Category: Biography

Education Background🎓

PhD in Distributed Computational Technologies (Honor) – St. Petersburg University
Master’s in Distributed Computational Technologies – St. Petersburg University | GPA: 4.8
Bachelor’s in Programming and Information Technology – St. Petersburg University | GPA: 4.6
Graduate Studies – Waseda University, Fukuoka, Japan
Certifications: MEXT Scholarship Recipient

Professional Experience🌱

1. Software Engineer, Lanit-Tercom (Jul 2022 – Present)

Developed decentralized applications (DApps) for blockchain, reducing operational costs and enhancing multi-network support.
Integrated APIs for augmented reality and optimized NFT data loading by 25%.
Conducted cross-chain research and implemented smart contract solutions.

2. Software Engineer, Huawei Russian Research Institute (Oct 2022 – Feb 2023)

Pioneered advancements in neural network quantization, improving computation speed and accuracy.

3. Research Laboratory Assistant, SPBU – Huawei (Dec 2020 – Jul 2022)

Conducted research in voice conversion and neural network development, leading to a 2% increase in model precision.

4. Software Engineer, Distributed Ledger Technology Center (Feb 2019 – Jul 2020)

Built DApps for Ethereum, integrated blockchain with IoT devices, and optimized Flask backend systems.

Research Interests🔬

Dr. Pavlova’s research focuses on distributed systems, blockchain technology, AI, computer vision, IoT integration, and real-time neural network applications. She has contributed to enhancing underwater video analysis systems, optimizing data pipelines, and advancing fault detection in industrial settings.

Author Metrics

Dr. Ekaterina Pavlova has established herself as a prolific contributor to the field of distributed systems, artificial intelligence, and blockchain technologies, with her research gaining notable recognition in academic and industrial domains. Her work has garnered approximately 200 citations, reflecting the impact and relevance of her contributions to the scientific community. With an h-index of 7, Dr. Pavlova demonstrates consistent influence through high-quality publications, and her i10-index of 5 highlights her ability to produce multiple papers that have been cited extensively. Her research publications span reputable journals and international conferences, underscoring her dedication to advancing technology and solving real-world challenges.

Publications Top Notes 📄

1. Underwater Biotope Mapping: Automatic Processing of Underwater Video Data

Authors: Iakushkin, O.O., Pavlova, E.D., Lavrova, A.K., Shabalin, N.V., Sedova, O.S.
Publication: Proceedings of Science, 2022, Vol. 429.
Abstract and Related Documents: Not accessible.
Citation Count: 0
Type: Conference Paper
Summary: This paper discusses the automated processing of underwater video data for biotope mapping using advanced computational methods, with a focus on efficiency and accuracy in underwater ecosystem analysis.

2. Automated Marking of Underwater Animals Using a Cascade of Neural Networks

Authors: Iakushkin, O., Pavlova, E., Pen, E., Shabalin, N., Sedova, O.
Publication: Lecture Notes in Computer Science (LNCS), 2021, Vol. 12956, pp. 460–470.
Abstract and Related Documents: Not accessible.
Citation Count: 2
Type: Conference Paper
Summary: This research presents a cascade of neural networks for the automated marking of underwater animals. It emphasizes efficient data processing and innovative neural network architecture to enhance detection accuracy in underwater environments.

3. Modelling the Interaction of Distributed Service Systems Components

Authors: Iakushkin, O., Malevanniy, D., Pavlova, E., Fatkina, A.
Publication: Lecture Notes in Computer Science (LNCS), 2020, Vol. 12251, pp. 48–57.
Abstract and Related Documents: Not accessible.
Citation Count: 0
Type: Conference Paper
Summary: This paper explores the modeling of distributed service system components, focusing on their interaction dynamics. It provides valuable insights into the efficient design of distributed applications across networked environments.

4. Architecture of a Smart Container Using Blockchain Technology

Authors: Iakushkin, O., Selivanov, D., Pavlova, E., Korkhov, V.
Publication: Lecture Notes in Computer Science (LNCS), 2019, Vol. 11620, pp. 537–545.
Abstract and Related Documents: Not accessible.
Citation Count: 1
Type: Conference Paper
Summary: The study proposes a smart container architecture leveraging blockchain technology to improve logistics and data integrity in supply chain management.

Conclusion

Dr. Ekaterina Pavlova is a deserving candidate for the Best Researcher Award, given her proven track record of impactful research, interdisciplinary expertise, and strong contributions to emerging technologies like blockchain and AI. Her innovative solutions and dedication to solving real-world challenges set her apart as a dynamic and forward-thinking researcher. With continued emphasis on collaboration and dissemination, Dr. Pavlova is poised to make even more significant contributions to her field in the future.

Diego Emmanuel Boldrini | Graph Analytics | Best Researcher Award

Posted on 09/01/202509/01/2025 by ScienceFatherLeave a Comment

Prof. Dr. Diego Emmanuel Boldrini | Graph Analytics | Best Researcher Award

Research Associate at Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina📖

Diego Emmanuel Boldrini is a Chemical Engineer and a PhD in Chemical Engineering from the Universidad Nacional del Sur (UNS), Argentina. He is currently a CONICET Adjoint Researcher at the Chemical Engineering Pilot Plant (PLAPIQUI, UNS-CONICET) in Bahía Blanca, Argentina. Boldrini has a strong academic and professional background in chemical engineering, specializing in catalysis and chemical process development. He has authored and presented numerous scientific papers at prestigious international conferences.

Profile

Education Background🎓

PhD in Chemical Engineering, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina, March 2015.
Bachelor’s in Chemistry, E.E.T. N° 4, Bahía Blanca, Argentina, December 1998.
Technical Chemist, E.E.T. N° 4, Bahía Blanca, Argentina, December 1999.
Chemical Engineer, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina, August 2009.

Professional Experience🌱

Boldrini has held various prestigious roles at CONICET (National Scientific and Technical Research Council, Argentina), where he was designated as a CPA Adjunto (March 2015 – October 2018), CIC Asistente (November 2018 – June 2022), and CIC Adjunto (since June 2022) at the PLAPIQUI (UNS-CONICET). Throughout his career, he has contributed significantly to research in chemical engineering, with a focus on catalyst development and technological processes related to chemical engineering.

Research Interests🔬

His research interests include the development of catalytic systems for chemical processes, specifically in the areas of monolithic catalysts, catalysis in energy generation, and hydrogen production and purification. He is also interested in process optimization, risk management in technological innovation, and the environmental impact of chemical processes.

Author Metrics

Diego Emmanuel Boldrini has a robust academic profile, with an impressive record of scholarly contributions. He holds an ORCID ID of 0000-0003-2221-802X, which tracks his academic output. Boldrini has authored several peer-reviewed articles in his field, particularly focusing on catalyst development and chemical engineering processes. His doctoral thesis, “Desarrollo de catalizadores monolíticos con sustrato de aluminio anodizado”, was defended in March 2015, receiving an exceptional grade of 10/10 (Outstanding). Additionally, he has presented at various renowned scientific conferences, such as the XXIII Congreso Iberoamericano de Catálisis (2012) and the XVIII Congreso Argentino de Catálisis (2013), where he shared his innovative research with the global academic community.

Publications Top Notes 📄

1. Study of Structural Properties of Acid-Treated Natural Sediment and Its Application as a Sustainable Catalyst

Authors: Reinoso, D.M., Angeletti, S., Cervellini, P.M., Boldrini, D.E.
Journal: Brazilian Journal of Chemical Engineering
Year: 2020
Volume: 37, Issue 4
Pages: 679–690
Citations: 4

2. Kinetic Study of Fuel Bio-Additive Synthesis from Glycerol Esterification with Acetic Acid Over Acid Polymeric Resin as Catalyst

Authors: Reinoso, D.M., Boldrini, D.E.
Journal: Fuel
Year: 2020
Volume: 264, Article 116879
Citations: 42

3. Highly Ordered Mesoporous Al-MCM-41 Synthesis through Valorization of Natural Sediment

Authors: Boldrini, D.E., Angeletti, S., Cervellini, P.M., Reinoso, D.M.
Journal: ACS Sustainable Chemistry and Engineering
Year: 2019
Volume: 7, Issue 5
Pages: 4684–4691
Citations: 22

4. Monolithic Stirrer Reactor for Vegetable Oil Hydrogenation: A Technical and Economic Assessment

Authors: Boldrini, D.E.
Journal: Chemical Engineering and Processing – Process Intensification
Year: 2018
Volume: 132
Pages: 229–240
Citations: 10

5. Effect of Operating Variables and Kinetics of the Lipase Catalyzed Transesterification of Ethylene Carbonate and Glycerol

Authors: Gutierrez-Lazaro, A., Velasco, D., Boldrini, D.E., Esteban, J., Ladero, M.
Journal: Fermentation
Year: 2018
Volume: 4, Issue 3, Article 75
Citations: 15

Conclusion

Prof. Dr. Diego Emmanuel Boldrini is a highly deserving candidate for the Best Researcher Award due to his outstanding academic background, innovative research in catalysis, and contributions to sustainable chemical processes. His scholarly works, extensive citations, and leadership in the academic and professional community position him as an influential figure in chemical engineering research. By enhancing his collaboration with industry and exploring interdisciplinary research, Boldrini could further expand his impact and continue to drive significant advancements in his field.

Given his proven track record, leadership, and dedication to advancing scientific knowledge in critical areas like catalysis, sustainability, and energy, he is an ideal candidate for the Best Researcher Award.

Dominique Badr | Twin Pregnancy | Best Researcher Award

Posted on 09/01/202509/01/2025 by ScienceFatherLeave a Comment

Dr. Dominique Badr | Twin Pregnancy | Best Researcher Award

Physician at University Hospital Brugmann, Belgium📖

Dr. Dominique Badr is a distinguished specialist in Fetal Medicine and Obstetrics and Gynecology, currently serving as the Deputy Chief of Fetal Medicine at the University Hospital Brugmann, Université Libre de Bruxelles, in Brussels, Belgium. With a strong academic foundation, Dr. Badr is a Ph.D. student in Medical Science at Université Libre de Bruxelles, where he also obtained his biostatistics certificate. He completed advanced studies in Fetal Medicine and Gynecological Ultrasound, alongside a diploma in Maternal and Pregnancy Diseases and Advanced Laparoscopy in Gynecology.

Profile

Education Background🎓

Dr. Badr holds multiple prestigious qualifications, including a Docteur in Medicine from the Lebanese University and a diploma in Gynecological and Obstetrical Ultrasound from Université Paris-Sud. He pursued further training in Fetal Medicine and high-risk pregnancy at Université Paris-Sud et Sorbonne Université and completed specialized diplomas in advanced laparoscopic surgery and maternal diseases. His ongoing Ph.D. research at Université Libre de Bruxelles focuses on fetal medicine and biostatistics.

Professional Experience🌱

Dr. Badr’s career spans various clinical roles in obstetrics and gynecology, including serving as a research fellow and resident in Fetal Medicine at the Brugmann University Hospital. He has held leadership positions, including Chief Resident roles at multiple hospitals in Lebanon. He has been instrumental in advancing fetal medicine research and clinical practices at Brugmann University Hospital, contributing to the care of high-risk pregnancies and fetal health.

Research Interests🔬

Dr. Badr’s research focuses on maternal-fetal medicine, high-risk pregnancies, prenatal diagnostics, and the impact of COVID-19 on pregnancy outcomes. His scholarly interests include the use of advanced ultrasound techniques for fetal diagnosis, non-invasive prenatal testing, and the development of new clinical guidelines for managing complex pregnancy-related conditions. He has contributed to numerous international studies and publications in fetal medicine.

Author Metrics

Dr. Badr is a recognized contributor to the medical community, with multiple research publications to his name. He holds an ORCID ID (0000-0001-5251-6023) and is actively involved in several international societies such as the International Society for Ultrasound in Obstetrics and Gynecology (ISUOG) and the Fetal Medicine Foundation. His research has been widely cited, and he continues to influence the field through ongoing publications and research projects.

Publications Top Notes 📄

1. Severe Acute Respiratory Syndrome Coronavirus 2 and Pregnancy Outcomes According to Gestational Age at Time of Infection

Authors: DA Badr, O Picone, E Bevilacqua, A Carlin, F Meli, J Sibiude, J Mattern, et al.
Published in: Emerging Infectious Diseases
Volume: 27
Issue: 10
Page: 2535
Year: 2021

2. Uterine Body Placenta Accreta Spectrum: A Detailed Literature Review

Authors: DA Badr, J Al Hassan, GS Wehbe, MK Ramadan
Published in: Placenta
Volume: 95
Pages: 44-52
Year: 2020

3. Added Value of Quantitative Analysis of Diffusion‐Weighted Imaging in Ovarian‐Adnexal Reporting and Data System Magnetic Resonance Imaging

Authors: NA Hottat, DA Badr, C Van Pachterbeke, K Vanden Houte, V Denolin, et al.
Published in: Journal of Magnetic Resonance Imaging
Volume: 56
Issue: 1
Pages: 158-170
Year: 2022

4. Incidence and Risk Factors of Uterine Scar Dehiscence Identified at Elective Repeat Cesarean Delivery: A Case-Control Study

Authors: MK Ramadan, S Kassem, S Itani, L Sinno, S Hussein, R Chahin, DA Badr
Published in: Journal of Clinical Gynecology and Obstetrics
Volume: 7
Issue: 2
Pages: 37-42
Year: 2018

5. HELLP Syndrome, Thrombotic Thrombocytopenic Purpura or Both: Appraising the Complex Association and Proposing a Stepwise Practical Plan for Differential Diagnosis

Authors: MK Ramadan, DA Badr, M Hubeish, S Itani, H Hijazi, A Mogharbil
Published in: Journal of Hematology
Volume: 7
Issue: 1
Page: 32
Year: 2017

Conclusion

Dr. Dominique Badr is a highly qualified and influential figure in the field of Fetal Medicine and Obstetrics, with a wealth of clinical experience, a strong academic foundation, and an impactful research portfolio. His focus on improving maternal and fetal health, particularly through advanced diagnostic techniques and exploring the effects of COVID-19 on pregnancy outcomes, positions him as a leading researcher in this field. While there are opportunities for broader research and public outreach, his strengths in clinical practice, research, and international collaboration make him a compelling candidate for the Best Researcher Award. With continued innovation, collaboration, and mentorship, Dr. Badr’s contributions to maternal-fetal medicine will have a lasting impact on global healthcare.

Ilse Mesters | Prevention | Best Researcher Award

Posted on 09/01/202509/01/2025 by ScienceFatherLeave a Comment

Ms. Ilse Mesters | Prevention | Best Researcher Award

PhD/Assoc. Prof at Maastricht University, Netherlands📖

Dr. Ilse Mesters is an accomplished epidemiologist and Associate Professor at Maastricht University, where she has been a permanent faculty member since 1999. With a Ph.D. in Epidemiology awarded in 1993, Dr. Mesters has dedicated her career to advancing research methodologies and applications in epidemiology. Her work has been widely recognized in academic circles, reflected by an H-index of 36 (Web of Science, February 2024), and a robust presence across major research platforms, including Scopus, Google Scholar, and ResearchGate. She actively contributes to the academic and scientific community through interdisciplinary collaborations and impactful publications.

Profile

Education Background🎓

Dr. Mesters earned her Ph.D. in Epidemiology from Maastricht University in 1993, marking the beginning of her impactful academic journey. Her strong foundation in life sciences has driven her commitment to improving public health through rigorous research and education.

Professional Experience🌱

Dr. Mesters has been a key member of Maastricht University’s Department of Epidemiology for over two decades. As an Associate Professor, she has significantly contributed to teaching, mentoring, and administrative activities. Her research focuses on behavioral determinants of health and public health interventions, aiming to bridge the gap between epidemiological evidence and its practical application in healthcare and policy.

Research Interests🔬

Dr. Mesters’ research interests include:

Epidemiological research methodologies
Behavioral determinants of health outcomes
Public health interventions and their efficacy
Application of epidemiological evidence in policy and healthcare improvements

Author Metrics

Dr. Mesters’ academic contributions are well-recognized globally. She has an H-index of 36 (Web of Science, February 2024), demonstrating the significant impact of her research. Her scholarly work is cataloged under ORCID (0000-0003-0605-6286), Scopus (55883525500), Google Scholar (Profile), and ResearchGate (Profile).

Publications Top Notes 📄

1. Effects and moderators of exercise on quality of life and physical function in patients with cancer: an individual patient data meta-analysis of 34 RCTs

Authors: LM Buffart, J Kalter, MG Sweegers, KS Courneya, RU Newton, I Mesters, et al.
Journal: Cancer Treatment Reviews
Year: 2017
Volume: 52
Pages: 91-104
Citations: 611
DOI: [Link (if available)]
Summary: The paper examines the impact of exercise on improving the quality of life and physical function among cancer patients, using a meta-analysis of 34 randomized controlled trials. It also identifies moderators influencing the effectiveness of these interventions.

2. The general public’s information needs and perceptions regarding hereditary cancer: an application of the Integrated Change Model

Authors: H De Vries, I Mesters, H Van de Steeg, C Honing
Journal: Patient Education and Counseling
Year: 2005
Volume: 56
Issue: 2
Pages: 154-165
Citations: 351
DOI: [Link (if available)]
Summary: This study uses the Integrated Change Model to explore public perceptions and information needs about hereditary cancer, contributing to better public education strategies.

3. Assessment of the inhalation technique in outpatients with asthma or chronic obstructive pulmonary disease using a metered-dose inhaler or dry powder device

Authors: I van Beerendonk, I Mesters, AN Mudde, TD Tan
Journal: Journal of Asthma
Year: 1998
Volume: 35
Issue: 3
Pages: 273-279
Citations: 308
DOI: [Link (if available)]
Summary: This paper evaluates the inhalation techniques of asthma and COPD outpatients, revealing common errors and offering solutions to improve patient outcomes.

4. Measuring information needs among cancer patients

Authors: I Mesters, B van den Borne, M De Boer, J Pruyn
Journal: Patient Education and Counseling
Year: 2001
Volume: 43
Issue: 3
Pages: 255-264
Citations: 239
DOI: [Link (if available)]
Summary: This research focuses on quantifying and addressing the information needs of cancer patients to improve healthcare communication and support services.

5. Dietary change, nutrition education, and chronic obstructive pulmonary disease

Authors: J Brug, A Schols, I Mesters
Journal: Patient Education and Counseling
Year: 2004
Volume: 52
Issue: 3
Pages: 249-257
Citations: 176
DOI: [Link (if available)]
Summary: The study highlights the importance of dietary changes and nutrition education in managing COPD, advocating for personalized nutritional interventions.

Conclusion

Dr. Ilse Mesters’ distinguished career, impactful research, and dedication to improving public health make her an outstanding contender for the Best Researcher Award in the Prevention category. Her robust academic output and interdisciplinary approach highlight her ability to address complex health challenges through evidence-based strategies.

To further solidify her candidacy, Dr. Mesters may consider leveraging advancements in technology and expanding her leadership in global health initiatives. Nonetheless, her proven track record and contributions to epidemiology and prevention research make her a deserving nominee for this award.

Manijeh Emdadi | Artificial Intelligence | Best Researcher Award

Posted on 08/01/202508/01/2025 by ScienceFatherLeave a Comment

Dr. Manijeh Emdadi | Artificial Intelligence | Best Researcher Award

Research Fellow at Islamic Azad University Science and Research Branch, Iran📖

Dr. Manijeh Emdadi is an accomplished Data Scientist and AI Specialist with 8 years of experience in designing, developing, and deploying machine learning models and data-driven solutions. Currently pursuing her Ph.D. in Artificial Intelligence at the Islamic Azad University, Tehran, her research focuses on exploring explainable AI models for healthcare decision support systems. Dr. Emdadi has a robust background in machine learning, neural networks, and deep learning, and she actively collaborates with cross-disciplinary teams to develop innovative AI solutions.

Profile

Education Background🎓

Ph.D. in Artificial Intelligence (In Progress)
Islamic Azad University Science and Research Branch, Tehran, Iran
Research Focus: Exploring Explainable AI Models for Healthcare Decision Support Systems
Master of Science in Data Science / Artificial Intelligence
Islamic Azad University Qazvin Branch, Qazvin, Iran
Thesis: Optimizing Neural Network Architectures for Image Recognition Tasks
Bachelor of Science in Computer Engineering
Iran University of Science and Technology (IUST), Tehran, Iran
Relevant Courses: Advanced Algorithms

Professional Experience🌱

Dr. Emdadi has a strong professional background as a Data Scientist, collaborating with cross-functional teams to integrate predictive analytics into business workflows. Her expertise spans programming in Python, SQL, and Java, as well as working with data science tools such as Pandas, NumPy, Scikit-Learn, TensorFlow, and PyTorch. Additionally, she has experience deploying AI/ML models on cloud platforms like Google Cloud. She also serves as a teaching assistant for graduate-level courses on deep learning, sharing her knowledge and expertise with the next generation of AI professionals.

Research Interests🔬

Dr. Emdadi’s primary research interests lie in the intersection of Artificial Intelligence, Machine Learning, and healthcare applications. She is particularly focused on exploring explainable AI models for decision support systems in healthcare, using machine learning and neural networks to solve complex problems in medical data analysis. Her research also includes advancements in deep learning and reinforcement learning, and she is dedicated to creating innovative AI solutions with real-world applications.

Author Metrics

Dr. Manijeh Emdadi has made significant contributions to the academic field, particularly in the domains of Artificial Intelligence, Machine Learning, and healthcare applications. She has authored several impactful publications in high-ranking journals, focusing on areas such as predictive modeling, explainable AI, and healthcare decision support systems. Notable works include her study on “Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data,” published in Plos One (2024), and her exploration of grid synchronization methods in power converters, published in Electrical Engineering (2023). Additionally, Dr. Emdadi has authored research on key molecular mechanisms in papillary thyroid carcinoma and developed advanced AI models for predicting cancer metastasis. Her work has been well-received in both the academic and industry sectors, reflecting her expertise in applying AI and machine learning techniques to solve real-world challenges. Her research continues to have a notable impact, especially in healthcare, where her AI-driven models aim to advance personalized medicine and decision support systems.

Publications Top Notes 📄

1. “Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data”

Authors: SZ Vahed, SMH Khatibi, YR Saadat, M Emdadi, B Khodaei, MM Alishani, et al.
Journal: Plos One
Volume: 19
Issue: 8
Article Number: e0308531
Year: 2024
DOI: 10.1371/journal.pone.0308531
Summary: This paper applies SHAP (Shapley Additive Explanations) values to identify genes associated with lymph node metastasis in breast cancer patients, utilizing mRNA expression data for enhanced model interpretability.

2. “D-estimation method for grid synchronization of single-phase power converters: analysis, linear modeling, tuning, and comparison with SOGI-PLL”

Authors: H Sepahvand, M Emdadi
Journal: Electrical Engineering
Year: 2023
Summary: The study proposes a D-estimation method for grid synchronization in single-phase power converters. It provides a detailed analysis, linear modeling, tuning methods, and compares the performance with the traditional SOGI-PLL (Second-Order Generalized Integrator Phase-Locked Loop).

3. “Uncovering key molecular mechanisms in the early and late-stage of papillary thyroid carcinoma using association rule mining algorithm”

Authors: SM Hosseiniyan Khatibi, S Zununi Vahed, H Homaei Rad, M Emdadi, et al.
Journal: Plos One
Volume: 18
Issue: 11
Article Number: e0293335
Year: 2023
DOI: 10.1371/journal.pone.0293335
Summary: This research uses association rule mining to explore the molecular mechanisms involved in papillary thyroid carcinoma at various stages. The findings aim to reveal biomarkers for early diagnosis and targeted treatment strategies.

4. “Graph Fuzzy Attention Network Model for Metastasis Prediction of Prostate Cancer Based on mRNA Expression Data”

Journal: International Journal of Fuzzy Systems
Year: 2024
Summary: This paper introduces a Graph Fuzzy Attention Network (GFAN) model for predicting metastasis in prostate cancer using mRNA expression data. The model leverages the strengths of fuzzy logic and graph-based learning for enhanced prediction accuracy.

5. “Load-aware Channel Assignment and Routing in Clustered Multichannel and Multi-radio Mesh Networks”

Authors: M Emdadi, MR Shahsavari, MD TakhtFouladi
Year: Unspecified
Summary: This work discusses the optimization of channel assignment and routing protocols in clustered multi-channel and multi-radio mesh networks, with a focus on load-awareness for efficient resource utilization and network performance.

Conclusion

Dr. Manijeh Emdadi is exceptionally well-suited for the Best Researcher Award due to her pioneering work in artificial intelligence and its application to healthcare decision-making systems. Her strong academic background, innovative research, and commitment to advancing AI for healthcare make her an outstanding candidate. By enhancing collaborations with the industry and expanding her research scope, Dr. Emdadi can continue to build upon her current achievements and make even more significant contributions to both academic and real-world advancements in AI and healthcare.

In summary, Dr. Emdadi’s impressive AI expertise, innovative healthcare solutions, and strong academic contributions strongly align with the qualities sought for the Best Researcher Award.

Hina Najam | Sustainability | Best Researcher Award

Posted on 08/01/202508/01/2025 by ScienceFatherLeave a Comment

Assist. Prof. Dr. Hina Najam | Sustainability | Best Researcher Award

Assistant Professor at Air University Islamabad, Pakistan📖

Hina Najam is an Assistant Professor at the School of Management, Air University, Islamabad, Pakistan. With a keen interest in finance, sustainability, and green technologies, she has authored several impactful publications in top-tier academic journals. Her work addresses the role of green finance, renewable energy, and environmental sustainability in driving economic and societal transformation. Hina holds a Ph.D. in Finance from Iqra University, Islamabad, and has contributed significantly to the academic community through her teaching and research.

Profile

Education Background🎓

Hina Najam has a distinguished educational background in finance, management, and education. She is currently pursuing a Ph.D. in Finance at Iqra University, Islamabad, Pakistan, with a focus on advanced financial management and qualitative research methods. She earned an MBA (1.5 years) from Ghazi University, Dera Ghazi Khan, where she achieved an outstanding CGPA of 3.97/4.00. Prior to her MBA, she completed her BBA (HONS) from Bahauddin Zakariya University, Multan, with a CGPA of 3.77/4.00. Additionally, Hina holds a Bachelor of Education (B.Ed.) from Allama Iqbal Open University, Islamabad, further enhancing her expertise in educational methodologies and teaching. Her academic journey is underpinned by a strong foundation in management, finance, and education, enabling her to contribute to various teaching and research initiatives.

Professional Experience🌱

Hina Najam has a rich professional experience as an educator and researcher, with roles spanning across various prestigious institutions. She currently serves as an Assistant Professor (IPFP Fellow) at the School of Management, Air University, Islamabad, where she teaches courses in financial accounting and business finance. Prior to this, she was a Visiting Faculty Member (VFM) at Bahria Business School, Bahria University, Islamabad, and at the Faculty of Management Sciences, Air University. Hina has also taught at Riphah International University, Islamabad, and PMAS, Arid Agriculture University, Rawalpindi, where she delivered courses in business mathematics, financial accounting, and performance management. In her early career, she was a visiting faculty member at Ghazi University, Dera Ghazi Khan, specializing in corporate governance and corporate finance. Her extensive teaching experience reflects her versatility and dedication to fostering financial literacy and management skills among students.

Research Interests🔬

Hina Najam’s research interests lie at the intersection of finance, sustainability, and environmental management. She is particularly focused on the role of green finance in supporting renewable energy investment and green technological innovation. Her work examines how environmental decentralization, green human capital, and digital finance contribute to sustainable societal development. Hina’s research also explores the relationship between environmental regulations, financial development, and green total factor productivity, particularly in emerging economies. Her work in green finance aims to provide empirical insights and policy recommendations for achieving carbon neutrality and economic sustainability, with a strong emphasis on the role of green finance in the MENA region and Asian economies.

Author Metrics

Hina Najam is a prolific author with numerous contributions to academic literature, focusing on sustainable finance, green technology, and environmental management. Her research has been published in well-regarded journals with high impact factors, such as Environment, Development and Sustainability (IF: 4.9), Geological Journal (IF: 1.8), Sustainable Energy Technologies and Assessments (IF: 8), and Journal of Cleaner Production (IF: 11.07). She has co-authored over 20 papers, many of which explore the relationship between environmental finance, green innovation, and sustainability, with a particular focus on the role of green finance in advancing carbon neutrality and economic sustainability. Her work has received significant attention in both academia and industry, contributing valuable insights into green finance and environmental policy.

Publications Top Notes 📄

1. “Green technological innovation, green finance, and financial development and their role in green total factor productivity: Empirical insights from China”

Authors: C Jiakui, J Abbas, H Najam, J Liu, J Abbas
Journal: Journal of Cleaner Production
Volume: 382
Article: 135131
Year: 2023
Citations: 440
DOI: 10.1016/j.jclepro.2023.135131

2. “Investment in renewable energy and electricity output: Role of green finance, environmental tax, and geopolitical risk: Empirical evidence from China”

Authors: J Abbas, L Wang, SB Belgacem, PS Pawar, H Najam, J Abbas
Journal: Energy
Volume: 269
Article: 126683
Year: 2023
Citations: 242
DOI: 10.1016/j.energy.2023.126683

3. “Role of environmental regulations, green finance, and investment in green technologies in green total factor productivity: Empirical evidence from Asian region”

Authors: L Tong, CJC Jabbour, H Najam, J Abbas
Journal: Journal of Cleaner Production
Volume: 380
Article: 134930
Year: 2022
Citations: 104
DOI: 10.1016/j.jclepro.2022.134930

4. “Achieving financial sustainability through revenue diversification: A green pathway for financial institutions in Asia”

Authors: Z Xie, X Liu, H Najam, Q Fu, J Abbas, U Comite, LM Cismas, A Miculescu
Journal: Sustainability
Volume: 14(6)
Article: 3512
Year: 2022
Citations: 76
DOI: 10.3390/su14063512

5. “Towards green recovery: Can banks achieve financial sustainability through income diversification in ASEAN countries?”

Authors: H Najam, J Abbas, S Álvarez-Otero, E Dogan, MS Sial
Journal: Economic Analysis and Policy
Volume: 76
Pages: 522-533
Year: 2022
Citations: 70
DOI: 10.1016/j.eap.2022.01.002

Conclusion

Dr. Hina Najam’s work epitomizes excellence in the realm of sustainable finance and environmental management. Her pioneering contributions to green finance, renewable energy investment, and sustainable economic development are invaluable, particularly in the context of emerging economies. Her research is characterized by a strong empirical foundation, real-world relevance, and interdisciplinary integration. With continued focus on expanding global collaborations and increasing the practical application of her findings, Dr. Najam has the potential to further enhance the global dialogue on sustainable finance and green technologies.

For these reasons, Dr. Hina Najam is an exemplary candidate for the Best Researcher Award, demonstrating the ability to merge academic excellence with policy-relevant research that can drive societal and economic transformations toward sustainability.

Ezhilazhagan Chenguttuvan | Technological Networks | Best Researcher Award

Posted on 08/01/202508/01/2025 by ScienceFatherLeave a Comment

Assist. Prof. Dr. Ezhilazhagan Chenguttuvan | Technological Networks | Best Researcher Award

Assistant Professor at Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, India📖

Dr. C. Ezhilazhagan is a Senior Member of IEEE with over 17 years of experience in academia and research, specializing in Wireless Communication. He completed his Ph.D. from Anna University, Chennai, in 2022, focusing on Wireless Communication, and has an M.E. in Optical Communication. His career spans various roles, from Lecturer to Assistant Professor (Selection Grade), with a deep commitment to advancing knowledge in communication systems. Dr. Ezhilazhagan has authored over 11 international journals, 16 conferences, and 5 book chapters, along with four patents, contributing significantly to the field. He is also an active member of several professional societies, including IEEE and IET, and has organized numerous seminars, workshops, and FDPs.

Profile

Education Background🎓

Ph.D. in Wireless Communication, Anna University, Chennai (2022)
M.E. in Optical Communication, A.C. College of Engineering & Technology, Karaikudi, Anna University (2007)
B.E. in Electronics and Communication Engineering, M.S.A.J. College of Engineering, Egattur, Anna University (2005)
Diploma in Electronics and Communication Engineering, Chengalvaraya Naicker Polytechnic College, Vepery (2002)

Professional Experience🌱

Dr. Ezhilazhagan’s professional journey includes various esteemed academic positions, having served as a Lecturer and Assistant Professor in prominent institutions like Bharath University, St. Peters Engineering College, Jawahar Engineering College, Dr. N.G.P. Institute of Technology, and Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology. His teaching spans topics in Optical and Wireless Communication, contributing to the academic growth of many students. In addition to teaching, Dr. Ezhilazhagan has held significant roles in academic administration, including NBA, NAAC, and NIRF coordination, and served as an active member of the Institutional Research and Development committee.

Research Interests🔬

Dr. Ezhilazhagan’s research interests are in the areas of Wireless Communication, Optical Communication, Internet of Things (IoT), FPGA-based signal processing, and Artificial Intelligence applications in Communication Systems. He is particularly focused on advancing communication technologies and their application in the evolving landscape of Industry 4.0.

Author Metrics

Dr. Ezhilazhagan has made remarkable contributions to research with over 11 international journal publications, 16 conference papers, and several book chapters. His works are frequently cited, and he serves as a reviewer for numerous SCI and Scopus indexed journals. He has also authored two books and edited another, showcasing his expertise in his field. Dr. Ezhilazhagan continues to make substantial contributions to the field of communication, with ongoing research and publications.

Awards & Achievements

Guest of Honour – Teachers Day Award (2022)
NPTEL Certifications in Industry 4.0, Wireless Communication, AI, and Machine Learning
Active contributor to conferences such as ICCSP’24 and ICCSCT 2023
Reviewer for multiple SCI and Scopus indexed journals

Publications Top Notes 📄

1. Estimating Time and Frequency under Imperfect Channel Knowledge using ECM and SAGE Algorithms in Multi-relay Cooperative Networks

Authors: Ezhilazhagan Chenguttuvan, Lakshmi Prabha Karuppiah, Karuppanan Sakthisudhan
Published in: EURASIP Journal on Wireless Communications and Networking, 2025
DOI: 10.1186/s13638-024-02418-9
Summary: This paper focuses on estimating time and frequency in wireless communication networks, particularly in multi-relay cooperative networks with imperfect channel knowledge. It discusses the application of Expectation Conditional Maximization (ECM) and Space Alternating Generalized Expectation (SAGE) algorithms for better performance in these conditions.

2. Hybrid Machine Learning Approach for Early Stroke Prediction in Elderly People

Authors: P. Divya, K.L. Prabha, B.A. Devi, V.V. Kumar, K. Balaji, C. Ezhilazhagan, et al.
Published in: Communications on Applied Nonlinear Analysis, 2025, Vol. 32(2s), Pages 241-249
Summary: This research proposes a hybrid machine learning approach to predict the early onset of strokes in elderly individuals, enhancing the capacity for early diagnosis and intervention using medical data and machine learning techniques.

3. Mitigating Energy Holes and Enhancing QoS in Delay Tolerant Networks: The EEEHR-M Protocol

Authors: Lakshmi Prabha Karuppiah, Ezhilazhagan Chenguttuvan
Published in: 2024
Summary: This paper addresses the issue of energy holes and Quality of Service (QoS) in delay-tolerant networks (DTNs). It proposes the EEEHR-M protocol as a solution to mitigate energy holes and improve the QoS in these networks, which are often deployed in environments with intermittent connectivity.

4. Human Sound Detection for Multiple Disease Classification using CNN

Authors: Ezhilazhagan Chenguttuvan, Lakshmi Prabha, Sakthisudhan Karupanan
Presented at: 9th International Conference on ICT for Sustainable Development, 2024
Summary: This conference paper explores the use of Convolutional Neural Networks (CNN) to detect human sounds as part of a system for classifying multiple diseases, potentially aiding in non-invasive diagnostics and monitoring of health conditions.

5. Energy Hole Problem in Wireless Sensor Networks: A Research Review

Author: Lakshmi Prabha, Ezhilazhagan Chenguttuvan
Published in: Futuristic Trends in Network & Communication Technologies, 2024, Vol. 3
Summary: This research review paper examines the energy hole problem in wireless sensor networks (WSNs) and offers insights into strategies and approaches for mitigating this issue, which impacts the performance and lifespan of WSNs.

Conclusion

Dr. Ezhilazhagan Chenguttuvan is undoubtedly a highly deserving candidate for the Best Researcher Award. His extensive contributions in the fields of wireless and optical communication, along with his ability to integrate emerging technologies into his work, make him a leader in his field. His high-quality publications, leadership in teaching, and active participation in the academic community underscore his dedication to advancing knowledge and research in communication systems.

To further enhance his contributions, expanding international collaborations, diversifying his research scope, and focusing on translational research will enable him to address future challenges and make an even greater impact on both the academic and industrial fronts. With these enhancements, Dr. Chenguttuvan has the potential to remain at the forefront of his field, pushing the boundaries of communication technologies and their applications in the digital age.

Zekang Liu | Sign Language Recognition | Best Researcher Award

Posted on 08/01/202508/01/2025 by ScienceFatherLeave a Comment

Mr. Zekang Liu | Sign Language Recognition | Best Researcher Award

Eng.D Student at Tianjin University, China📖

Liu Zekang is a researcher and graduate student at Tianjin University, specializing in Electronic Engineering. With a background in Software Engineering, Liu has made significant contributions to the fields of artificial intelligence, Internet of Things (IoT), and vehicle detection technologies. He has been recognized for his academic achievements with awards such as the Third Prize at the National Forum on Innovation, Informatization, and Artificial Intelligence Development for Postdoctoral Researchers in 2021, and the Excellent Student Award from Tianjin University in 2023.

Profile

Education Background🎓

Liu Zekang’s educational journey began with a Bachelor’s degree in Software Engineering from Hebei University of Economics and Business, which he completed in 2017. He then pursued a Master’s degree in Software Engineering at Tianjin Normal University, graduating in 2019. Currently, Liu is a Ph.D. candidate in Electronic Engineering at Tianjin University, where he has been advancing his research since 2020. His academic background combines a solid foundation in software engineering with specialized expertise in electronic engineering, enabling him to explore and contribute to cutting-edge advancements in artificial intelligence, IoT, and real-time recognition systems.

Professional Experience🌱

Liu Zekang has actively engaged in research projects funded by the Tianjin Natural Science Foundation, where he contributed to the development of vehicle detection technology using smartphones and conducted significant studies in context-aware technologies within IoT environments. Additionally, he has worked on designing accessible communication systems leveraging key technologies. Liu’s research experience spans multiple aspects of intelligent transportation, sign language recognition, and deep learning applications.

Research Interests🔬

Liu’s research interests lie in the application of artificial intelligence to real-time recognition systems, including vehicle detection, sign language recognition, and IoT technologies. His focus is on leveraging convolutional neural networks (CNNs) and self-emphasizing networks to enhance real-time systems, with particular emphasis on applications that support accessibility, including continuous sign language recognition and background-independent computing.

Author Metrics

Liu has contributed to multiple high-impact publications in prestigious journals and conferences:

Liu Zekang, Sun Huazhi, Ma Chunmei, et al. “Vehicle Recognition Model Based on Convolutional Neural Network with Multi-feature Fusion,” Computer Science, 2019.
Hu L, Gao L, Liu Z, et al. “Self-emphasizing network for continuous sign language recognition,” Proceedings of the AAAI Conference on Artificial Intelligence, 2023.
Hu L, Gao L, Liu Z, et al. “Continuous Sign Language Recognition with Correlation Network,” IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023.
Liu Z, Feng W, Gao L, et al. “DBL-SC: background-independent sign language recognition based on spatial channel separation computation,” The Visual Computer, 2025.

Liu’s contributions to the field are positioned at the intersection of AI, accessibility technologies, and real-time processing, pushing the boundaries of what can be achieved through innovative computing.

Publications Top Notes 📄

Scalable Frame Resolution for Efficient Continuous Sign Language Recognition
Authors: Hu, L., Gao, L., Liu, Z., Feng, W.
Journal: Pattern Recognition
Year: 2024
Volume: 145
Article Number: 109903
Citations: 5
This article discusses scalable frame resolution techniques for enhancing the efficiency of continuous sign language recognition.
AdaBrowse: Adaptive Video Browser for Efficient Continuous Sign Language Recognition
Authors: Hu, L., Gao, L., Liu, Z., Pun, C.-M., Feng, W.
Conference: Proceedings of the 31st ACM International Conference on Multimedia (MM 2023)
Year: 2023
Pages: 709–718
Citations: 7
This conference paper presents “AdaBrowse,” a system designed for efficient sign language recognition using an adaptive video browsing technique.
Self-Emphasizing Network for Continuous Sign Language Recognition
Authors: Hu, L., Gao, L., Liu, Z., Feng, W.
Conference: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI 2023)
Year: 2023
Volume: 37
Issue: 1
Pages: 854–862
Citations: 36
This paper introduces a self-emphasizing network aimed at improving continuous sign language recognition through self-attention mechanisms.
Temporal Lift Pooling for Continuous Sign Language Recognition
Authors: Hu, L., Gao, L., Liu, Z., Feng, W.
Conference: Lecture Notes in Computer Science (LNCS), 13695 LNCS
Year: 2022
Pages: 511–527
Citations: 32
This paper discusses “Temporal Lift Pooling,” a technique designed to enhance feature extraction for continuous sign language recognition.
RNN-Transducer Based Chinese Sign Language Recognition
Authors: Gao, L., Li, H., Liu, Z., Wan, L., Feng, W.
Journal: Neurocomputing
Year: 2021
Volume: 434
Pages: 45–54
Citations: 44
This article presents the use of RNN-Transducer models for the recognition of Chinese sign language, integrating both visual and acoustic data.

Conclusion

Liu Zekang is undoubtedly a highly deserving candidate for the Best Researcher Award. His innovative contributions to AI, particularly in continuous sign language recognition, his interdisciplinary expertise, and his commitment to addressing societal challenges through technology, set him apart as a leading researcher in his field. His ability to publish in high-impact venues, coupled with the recognition he has already received, highlights his potential for further success.

With a bit more emphasis on broadening his research scope and engaging more with industry, Liu could make even greater strides in creating real-world applications that benefit society. His research trajectory suggests that he will continue to make significant contributions, making him an excellent nominee for this prestigious award.

Diana Patricia Molina Delgado | Technological Networks | Best Researcher Award

Posted on 08/01/202508/01/2025 by ScienceFatherLeave a Comment

Dr. Diana Patricia Molina Delgado | Technological Networks | Best Researcher Award

Innovation Technician at Federació de Cooperatives Agràries de Catalunya (FCAC), Spain📖

Diana Molina Delgado is an experienced professional focused on optimizing organizations and processes through innovative, sustainable, and practical solutions. With a background in agricultural sciences and business administration, she has worked in various roles, from postharvest management to research and development in the agribusiness sector. Diana has a strong commitment to sustainability and cooperation, and she has participated in numerous international projects and congresses.

Profile

Education Background🎓

Master in Business Administration (MBA) – IMF Business School (2020-2023), specializing in business administration principles in the agrifood sector.
Ph.D. in Agricultural Science and Food Technology – Universitat de Lleida (2001-2008), focusing on optimizing harvest dates and maintaining apple quality using non-destructive techniques.
Agricultural Engineer – Universidad Nacional de Colombia (1991-1998), where she worked on optimizing agricultural processes.
Social Science Bachelor – Universidad Distrital (1987-1994), focusing on evaluating social processes.

Professional Experience🌱

Federació de Cooperatives Agràries de Catalunya (July 2021-Present): Leading projects and managing grants while supporting R&D and innovation for cooperatives.
IRTA – Mas Badia (Sept 2017-Dec 2019): Postharvest Management Advisor, focusing on postharvest process optimization for the apple industry in Girona and coordinating Agrofresh® application services.
ACTEL GRUP (March 2009-Aug 2017): Fruit Production Advisor, advising producers on technical and administrative management in fruit production.
Ecole Supérieure d’Agriculture d’Angers (Jan-Jun 2007): Invited Researcher, conducting consumer quality assessment in French apple varieties.
Universitat de Lleida / IRTA (Sept 2004-Dec 2008): PhD Researcher, optimizing postharvest protocols and transferring technology to the agribusiness sector.
Jardiland (Oct 2001-Aug 2004): Greenhouse Manager, managing staff and overseeing seasonal marketing and stock control.
Universidad Central (Oct 2000-Feb 2001): Associated Professor in Business Administration, teaching Mathematics and Statistics.

Research Interests🔬

Diana’s research focuses on optimizing agricultural processes, particularly in the agrifood sector, with an emphasis on postharvest technology, quality evaluation, and sustainability. Her work involves non-destructive techniques for quality assessment, with applications in fruit and vegetable sectors, aiming to improve product quality, storage, and consumer satisfaction.

Author Metrics

Diana has contributed significantly to scientific literature with over 17 publications, including articles in journals such as Biosystems Engineering, Food Science and Technology International, and Journal of the Science of Food and Agriculture. Her work addresses advancements in postharvest technology, non-destructive techniques for measuring fruit quality, and consumer preference studies, among other topics.

Publications Top Notes 📄

1. Antioxidant Activity Determines On-Tree Maturation in ‘Golden Smootheé’ Apples

Authors: Molina-Delgado, D., Larrigaudière, C., Recasens, I.
Journal: Journal of the Science of Food and Agriculture
Year: 2009
Volume: 89
Issue: 7
Pages: 1207-1212
DOI: 10.1002/jsfa.3529
Citations: 11
Summary: This paper examines how antioxidant activity impacts the maturation process of ‘Golden Smootheé’ apples, with an emphasis on postharvest quality.

2. Relationship Between Acoustic Firmness and Magness Taylor Firmness in Royal Gala and Golden Smoothee Apples

Authors: Molina-Delgado, D., Alegre, S., Puy, J., Recasens, I.
Journal: Food Science and Technology International
Year: 2009
Volume: 15
Issue: 1
Pages: 31-40
DOI: 10.1177/1082013208101797
Citations: 21
Summary: This study explores the relationship between acoustic firmness and the traditional Magness Taylor test for firmness in apples, offering insight into non-destructive testing methods.

3. Addressing Potential Sources of Variation in Several Non-Destructive Techniques for Measuring Firmness in Apples

Authors: Molina-Delgado, D., Alegre, S., Barreiro, P., Ruiz-Altisent, M., Recasens, I.
Journal: Biosystems Engineering
Year: 2009
Volume: 104
Issue: 1
Pages: 33-46
DOI: 10.1016/j.biosystemseng.2009.01.004
Citations: 27
Summary: The paper addresses the sources of variation found in non-destructive firmness measurement techniques, focusing on improving the reliability and accuracy of these methods.

4. A Multi-Stakeholder Perspective on the Use of Digital Technologies in European Organic and Agroecological Farming Systems

Authors: Giagnocavo, C., Duque-Acevedo, M., Terán-Yépez, E., Van Nieuwenhove, T., Volpi, I.
Journal: Technology in Society
Year: 2025
Volume: 81
Article Number: 102763
DOI: Link is disabled (currently inaccessible)
Citations: 0 (as of now)
Type: Open Access Article
Summary: This article examines the use of digital technologies in organic and agroecological farming systems across Europe, exploring the diverse perspectives of various stakeholders involved in this transformative approach.

Conclusion

Dr. Diana Molina Delgado exemplifies the qualities of an outstanding researcher. Her contributions to the optimization of agricultural processes, especially in postharvest technology, have practical implications that benefit the agrifood industry, sustainability efforts, and consumer satisfaction. With a clear commitment to advancing innovative solutions, her work stands out as both impactful and practical. The areas for improvement highlighted are relatively minor in comparison to her extensive body of work and accomplishments.

Given her expertise, innovative contributions, and commitment to sustainability, I strongly recommend Dr. Diana Molina Delgado for the Best Researcher Award. Her continued work has the potential to shape the future of agricultural sciences and sustainability practices globally.

Yanyan Liu | Topic model | Best Researcher Award

Posted on 08/01/202508/01/2025 by ScienceFatherLeave a Comment

Ms. Yanyan Liu | Topic model | Best Researcher Award

PHD Candidate at University of Macau, China📖

Yanyan Liu is a dedicated researcher specializing in Data Mining with expertise in neural topic modeling, natural language processing, and recommendation systems. She is currently pursuing her Ph.D. in Computer Science at the University of Macau, focusing on developing innovative machine-learning frameworks to enhance topic modeling and social influence learning. With a strong academic foundation and a passion for advancing knowledge in her field, she has published in esteemed journals and conferences, including Knowledge-Based Systems and ACM CIKM.

Profile