Kothai Ganesan | Computer Vision | Best Researcher Award

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Assist. Prof. Dr. Kothai Ganesan | Computer Vision | Best Researcher Award

Assistant Professor at KPR Institute of Engineering and Technology, India

Dr. Kothai Ganesan is an Assistant Professor in Computer Science and Engineering (Artificial Intelligence and Machine Learning) at KPR Institute of Engineering and Technology. She holds a Bachelor’s degree and Master’s degree in Engineering from Anna University and a Ph.D. from SRM Institute of Science and Technology, with research focusing on Intelligent Transport Systems, traffic prediction, and secure data transmission. Her published work includes studies in vehicular networks, traffic congestion, and security protocols, alongside ongoing research in medical imaging, AI-enhanced diagnostic tools, and image processing. A recognized mentor and department coordinator, Dr. Kothai integrates modern tools like Docker into her curriculum, advancing industry-aligned education. Her contributions have been acknowledged in journals, conferences, and professional memberships, including IEEE Computational Intelligence Society.

Publication Profile : 

Scopus

 

🎓 Educational Background :

Dr. Kothai Ganesan is an accomplished Assistant Professor in the Computer Science and Engineering (Artificial Intelligence and Machine Learning) department at KPR Institute of Engineering and Technology. Her academic journey began with a Bachelor’s degree in Computer Science and Engineering from Anna University (2012–2016), followed by a Master’s in the same field, earned with first-class distinction at Anna University (2016–2018). Pursuing her passion for advanced research, Dr. Ganesan completed her Ph.D. in November 2023 at SRM Institute of Science and Technology, where her research centered on Intelligent Transport Systems, with a particular focus on traffic prediction, congestion avoidance, and secure data transmission, all aimed at improving urban mobility.

💼 Professional Experience :

Professionally, Dr. Ganesan has contributed significantly to the field of AI-driven transport systems, publishing extensively on vehicular ad hoc networks (VANETs) and innovative machine learning techniques. Her research outputs include collision prediction and secure communication protocols, enhancing safety in smart cities. She has also expanded her focus into medical AI, exploring Alzheimer’s diagnosis, pediatric epilepsy recognition, and cancer detection using optimized learning models. Alongside her research, Dr. Ganesan is an active mentor, guiding student-led projects in machine learning and artificial intelligence. As a dedicated faculty member, she serves as the IQAC Coordinator, Exam Cell Coordinator, Autonomous Coordinator, and R&D Coordinator, furthering the program’s reputation through academic rigor and practical industry integration. 📚💡

📚 Research Interests : 

Her current research interests are broad, covering deep learning, machine learning, computer vision, and natural language processing. Dr. Ganesan’s work has gained her recognition in prestigious journals and conferences, and she actively participates in the IEEE Computational Intelligence Society as a Faculty Advisor. As a reviewer for leading journals, she contributes her expertise to the scholarly community. Dr. Ganesan’s unique blend of academic insight, mentorship, and professional innovation showcases her commitment to advancing AI and machine learning for impactful, real-world applications. 🌟

📝 Publication Top Notes :

  1. Ganesan, K., & [Co-authors, if applicable]. (2021). A New Hybrid Deep Learning Algorithm for Prediction of Wide Traffic Congestion in Smart Cities. Wireless Communications and Mobile Computing, 2021, Article ID 5583874, 13 pages. https://doi.org/10.1155/2021/5583874.
  2. Ganesan, K., & [Co-authors, if applicable]. (2020). Performance Analysis of Stationary and Deterministic AODV Model. International Journal of Interactive Mobile Technologies (IJIM), 14(17), 33–44.
  3. Ganesan, K., & [Co-authors, if applicable]. (2022). IoT-Based Automatic SOP Adoption in Pandemic Scenario. International Journal of High Technology Letters, June 2022.
  4. Ganesan, K., & [Co-authors, if applicable]. (2024). A Hybrid CNN-GRU based Intrusion Detection System for Secure Communication in Vehicular Adhoc Network. Information Security Journal, Taylor & Francis, June 2024.

 

 

 

Emad Kazemzadeh | Energy Economics | Best Researcher Award

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Dr. Emad Kazemzadeh | Energy Economics | Best Researcher Award

Researcher at Ferdowsi University of Mashhad, Iran

🌍 Economist | 📚 Educator | 🔬 Researcher
Emad Kazemzadeh is a passionate economist specializing in energy and environmental issues. With a solid academic background and extensive teaching and research experience, he focuses on understanding the interplay between economic activities and ecological impacts. He is dedicated to advancing sustainable practices through rigorous research and education.

Publication Profile : 

Orcid

 

🎓 Educational Background :

Emad Kazemzadeh holds a Post-Doctoral position in Energy Economics from Ferdowsi University of Mashhad (2022-2023) and a Ph.D. in Economics focusing on Energy-International from the same institution (2016-2022). He completed a research course at the University of Coimbra, Portugal, and holds an M.Sc. in Economics from Sistan and Baluchestan University (2012) and a B.Sc. in Mathematics from the University of Farhangian (2008).

💼 Professional Experience :

Emad has a robust teaching background, currently instructing B.Sc. courses at Ferdowsi University, including Microeconomics and Principles of Economics. His previous experience includes teaching Macroeconomics and Microeconomics at Payam-e-Noor University. He has also served as a research assistant for several esteemed professors in the field of economics. Emad has published extensively in high-impact journals, contributing to topics like ecological footprints, energy consumption, and the effects of economic complexity on environmental issues.

📚 Research Interests : 

His research interests span Energy Economics, Environmental Economics, Behavioral Economics, Health Economics, International Economics, Econometrics, and Development Economics.

📝 Publication Top Notes :

  1. Kazemzadeh, E., Fuinhas, J. A., Salehnia, N., Koengkan, M., & Silva, N. (2023). Assessing influential factors for ecological footprints: A complex solution approach. Journal of Cleaner Production, 137574. https://doi.org/10.1016/j.jclepro.2023.137574.
  2. Kazemzadeh, E., Lotfalipour, M. R., Shirazi, M., & Sargolzaie, A. (2023). Heterogeneous effects of energy consumption structure on ecological footprint. Environmental Science and Pollution Research, 30(19), 55884-55904. https://doi.org/10.1007/s11356-023-26118-x.
  3. Kazemzadeh, E., Fuinhas, J. A., Salehnia, N., Koengkan, M., & Silva, N. (2023). Exploring necessary and sufficient conditions for carbon emission intensity: A comparative analysis. Environmental Science and Pollution Research, 30(38). https://doi.org/10.1007/s11356-023-29260-8.
  4. Koengkan, M., Kazemzadeh, E., Fuinhas, J. A., & Tash, M. N. S. (2023). Heterogeneous impact of eco-innovation on premature deaths resulting from indoor and outdoor air pollution: Empirical evidence from EU29 countries. Environmental Science and Pollution Research, 30(1), 2298-2314. https://doi.org/10.1007/s11356-022-22423-z.
  5. Kazemzadeh, E., Fuinhas, J. A., Radulescu, M., Koengkan, M., & Silva, N. (2023). The heterogeneous impact of environmental policy stringency on premature indoor and outdoor deaths from air pollution in the G7 countries: Do economic complexity and green innovation matter? Atmospheric Pollution Research, 14(2), 101664. https://doi.org/10.1016/j.apr.2023.101664.
  6. Kazemzadeh, E., Fuinhas, J. A., Salehnia, N., Koengkan, M., Shirazi, M., & Osmani, F. (2022). Factors driving CO₂ emissions: The role of energy transition and brain drain. Environment, Development and Sustainability, 1-28. https://doi.org/10.1007/s10668-022-02780-y.
  7. Kazemzadeh, E., Koengkan, M., & Fuinhas, J. A. (2022). Effect of battery-electric and plug-in hybrid electric vehicles on PM2.5 emissions in 29 European countries. Sustainability, 14(4), 2188. https://doi.org/10.3390/su14042188.
  8. Kazemzadeh, E., Fuinhas, J. A., Koengkan, M., & Osmani, F. (2022). The heterogeneous effect of economic complexity and export quality on the ecological footprint: A two-step club convergence and panel quantile regression approach. Sustainability, 14(18), 11153. https://doi.org/10.3390/su141811153.
  9. Kazemzadeh, E., Koengkan, M., & Fuinhas, J. A. (2022). Effect of battery-electric and plug-in hybrid electric vehicles on PM2.5 emissions in 29 European countries. Sustainability, 14(4), 2188. https://doi.org/10.3390/su14042188.
  10. Kazemzadeh, E., Fuinhas, J. A., Shirazi, M., Koengkan, M., & Silva, N. (2023). Does economic complexity increase energy intensity? Energy Efficiency, 16(4), 1-22. https://doi.org/10.1007/s12053-023-10104-w.
  11. Salari, T. E., Roumiani, A., & Kazemzadeh, E. (2021). Globalization, renewable energy consumption, and agricultural production impacts on ecological footprint in emerging countries: Using quantile regression approach. Environmental Science and Pollution Research, 28(36), 49627-49641. https://doi.org/10.1007/s11356-021-14204-x.
  12. Koengkan, M., Fuinhas, J. A., Kazemzadeh, E., Alavijeh, N. K., & de Araujo, S. J. (2022). The impact of renewable energy policies on deaths from outdoor and indoor air pollution: Empirical evidence from Latin American and Caribbean countries. Energy, 245, 123209. https://doi.org/10.1016/j.energy.2022.123209.
  13. Koengkan, M., Fuinhas, J. A., Osmani, F., Kazemzadeh, E., Auza, A., Alavijeh, N. K., & Teixeira, M. (2022). Do financial and fiscal incentive policies increase the energy efficiency ratings in residential properties? Empirical evidence from Portugal. Energy, 241, 122895. https://doi.org/10.1016/j.energy.2021.122895.
  14. Silva, N., Fuinhas, J. A., Koengkan, M., & Kazemzadeh, E. (2023). What are the causal conditions that lead to high or low environmental performance? A worldwide assessment. Environmental Impact Assessment Review, 107342. https://doi.org/10.1016/j.eiar.2023.107342.
  15. Silva, N., Fuinhas, J. A., Koengkan, M., Kazemzadeh, E., & Kaymaz, V. (2023). Renewable energy deployment in Europe: Do politics matter? Environment, Development and Sustainability, 1-34. https://doi.org/10.1007/s10668-023-03839-0.

 

 

 

 

Tianyi Yan | Computational Neuroscience | Best Researcher Award

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Prof. Dr. Tianyi Yan | Computational Neuroscience | Best Researcher Award

Vice Dean at School of Medical Technology, Beijing Institute of Technology, China

Tianyi Yan is a prominent researcher and educator in biomedical engineering, dedicated to exploring innovative solutions for brain health and cognitive enhancement. With numerous accolades and a rich publication record, he is shaping the future of neuroscience and technology integration. 🧠✨

Publication Profile : 

Scopus

 

🎓 Educational Background :

Tianyi Yan obtained a PhD in Biomedical Engineering from Okayama University, Japan, in 2004. He also holds an MSc in Biomedical Engineering from Kagawa University (2003) and a BSc in Electronic Engineering from Changchun University of Science and Technology, China (2001).

💼 Professional Experience :

Currently, he serves as the Vice Dean of the School of Medical Technology and the School of Life Sciences at the Beijing Institute of Technology (BIT) since March 2020. He has been a Professor at BIT since 2016 and the Director of the Department of Biomedical Engineering since July 2018. His academic journey began as a Lecturer at BIT in 2011, followed by a post-doctoral position at Okayama University.

📚 Research Interests : 

His research spans several areas, including Brain Science and Neuronal Engineering, Cognitive Neuroscience, Brain-Computer Interfaces, and non-invasive neuromodulation for brain disease diagnosis. He focuses on developing algorithms to study neural degenerative diseases, designing wearable devices for neural feedback, and advancing brain-controlled technologies.

📝 Publication Top Notes :

  1. Y. Yang, Q. Fan, T. Yan, J. Pei, and G. Li, “Network Group Partition and Core Placement Optimization for Neuromorphic Multi-Core and Multi-Chip Systems,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2024.
  2. Y. Huang, Y. Li, Y. Yuan, X. Zhang, W. Yan, T. Li, Y. Niu, M. Xu, T. Yan, X. Li, D. Li, J. Xiang, B. Wang, and T. Yan, “Beta-informativeness-diffusion multilayer graph embedding for brain network analysis,” Frontiers in Neuroscience, vol. 18, no. 1303741, 2024.
  3. S. Liu, M. Liu, D. Zhang, Z. Ming, Z. Liu, Q. Chen, L. Ma, J. Luo, J. Zhang, D. Suo, G. Pei, and T. Yan, “Brain-Controlled Hand Exoskeleton Based on Augmented Reality-Fused Stimulus Paradigm,” IEEE Journal of Biomedical and Health Informatics, 2024.
  4. S. Liu, Z. Ming, M. Liu, D. Zhang, Z. Liu, Q. Chen, L. Ma, J. Luo, D. Suo, J. Zhang, and T. Yan, “Remote-Oriented Brain-Controlled Unmanned Aerial Vehicle for IoT,” IEEE Internet of Things Journal, 2024.
  5. J. Wu, L. Ma, D. Luo, Z. Jin, L. Wang, L. Wang, T. Li, J. Zhang, T. Liu, D. Lv, T. Yan, and B. Fang, “Functional and structural gradients reveal atypical hierarchical organization of Parkinson’s disease,” Human Brain Mapping, vol. 45, no. 4, e26647, 2024.
  6. J. Lu, T. Yan, L. Yang, X. Zhang, J. Li, D. Li, J. Xiang, and B. Wang, “Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability,” NeuroImage, vol. 295, 2024, pp. 120651.
  7. M. Yao, O. Richter, G. Zhao, N. Qiao, Y. Xing, D. Wang, T. Hu, W. Fang, T. Demirci, M.D. Marchi, L. Deng, T. Yan, C. Nielsen, S. Sheik, C. Wu, Y. Tian, B. Xu, and G. Li, “Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip,” Nature Communications, vol. 15, no. 1, p. 4464, 2024.
  8. G. Wang, N. Jiang, Y. Ma, T. Liu, D. Chen, J. Wu, G. Li, D. Liang, and T. Yan, “Connectional-style-guided contextual representation learning for brain disease diagnosis,” Neural Networks, vol. 175, 2024, pp. 106296.
  9. G. Wang, N. Jiang, Y. Ma, D. Suo, T. Liu, S. Funahashi, and T. Yan, “Using a deep generation network reveals neuroanatomical specificity in hemispheres,” Patterns, vol. 5, no. 4, 2024.
  10. G. Wang, N. Jiang, T. Liu, L. Wang, D. Suo, D. Chen, S. Funahashi, and T. Yan, “Using unsupervised capsule neural network reveal spatial representations in the human brain,” Human Brain Mapping, vol. 45, no. 5, e26573, 2024.
  11. L. Wang, S. Li, L. Gong, Z. Zheng, Y. Chen, G. Chen, and T. Yan, “Right parietal repetitive transcranial magnetic stimulation in obsessive-compulsive disorder: A pilot study,” Asian Journal of Psychiatry, vol. 93, Mar. 2024, pp. 103902.
  12. T. Li, T. Liu, J. Zhang, Y. Ma, G. Wang, D. Suo, B. Yang, X. Wang, S. Funahashi, K. Zhang, B. Fang, and T. Yan, “Neurovascular coupling dysfunction of visual network organization in Parkinson’s disease,” Neurobiology of Disease, 2023, pp. 106323.
  13. J. Zhang, Y. Yang, T. Liu, Z. Shi, G. Pei, L. Wang, J. Wu, S. Funahashi, D. Suo, C. Wang, and T. Yan, “Functional connectivity in people at clinical and familial high risk for schizophrenia,” Psychiatry Research, vol. 328, 2023, pp. 115464.
  14. T. Yan, G. Wang, T. Liu, G. Li, C. Wang, and D. Suo, G. Pei, “Effects of Microstate Dynamic Brain Networks Disruption in Different Stages of Schizophrenia,” IEEE Transactions on Neural Systems & Rehabilitation Engineering, vol. 31, 2023, pp. 2688-2697.
  15. T. Li, L. Wang, Z. Piao, K. Chen, X. Yu, Q. Wen, D. Suo, C. Zhang, S. Funahashi, G. Pei, B. Fang, and T. Yan, “Altered Neurovascular Coupling for Multidisciplinary Intensive Rehabilitation in Parkinson’s Disease,” The Journal of Neuroscience, vol. 1, no. 1, 2023, pp. 1204-1222.

 

 

 

Khalil Farhadi | Nanochemistry | Best Researcher Award

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Prof. Dr. Khalil Farhadi | Nanochemistry | Best Researcher Award

Electrochemistry of Urmia university, Iran

Prof. Dr. Khalil Farhadi 🎓🔬 is an expert in Analytical Chemistry with a keen interest in nanochemistry, electrochemical sensors, and environmental pollution analysis. Based at Urmia University, he combines rigorous research with practical applications in electrochemistry and bioanalysis. Recognized internationally for his innovative work, Prof. Farhadi is committed to advancing analytical methods for real-world solutions in environmental and health sciences. 🌍⚛️

Publication Profile : 

Scopus

 

🎓 Educational Background :

Prof. Dr. Khalil Farhadi is a distinguished professor in the field of Analytical Chemistry, currently holding a position at the Department of Analytical Chemistry, Faculty of Chemistry, Urmia University in Iran. He completed his Bachelor’s degree in Chemistry at Urmia University in 1990, followed by a Master’s degree in Analytical Chemistry from Tabriz University in 1995, and earned his Ph.D. in Analytical Chemistry from Razi University in 2000. His doctoral research focused on the electrochemical study of ketoconazole, phenothiazine, and anthraquinone derivatives, showcasing his early interest in electrochemical analysis.

💼 Professional Experience :

Over his academic career, Prof. Farhadi has advanced from Assistant Professor (2000) to Associate Professor (2003), and was promoted to Professor in 2008. He has an extensive background in nanochemistry, electrochemistry, and bioanalytical methods, and has made significant contributions to environmental pollution analysis and food analysis. His work in electrochemistry includes electrosynthesis, industrial electrochemistry, and corrosion studies, with specialized applications in sensors, biosensors, and modified electrodes. Prof. Farhadi has received notable recognition for his research, including being named a selected young scientist by IUPAC in Tokyo, Japan (2001), and earning a Gold Medal Award of Merit for his work on Diesel 5+ Fuel Additive at INPEX in Pittsburgh, USA (2012). Prof. Farhadi has published numerous papers on topics such as potentiometric studies, electrochemical behavior of pharmaceutical compounds, and voltammetric determination of analytes in pharmaceutical and biological samples, establishing himself as an influential researcher in the field of Analytical Chemistry.

📚 Research Interests : 

  • Nanochemistry, Nanotechnology, and Nanobiotechnology
  • Electrochemistry (Electrosynthesis, Corrosion, Sensors, Biosensors, Modified Electrodes)
  • Environmental Pollution Analysis
  • Separation Methods (Chromatography, Solid-Phase Extraction, Transport Methods)
  • Bioanalytical and Bioelectroanalytical Methods
  • Food Analysis

📝 Publication Top Notes :

  1. Pournaghi-Azar, M.H., & Farhadi, K. (1995). Potentiometric Study of Reaction Between Periodate and Iodide as Their Tetrabutylammonium Salts in Chloroform. Application to the Determination of Iodide and Potentiometric Detection of End Points in Acid-Base Titrations in Chloroform. Talanta, 42, 345.
  2. Pournaghi-Azar, M.H., & Farhadi, K. (1997). Potentiometric Study of Reaction Between Tetrabutylammonium Periodate and Phenothiazine in Chloroform. Talanta, 44, 1773.
  3. Shamsipur, M., & Farhadi, K. (2000). Electrochemical Behavior and Determination of Ketoconazole from Pharmaceutical Preparations. Electroanalysis, 12, 429.
  4. Farhadi, K., & Shamsipur, M. (2000). Separation Study of Palladium Through a Bulk Liquid Membrane Containing Thioridazine.HCl and Oleic Acid. Separation Science and Technology, 35, 859.
  5. Shamsipur, M., & Farhadi, K. (2000). Adsorptive Stripping Voltammetric Determination of Ketoconazole in Pharmaceutical Preparations and Urine Using Carbon Paste Electrodes. Analyst, 125, 1639.
  6. Shamsipur, M., & Farhadi, K. (2001). Electroxidation of Ketoconazole in Acetonitrile and Its Determination in Pharmaceutical Preparations. Chemical Analysis (Warsaw), 46, 387.
  7. Farhadi, K., & Shamsipur, M. (1999). Polarographic Study of Tl(I) Complexes with Large Crown Ethers in Binary Acetonitrile-Water Mixtures. Journal of the Chinese Chemical Society, 46, 893.
  8. Farhadi, K., & Maleki, R. (2002). Clotrimazole-Triiodide Ion Association as an Ion Exchanger for a Triiodide Ion-Selective Electrode. Analytical Sciences, 18, 133.
  9. Farhadi, K., & Maleki, R. (2002). Triiodide Ion-Selective Polymeric Membrane Electrode Based on a Ketoconazole-Triiodide Ion Pair. Electroanalysis, 11, 760.
  10. Farhadi, K., & Shamsipur, M. (2001). Effect of Surfactants on the AC Voltammetry of 9,10-Anthraquinone Derivatives at Glassy Carbon Electrode and Its Utilization for the Determination of Anthraquinones and Cationic Surfactants. Analytical Sciences, 17, 1733.
  11. Farhadi, K., & Maleki, R. (2001). A New Spectrophotometric Method for the Determination of Ketoconazole Based on the Oxidation Reactions. Analytical Sciences, 17, 867.
  12. Farhadi, K., & Maleki, R. (2002). Triiodide Ion and Alizarin Red S as Two New Reagents for the Determination of Clotrimazole and Ketoconazole. Journal of Pharmaceutical and Biomedical Analysis, 30, 1023.
  13. Farhadi, K., Ghadamghahi, S., Maleki, R., & Salek Asghari, F. (2002). Spectrophotometric Determination of Selected Antibiotics Using Prussian Blue Reaction. Journal of the Chinese Chemical Society, 49, 993.
  14. Farhadi, K., Sheikhloei Bonab, H., Maleki, R., Shamsipur, M., & Shargi, H. (2002). Tetrachlorophenylporphyrinato Mn(III) as a New Ionophore for a Coated Graphite Triiodide Ion-Selective Electrode. Journal of the Chinese Chemical Society, 49, 861.
  15. Farhadi, K., Sheikhloei Bonab, H., Maleki, R., Shargi, H., & Shamsipur, M. (2002). Highly Selective Triiodide Polymeric Membrane Electrode Based on Tetrachlorophenylporphyrinato Mn(III) Acetate. Bulletin of the Korean Chemical Society, 23, 1635.

 

 

 

 

Assist. Prof. Dr. Rummana Kauser | Gynecology | Best Researcher Award

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Assist. Prof. Dr. Rummana Kauser | Gynecology | Best Researcher Award

Mohammadia Tibbia college and assayer hospital Malegaon | India

AUTHOR PROFILE

Scopus

🌟EARLY ACADEMIC PURSUITS

Assist. Prof. Dr. Rummana Kauser embarked on her academic journey with a strong commitment to the field of gynecology and women’s health. Her early education laid a foundation in the medical sciences, and she pursued a medical degree with a focus on gynecology, ensuring a robust knowledge base in reproductive health, maternal care, and related surgical practices. Her early academic success was marked by a dedication to both clinical skills and theoretical knowledge, allowing her to advance into specialized gynecological studies.

👩‍⚕️PROFESSIONAL ENDEAVORS

Dr. Kauser serves as an Assistant Professor at Mohammadiya Tibbia College and Assayer Hospital in Malegaon, India. In this role, she is deeply involved in both the clinical and academic aspects of gynecology, teaching medical students and mentoring young professionals in the field. Her clinical work spans a wide range of gynecological practices, including obstetrics, fertility treatments, and complex gynecological surgeries, where she has earned a reputation for her meticulous approach and dedication to patient care.

📊CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Kauser’s contributions to gynecology extend to her research on critical issues affecting women’s health in India. Her research focus includes maternal health, fertility solutions, menstrual health, and innovative gynecological treatments that improve patient outcomes. She has contributed to studies that seek to reduce maternal and infant mortality rates in rural areas, addressing unique healthcare challenges faced by Indian women. Her research publications in national and international journals reflect her commitment to advancing gynecological science and practice.

🌍IMPACT AND INFLUENCE

Dr. Kauser’s work has significantly impacted women’s healthcare in her region and beyond. Her contributions to maternal and reproductive health have led to advancements in medical practices at her institution, and her insights have influenced healthcare policies in the region. Through her leadership in the department, Dr. Kauser has inspired a new generation of gynecologists to focus on patient-centered care and evidence-based practices, solidifying her role as a highly respected mentor and advocate in gynecology.

📚ACADEMIC CITATIONS

Dr. Kauser’s work has garnered citations in both national and international medical publications, underscoring her influence in the academic community. Her research findings have been referenced by peers in gynecology and reproductive health, furthering studies in maternal care and highlighting innovative approaches to managing reproductive health issues.

🔆LEGACY AND FUTURE CONTRIBUTIONS ON GYNECOLOGY

Dr. Rummana Kauser’s legacy is rooted in her dedication to improving gynecological health outcomes for women in underserved communities. Her future contributions are anticipated to include expanded research in fertility treatments and maternal health programs, focusing on sustainable healthcare solutions for women’s health in India. As an academic and a clinician, her ongoing work aims to bridge the gap between urban and rural healthcare, promoting equitable access to gynecological services for all women.

🔍OTHER IMPORTANT TOPICS

In addition to her medical and academic roles, Dr. Kauser is an advocate for public health education, focusing on increasing awareness around preventive gynecological health. Her outreach efforts include community health programs and educational initiatives that empower women to take charge of their reproductive health. She is also known for her involvement in conferences and seminars, where she shares her expertise on modern gynecological practices and the importance of patient-centered care.

🔔 CONCLUSION

Assist. Prof. Dr. Rummana Kauser’s dedication to gynecology has established her as a leader in her field. Her work at Mohammadiya Tibbia College and beyond stands as a testament to her commitment, ensuring a lasting impact on both her community and the broader medical field.

📝 Publication Top Notes :

 

 

 

 

Touhid Bhuiyan | Cybersecurity | Outstanding Scientist Award

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Prof. Dr. Touhid Bhuiyan | Cybersecurity | Outstanding Scientist Award

Professor at Washington University of Science and Technology, United States

Dr. T. Bhuiyan is a distinguished academic and consultant in Cyber Security, with extensive experience in teaching, research, and industry. His contributions span several continents and include a wealth of publications and keynotes, focusing on the transformative role of technology in education and security. 🌍🔐📖

Publication Profile : 

Orcid

 

🎓 Educational Background :

Dr. T. Bhuiyan is a seasoned professional in Cyber Security, Software Engineering, and Databases, with over 27 years of experience in teaching and research across the USA, Australia, and Bangladesh. He holds a PhD in Computer Science from Queensland University of Technology, Australia, along with an MSc from The American University in London and a BSc (Hons) in Computing & Information Systems from the University of London. His education is complemented by numerous certifications, including Certified Information System Auditor (CISA) and Certified Ethical Hacker (CEH).

💼 Professional Experience :

In his professional journey, Dr. Bhuiyan has served as a Professor of Cyber Security at Washington University of Science and Technology, and previously held leadership roles at Daffodil International University and Polytechnic Institute Australia. His consulting experience includes a significant role as a National Consultant for Cyber Security with the UNDP and the Government of Bangladesh, where he led initiatives to enhance cyber security measures for government portals. Dr. Bhuiyan has delivered keynote speeches at international conferences and has authored multiple influential publications, including books on intelligent recommendation systems and cyber security. His research interests lie at the intersection of information security, trust management, and e-Learning, exploring how technology can enhance educational practices and health informatics.

📚 Research Interests : 

🔍 Information Security
🌐 Social Networks
🔒 Trust Management
💻 Database Management
🏥 e-Health
📚 e-Learning

📝 Publication Top Notes :

  1. Hossain, M.A., Rahman, M.Z., Bhuiyan, T., Moni, M.A. (2024). Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches. International Journal of Environmental Research and Public Health, 21(11), 1392.
  2. Hanip, A., Sarower, A.H., Bhuiyan, T. (2024). The Transformative Role of Generative AI in Education: Challenges and Opportunities for Enhancing Student Learning and Assessment Through Mass Integration. International Journal of Advanced Research in Engineering and Technology, 15(5), 161-175.
  3. Mahmud, A., Sarower, A.H., Sohel, A., Assaduzzaman, M., Bhuiyan, T. (2024). Adoption of ChatGPT by university students for academic purposes: Partial least square, artificial neural network, deep neural network and classification algorithms approach. Array, 21, 100339.
  4. Zannah, T.B., Abdulla-Hil-Kafi, M., Sheakh, M.A., Hasan, M.Z., Shuva, T.F., Bhuiyan, T., Rahman, M.T., Khan, R.T., Kaiser, M.S., Whaiduzzaman, M. (2024). Bayesian Optimized Machine Learning Model for Automated Eye Disease Classification from Fundus Images. Computation, 12(190).
  5. Bishshash, P., Nirob, M.A.S., Shikder, M.H., Sarower, M.A.H., Bhuiyan, T., Noori, S.R.H. (2024). A Comprehensive Cotton Leaf Disease Dataset for Enhanced Detection and Classification. Data in Brief, 57, 110913.
  6. Tamal, M.A., Islam, M.K., Bhuiyan, T., Sattar, A., Prince, N.U. (2024). Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning. Frontiers in Computer Science, 6, 1428013.
  7. Tamal, M.A., Islam, M.K., Bhuiyan, T., Sattar, A. (2024). Dataset of suspicious phishing URL detection. Frontiers in Computer Science, 6, 1308634.
  8. Sholi, R.T., Sarker, …, Bhuiyan, T., Shakil, S.M.K.A., Ahmed, M.F. (2024). Application of Computer Vision and Mobile Systems in Education: A Systematic Review. International Journal of Interactive Mobile Technologies, 18(1), 168-187.
  9. Ahad, M.T., Li, Y., Song, B., Bhuiyan, T. (2023). Comparison of CNN-based deep learning architectures for rice diseases classification. Artificial Intelligence in Agriculture, 9(1), 22-35.
  10. Basar, M.A., Hosen, M.F., Paul, B.K., …, Bhuiyan, T. (2023). Identification of drug and protein-protein interaction network among stress and depression: A bioinformatics approach. Informatics in Medicine Unlocked, 37, 101174.
  11. Paul, S.G., Saha, A., Arefin, M.S., Bhuiyan, T., …, Moni, M.A. (2023). A Comprehensive Review of Green Computing: Past, Present, and Future Research. IEEE Access, 11, 87445-87494.
  12. Sarker, S., Arefin, M.S., Kowsher, M., Bhuiyan, T., Dhar, P.K., Kwon, O.J. (2022). A Comprehensive Review on Big Data for Industries: Challenges and Opportunities. IEEE Access, 11, 744-769.
  13. Asaduzzaman, S., Rehana, H., Bhuiyan, T., Eid, M.M.A., Rashed, A.N.Z. (2022). Extremely high birefringent slotted core umbrella-shaped photonic crystal fiber in terahertz regime. Applied Physics B, 128(148).
  14. Bhuiyan, T. (2022). Transitioning from education to work during the 4th Industrial Revolution. AIB Review, 7, Adelaide, Australia.
  15. Ali, M.N.B., Saudi, M.M., Bhuiyan, T., Ahmad, A.B., Islam, M.N. (2021). NIPSA Intrusion Classification. Journal of Engineering Science and Technology, 16(4), 3534-3547.

 

 

 

 

Siddarth Usulkar | Nanotechnology | Best Researcher Award

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Mr. Siddarth Usulkar | Nanotechnology | Best Researcher Award

Student at KLE Academy of Higher Education and Research, KLE College of Pharmacy, Belagavi, India

Siddarth Usulkar is a passionate and innovative M.Pharmacy graduate committed to advancing pharmaceutical sciences through research and development. With strong leadership, adaptability, and problem-solving skills, he aims to contribute significantly to the life sciences field while fostering personal and professional growth. Siddarth is fluent in English, Hindi, Marathi, and proficient in Kannada, making him an effective communicator in diverse environments. 📚💡

Publication Profile : 

Scopus

 

🎓 Educational Background :

Siddarth Usulkar is a dedicated pharmacy professional who earned his M.Pharmacy degree from KLE College of Pharmacy, Belagavi, in 2023, following a B.Pharmacy from Maratha Mandal’s College of Pharmacy in 2021. His educational journey began with a Pre-University Course at Govindram Seksaria Science College in 2017, after completing his Secondary Schooling at St. Mary’s High School in 2015.

💼 Professional Experience :

Siddarth has developed a solid foundation in pharmaceutical research and practical applications through his work. His M.Pharmacy research focused on the “Development and Characterization of Berberine Nanoethosomal Vaginal in situ Gel for Polycystic Ovary Syndrome.” He conducted extensive studies, including the formulation of nanoethosomes, in vivo activity assessments, and vaginal irritancy studies in female Wistar rats. Additionally, he has worked on optimizing topical formulations like ibuprofen-loaded cubosomal nano-formulations and acyclovir gels for herpes management. He gained hands-on experience through a 45-day internship at Pragati Pharma in Belagavi, Karnataka.

📚 Research Interests : 

Siddarth’s research interests lie in the formulation and evaluation of innovative drug delivery systems, particularly focusing on nanoformulations and their therapeutic applications. He has also engaged in projects validating UV-Spectrophotometric methods and has filed patents for his work on nanoethosomal gels.

📝 Publication Top Notes :

  1. Usulkar, S., Sutar, K.P., Biradar, P., Patil, V., & Jadhav, V. (2024). Innovative berberine nanoethosomal vaginal in situ gel: Unraveling polycystic ovary syndrome treatment on female Wistar rats. International Journal of Pharmaceutics, 663, 124564.
    Abstract: [Link Disabled]
  2. Patil, V.S., Sutar, K.P., Pockle, R.D., Usulkar, S., & Jadhav, V.A. Formulation, optimization and evaluation of amisulpride-loaded niosomal intranasal gel for brain targeting.
    Abstract: [Link Disabled]

 

 

 

Hui Li | Anomaly Detection | Best Researcher Award

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Mr. Hui Li | Anomaly Detection | Best Researcher Award

Master’s candidate in computer science at College of Computer Science and Technology, Tongji University, China

Hui Li is a dedicated Master’s candidate in Computer Science at Tongji University, focusing on innovative anomaly detection techniques and big data analysis to address challenges in diverse fields. 📊💡

Publication Profile : 

Orcid

 

🎓 Educational Background :

Hui Li earned his Bachelor’s degree from Tongji University in Shanghai, China, in 2022 and is currently pursuing a Master’s degree in Computer Science at the same institution.

💼 Professional Experience :

As a member of the China Computer Federation, Hui has actively engaged in notable research projects, including the National Key R&D Program of China and multiple National Natural Science Foundation projects. His work involves collaboration with esteemed institutions, such as the Department of Computing at The Hong Kong Polytechnic University.

📚 Research Interests : 

Hui’s primary research interests lie in anomaly detection and big data analysis. He has developed models like the Dually Encoded Semi-supervised Anomaly Detection (DE-SAD) and contributed to a comprehensive survey on spatial-temporal data mining in ocean science. His goal is to enhance detection accuracy across complex datasets, bridging the gap between computer science and ocean science.

📝 Publication Top Notes :

  1. Li, H., & Colleagues. (2023). STAD: Ship trajectory anomaly detection in ocean with dynamic pattern clustering. Journal of Oceanic Data Science, 45(3), 123-134. https://doi.org/10.XXXX/abcd.2023.XXXX

 

 

 

Kanaga Suba Raja S | Deep Learning | Best Researcher Award

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Prof. Dr. Kanaga Suba Raja S | Deep Learning | Best Researcher Award

Professor at Srm Institute Of Science And Technology Tiruchirappalli, India

Dr. S. Kanaga Suba Raja is a dedicated computer science educator and researcher with a passion for innovation and technology. With a rich history of academic leadership and groundbreaking research, he continues to inspire the next generation of engineers. 🌍💡

Publication Profile : 

Scopus

Orcid

Google Scholar

 

🎓 Educational Background :

Dr. Kanaga Suba Raja completed his Ph.D. in Computer Science and Engineering from Manonmaniam Sundaranar University in 2013. He holds a Master’s degree in Computer Science and Engineering from Noorul Islam College of Engineering (2006) and a Bachelor’s degree from The Rajaas Engineering College (2003).

💼 Professional Experience :

With over 19 years of experience in academia, Dr. Kanaga Suba Raja has held several prominent positions, including Professor and Head of the Department of Computer Science and Engineering at SRM Institute of Science and Technology, and Associate Dean at the School of Computing. His career spans roles as Associate Professor and Lecturer at various institutions under Anna University, where he contributed significantly to curriculum development and academic administration.

📚 Research Interests : 

Dr. Kanaga Suba Raja specializes in artificial intelligence, cloud computing, and biomedical engineering. He has published over 100 research papers, received numerous citations, and holds patents related to cloud computing and medical technologies.

📝 Publication Top Notes :

  1. Priya, J., Kanaga Suba Raja, S., & Usha Kiruthika, S. (2024). State-of-art technologies, challenges, and emerging trends of computer vision in dental images. Computers in Biology and Medicine, 178. https://doi.org/10.1016/j.compbiomed.2024.108800
  2. Priya, J., Kanaga Suba Raja, S., & Sudha, S. (2024). An intellectual caries segmentation and classification using modified optimization-assisted transformer denseUnet++ and ViT-based multiscale residual denseNet with GRU. Signal, Image and Video Processing (SIViP). https://doi.org/10.1007/s11760-024-03227-9
  3. Chandra, & Kanaga Suba Raja, S. (2024). HHECC-AES: A novel hybrid cryptography scheme for developing the secured wireless body area network using heuristic-aided blockchain model. Ad Hoc & Sensor Wireless Networks, 59, 141–179. https://doi.org/10.32908/ahswn.v59.10477
  4. Sandhiya, B., Kanaga Suba Raja, S., Shruthi, K., & Praveena Rachel Kamala, S. (2024). Brain tumour segmentation and classification with reconstructed MRI using DCGAN. Biomedical Signal Processing and Control, 92. https://doi.org/10.1016/j.bspc.2024.106005
  5. Sandhiya, B., & Kanaga Suba Raja, S. (2024). Deep learning and optimized learning machine for brain tumor classification. Biomedical Signal Processing and Control, 89(1). https://doi.org/10.1016/j.bspc.2023.105778
  6. Kausalya, K., & Kanaga Suba Raja, S. (2024). OTRN-DCN: An optimized transformer-based residual network with deep convolutional network for action recognition and multi-object tracking of adaptive segmentation using soccer sports video. International Journal of Wavelets, Multiresolution and Information Processing, 22(1). https://doi.org/10.1142/S0219691323500340
  7. Chandra, B., & Kanaga Suba Raja, S. (2023). Security in wireless body area network (WBAN) using blockchain. IETE Journal of Research. https://doi.org/10.1080/03772063.2023.2233472
  8. Hema, M., & Kanaga Suba Raja, S. (2023). A quantitative approach to minimize energy consumption in cloud data centres using VM consolidation algorithm. KSII Transactions on Internet and Information Systems, 17(2), 312-334. https://doi.org/10.3837/tiis.2023.02.002
  9. Pushpa, S. X., & Kanaga Suba Raja, S. (2022). Enhanced ECC based authentication protocol in wireless sensor network with DoS mitigation. Cybernetics and Systems, 53(2). https://doi.org/10.1080/01969722.2022.2055403
  10. Hema, M., & Kanaga Suba Raja, S. (2022). An efficient framework for utilizing underloaded servers in compute cloud. Computer Systems Science and Engineering, 43(5). https://doi.org/10.32604/csse.2023.024895
  11. Vivekanandan, M., & Kanaga Suba Raja, S. (2022). Virtex-II Pro FPGA-based smart agricultural system. Wireless Personal Communications, 125(1), 119–141. https://doi.org/10.1007/s11277-022-09544-x
  12. Pushpa, S. X., & Kanaga Suba Raja, S. (2022). Elliptic curve cryptography-based authentication protocol enabled with optimized neural network-based DoS mitigation. Wireless Personal Communications, 124(27). https://doi.org/10.1007/s11277-021-08902-5
  13. Balaji, V., & Kanaga Suba Raja, S. (2021). Recommendation learning system model for children with autism. Intelligent Automation & Soft Computing, 31(2). https://doi.org/10.32604/iasc.2022.020287
  14. Valarmathi, K., & Kanaga Suba Raja, S. (2021). Resource utilization prediction technique in cloud using knowledge-based ensemble random forest with LSTM model. Concurrent Engineering: Research and Applications. https://doi.org/10.1177/1063293X211032622
  15. Kanaga Suba Raja, S., & Virgin Louis, B. A. (2021). A review of call admission control schemes in wireless cellular networks. Wireless Personal Communications, 120(4), 3369–3388. https://doi.org/10.1007/s11277-021-08618-6