cambridge, specializing in Civil and Structural Engineering. She has a profound expertise in steel reuse, the circular economy, life-cycle assessment, and the integration of digital twin technologies in construction. Her research focuses on leveraging artificial intelligence and machine learning to optimize structural designs, promoting sustainability in construction. Soheila holds a Ph.D. in Civil and Structural Engineering from Shanghai Jiao Tong University, where she pioneered research on GFRP elastic gridshells. With a commitment to environmental responsibility, she continuously explores innovative ways to integrate sustainable practices into building designs, aiming to revolutionize construction methodologies. She has numerous publications in leading journals, demonstrating her contribution to both academia and the industry. Her work emphasizes sustainable engineering practices that align with modern technological advancements, particularly in the realm of structural optimization and reuse strategies.

Professional Profile

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Summary of Suitability for the Research for Best Researcher Award

Soheila Kookalani’s innovative approach to structural engineering, coupled with her strong commitment to sustainability and integration of advanced technologies, positions her as a highly suitable candidate for the Research for Best Researcher Award. Her work has significant implications for the future of sustainable construction, making her a valuable asset to both academia and industry.

🎓 Education 

Soheila Kookalani pursued her academic journey with a solid foundation in architectural and civil engineering. She earned her Bachelor of Science in Architectural Engineering from Azad University in Iran, where her thesis explored hybrid architecture in cinematic arts. She then advanced her studies with a Master of Science in Civil and Structural Engineering from Hohai University, China, focusing on the seismic performance of hybrid structures in high-rise buildings. Her academic journey culminated with a Ph.D. from Shanghai Jiao Tong University, China, where she focused on the structural optimization of GFRP elastic gridshells using machine learning techniques. Her doctoral research contributed to advancing knowledge in structural design and building sustainability. Throughout her studies, Soheila has consistently integrated innovative technologies, such as artificial intelligence and machine learning, into her research, making her an authority in the field of structural design and optimization for sustainable construction.

💼 Experience 

Soheila Kookalani has accumulated extensive experience in civil and structural engineering, with a primary focus on sustainable design practices. She currently serves as a Research Associate at the University of Cambridge, where she is engaged in a groundbreaking project on the reuse of structural steel in construction. Her experience spans across diverse areas, including the circular economy, life-cycle assessment, building information modeling (BIM), and digital twin technology. From 2018 to 2022, she conducted research on GFRP elastic gridshells as part of her Ph.D. at Shanghai Jiao Tong University. Prior to this, Soheila gained practical experience working on seismic performance evaluation of hybrid structures during her Master’s at Hohai University. Her expertise also extends to the application of artificial intelligence in optimizing structural designs, demonstrating her capacity to bridge the gap between theoretical research and practical application in sustainable construction.

🏅Awards and Honors 

Throughout her academic and professional career, Soheila Kookalani has been recognized for her outstanding contributions to civil and structural engineering. She has received several prestigious awards and honors, including recognition from leading engineering conferences and academic institutions. Her work on the integration of AI and machine learning in structural design has garnered international attention, earning her accolades for innovation in sustainable construction. Soheila has also been honored for her research on GFRP elastic gridshells, receiving commendations for excellence in structural optimization and sustainable design. Her role as a published author in top-tier engineering journals has further solidified her reputation as a leading researcher in the field. Additionally, Soheila’s contributions to the reuse of structural steel and her involvement in cutting-edge projects at the University of Cambridge have earned her numerous industry awards, highlighting her commitment to environmental responsibility and sustainable engineering practices.

🌍 Research Focus 

Soheila Kookalani’s research is centered on the intersection of civil engineering, sustainability, and advanced technology. Her primary focus is on steel reuse, promoting a circular economy in construction through the reuse of structural components. She is also deeply involved in life-cycle assessments, aiming to reduce the environmental impact of construction projects. Her research integrates building information modeling (BIM) and digital twin technology to enhance the design, monitoring, and optimization of construction projects. Soheila is particularly interested in applying artificial intelligence (AI) and machine learning to optimize structural designs, especially in the context of GFRP elastic gridshells. Her work on generative AI in structural engineering seeks to streamline design processes and improve sustainability. By combining these advanced technologies, her research contributes to developing more efficient, eco-friendly building practices that align with global sustainability goals.

📖 Publication Top Notes

  • BIM-based augmented reality for facility maintenance management
    • Cited by: 24
  • Structural analysis of GFRP elastic gridshell structures by particle swarm optimization and least square support vector machine algorithms
    • Cited by: 18
  • Shape optimization of GFRP elastic gridshells by the weighted Lagrange ε-twin support vector machine and multi-objective particle swarm optimization algorithm considering …
    • Cited by: 14
  • An analytic approach to predict the shape and internal forces of barrel vault elastic gridshells during lifting construction
    • Cited by: 14
  • Effect of Fluid Viscous Damper parameters on the seismic performance
    • Cited by: 14

Dr. Stela Dragomanova | Neuroscience | Best Researcher Award

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Dr. Stela Dragomanova| Neuroscience | Best Researcher Award

Dr. Stela Dragomanova, Medical University of Varna, Bulgaria

Dr. Stela Dragomanova is a distinguished researcher and educator at the Medical University of Varna. She earned her master’s degree in Pharmacy from the Medical University of Sofia in 2004 and later specialized in Clinical Pharmacy. In 2020, she completed her Ph.D. in Pharmacology at the Institute of Neurobiology, Bulgarian Academy of Sciences. Dr. Dragomanova’s research centers on neuropharmacology, particularly neurodegenerative diseases. She is a member of the Bulgarian Pharmaceutical Union and serves as Chairlady of the Ethics Committee for the Regional Pharmaceutical Collegium in Varna. Dr. Dragomanova has published 30+ peer-reviewed papers, contributing significantly to pharmacology and neuroscience. She has also served as Assistant Professor from 2010 to 2021 and is currently Chief Assistant Professor in the Department of Pharmacology at the Medical University of Varna.

Professional Profile

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Summary of Suitability for the Research for Best Researcher Award

Dr. Stela Dragomanova demonstrates a strong profile as a candidate for the Research for Best Researcher Award. With a Ph.D. in Pharmacology and a focus on neuropharmacology, her research is centered around neurodegenerative diseases, a critical area of biomedical research. Her expertise in in vivo preclinical models and behavioral tests positions her as a valuable contributor to the scientific community, particularly in neuropharmacology and toxicology.Her academic career includes over a decade of teaching and research at the Medical University of Varna, Bulgaria, where she has steadily advanced from Assistant Professor to Chief Assistant Professor. Dr. Dragomanova has also made substantial contributions to the scientific literature, with 30+ publications, including articles in high-impact journals such as Antioxidants and Molecules, with topics addressing neuroprotective strategies and experimental pharmacology.

🎓 Education 

Dr. Stela Dragomanova began her academic journey at the Medical University of Sofia, where she obtained her master’s degree in Pharmacy in 2004. She further specialized in Clinical Pharmacy, enhancing her expertise in pharmacological interventions. Driven by her passion for neuropharmacology, Dr. Dragomanova pursued her Ph.D. in Pharmacology at the Bulgarian Academy of Sciences’ Institute of Neurobiology, completing it in 2020. Her doctoral research provided significant insights into neurodegenerative diseases and related pharmacotherapies. With a strong foundation in experimental pharmacology and toxicology, Dr. Dragomanova is equipped with advanced skills in preclinical in vivo models and behavioral testing. Her academic qualifications, coupled with her research experience, reflect her commitment to advancing knowledge in the pharmaceutical and neuropharmacological fields.

💼 Experience 

Dr. Stela Dragomanova has been an integral part of the Medical University of Varna since 2010, starting as an Assistant Professor in the Department of Pharmacology, Toxicology, and Pharmacotherapy. She transitioned into the role of Chief Assistant Professor in 2021, where she continues to lead and mentor young scientists in neuropharmacology. In her academic career, she has overseen numerous research projects focusing on neurodegenerative disorders, particularly in exploring neuroprotective agents and pharmacological treatments. She has extensive expertise in in vivo preclinical models and behavioral testing in experimental pharmacology. Dr. Dragomanova is also deeply involved in regulatory and ethical aspects of pharmacology research, serving as the Chairlady of the Ethics Committee for the Regional Pharmaceutical Collegium in Varna and being an active member of several scientific and pharmaceutical associations.

🏅Awards and Honors 

Dr. Stela Dragomanova has been recognized for her outstanding contributions to the field of pharmacology and her dedication to healthcare and education. In 2018, she was named “Pharmacist of the Year” for the Varna region by the Regional Pharmaceutical Collegium. This prestigious award highlights her commitment to the pharmaceutical profession and the positive impact of her work in the healthcare sector. In addition to her regional recognition, Dr. Dragomanova is an esteemed member of the Bulgarian Pharmaceutical Union, which is part of the Pharmaceutical Group of the European Union (PGEU). She also holds leadership roles in several academic and professional organizations, including the Bulgarian Association of Pharmacology, Clinical Pharmacology, and Therapeutics. Her extensive experience in both research and education further solidifies her as a prominent figure in the pharmacological sciences.

🌍 Research Focus 

Dr. Stela Dragomanova’s research is primarily focused on neuropharmacology, particularly in understanding the mechanisms underlying neurodegenerative diseases. Her work aims to discover potential therapeutic agents that can mitigate the progression of disorders such as Alzheimer’s and Parkinson’s disease. She has developed expertise in using in vivo preclinical models to evaluate neuroprotective compounds and conduct behavioral tests. Her research explores the role of antioxidants and polyphenols, studying their neuroprotective effects and potential applications in pharmacotherapy. Additionally, Dr. Dragomanova is interested in the therapeutic potential of lipid emulsions in treating convulsions and other toxicological conditions. Her investigations have led to a deeper understanding of the molecular and biochemical processes that drive neurodegeneration, with a strong focus on developing novel interventions for these challenging medical conditions.

📖 Publications Top Notes

  • Intravenous Lipid Emulsions in Anticonvulsants’ Toxicity
  • Trehalose: Neuroprotective Effects and Mechanisms—An Updated Review
  • Intravenous Lipid Emulsions in Anticonvulsants’ Toxicity
  • Neuropharmacological investigation of myrtenal conjugates with aminoadamantane
  • Emerging Therapeutic Potential of Polyphenols from Geranium sanguineum L. in Viral Infections, Including SARS-CoV-2

 

Assoc. Prof. Dr. Somayeh Labafi | management | Women Researcher Award

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Assoc. Prof. Dr. Somayeh Labafi | management | Women Researcher Award

Assoc. Prof. Dr. Somayeh Labafi, Iranian Research institute for information science and technology, Iran

Dr. Somayeh Labafi is an associate professor at the Iranian Research Institute for Information Science and Technology (IranDoc), specializing in media management and policy analysis. With a strong background in both mathematics and media studies, she focuses on the intersection of technology, communication, and policy frameworks. Her academic journey began with a Bachelor’s degree in Mathematics from the University of Esfahan, followed by a Master’s and PhD in Media Management from the University of Tehran. Dr. Labafi has authored several books and research articles exploring the impact of digital platforms, media entrepreneurship, and data protection policies. She is a recognized thought leader in the field, contributing to both academic discussions and policy-making processes in Iran. Her work extends to analyzing social media dynamics and the implications of media regulations on society.

Professional Profile

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Suitability of Somayeh Labafi for the Research for Women Researcher Award

Summary: Dr. Somayeh Labafi is a distinguished academic and researcher, currently an Associate Professor at the Iranian Research Institute for Information Science and Technology (IranDoc). She has an extensive educational background, holding a PhD in Media Management from the University of Tehran, after earning her Master’s in the same field and a Bachelor’s in Mathematics. Her interdisciplinary expertise in media management and policy, coupled with her focus on data protection and digital media, makes her a leading researcher in her domain.

 🎓 Education 

Dr. Somayeh Labafi’s educational path demonstrates her multidisciplinary expertise in both quantitative and social sciences. She earned her Bachelor of Science in Mathematics from the University of Esfahan, a foundation that sharpened her analytical skills. Pursuing her passion for media and communication, she obtained a Master’s degree in Media Management from the University of Tehran. Her commitment to furthering her knowledge led her to pursue a Ph.D. in Media Management, also from the University of Tehran. Throughout her academic journey, Dr. Labafi explored complex interactions between media, technology, and society, equipping her with the skills to analyze the policy frameworks surrounding data protection, media entrepreneurship, and digital communication. Her education has been instrumental in shaping her research focus on policy-making in media and technology sectors, positioning her as a thought leader in both academic and policy circles.

 💼 Experience 

Dr. Somayeh Labafi currently holds the position of associate professor at the Iranian Research Institute for Information Science and Technology (IranDoc). With over a decade of experience, she has made significant contributions to media management and policy research. Her career spans a variety of roles, from a lecturer to a research leader, where she focuses on the impact of digital technologies on media regulation and innovation. Dr. Labafi has collaborated with various institutions and international researchers to explore pressing issues in data protection, social media, and public communication. She has authored numerous chapters in internationally recognized books, addressing the intricacies of media richness, policy frameworks, and knowledge-sharing behavior in organizations. Her expertise is frequently sought in policy-making discussions, particularly those involving media regulations and the protection of digital rights, making her a vital figure in shaping Iran’s evolving media landscape.

🏅Awards and Honors 

Dr. Somayeh Labafi has received numerous accolades for her pioneering research in media management and digital policy. She has been honored for her contributions to the academic community through her extensive research on media entrepreneurship, policy-making, and data protection. Notably, she was recognized for her groundbreaking chapter contributions to prominent international books such as “5G, Cybersecurity, and Privacy in Developing Countries” and “Contemporary Application of Actor-Network Theory.” Her work has garnered attention from both academic and policy-making bodies, establishing her as an expert in the field of media regulations. Dr. Labafi has also been invited to speak at international conferences and workshops, where her insights into media policy have influenced discussions on social media governance and network neutrality. Her accolades reflect her dedication to advancing knowledge and shaping policy in media management, with an emphasis on digital transformation in developing countries.

🌍 Research Focus 

Dr. Somayeh Labafi’s research is centered on media management, digital policy-making, and the socio-technological implications of media platforms. Her work explores the intersection of media innovation, regulation, and entrepreneurship, with a focus on how digital platforms shape public communication and data protection policies. She has extensively researched topics such as network neutrality, media richness, and the role of social media in shaping public behaviors and policy. Her recent projects delve into the implications of media management in the era of digital transformation, with a particular emphasis on the challenges and opportunities posed by emerging technologies like 5G and Web 3.0. Dr. Labafi employs methodologies such as Actor-Network Theory and ethnographic studies to analyze media dynamics and their impact on policy frameworks. Her research aims to provide insights for both academic and policy-making communities, particularly in developing countries.

📖 Publications Top notes 

Knowledge hiding as an obstacle of innovation in organizations: A qualitative study of the software industry
  • Cited by: 103
Effects of social media on the environmental protection behaviour of the public (Case study: Protecting Zayandeh-rood river environment)
  • Cited by: 38
An introduction to competitiveness in a fast-changing business environment
  • Cited by: 36
Contemporary applications of actor-network theory
  • Cited by: 26
Media Entrepreneurship and Web 3.0: The way passed, the way forward
  • Cited by: 21*