Dr. Congcong Wang | Wireless Communication | Best Researcher Award

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Dr. Congcong Wang | Wireless Communication | Best Researcher Award

Research Associate, Institute of Computing, Chinese Academy of Sciences, China

Congcong Wang is a dedicated Ph.D.-level Research Scientist currently serving as a Special Research Assistant at the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. She is recognized for her cutting-edge work in wireless communication systems, particularly in Visible Light Communication (VLC), Full-Spectrum Wireless Communication, and Body Area Networks. With over ten peer-reviewed publications in prestigious journals such as IEEE TCOM and Optical Express, and seven national and international patents, Dr. Wang combines theoretical insight with practical innovations in experimental platforms and system design.

Publication Profile

ORCID

🎓 Education Background

Congcong Wang has pursued advanced academic training leading to a doctoral-level research profile, focused intensively on next-generation wireless communication technologies. Her rigorous education laid a solid foundation in areas such as MIMO VLC systems, OFDM, and dimming control in communication systems.

💼 Professional Experience

Currently, Dr. Wang is affiliated with the Institute of Computing Technology, Chinese Academy of Sciences, where she works as a Special Research Assistant. In this role, she has contributed significantly to research and development efforts, combining theoretical modeling with real-world system implementations and contributing to international standards in wireless communication.

🏆 Awards and Honors

Congcong Wang has been recognized through numerous accolades, including accepted papers at prestigious IEEE conferences and journal publications. Her innovative work has led to multiple national and international patents, showcasing her as a leader in wireless communication R&D.

🔬 Research Focus

Her core research interests include MIMO-based Visible Light Communication, Full-Spectrum Wireless Communication systems, Robotic Body Area Wireless Networks, dynamic subcarrier activation schemes, and deep learning-based signal detection in OTFS systems. She is also exploring AI-enabled wireless sensing and channel prediction through advanced architectures like Sparse Graph Attention Networks and CanFormer.

📝 Conclusion

Congcong Wang stands out as a young, impactful researcher in the wireless communication domain. Her blend of theoretical rigor, experimental validation, and translational outcomes continues to influence next-generation communication technologies.

📚 Top Publications with Details

  1. Joint SIC-Based Precoding and Sub-connected Architecture Design for MIMO VLC Systems – IEEE Transactions on Communications, 2022

    • Cited by: 30+

    • DOI: 10.1109/TCOMM.2022.3142696

  2. Joint Ordered QR Precoding and SIC Detection for MIMO VLC Systems – Optics Express, 2023

    • Cited by: 10+

    • DOI: 10.1364/OE.471543

  3. A Dimmable OFDM Scheme With Dynamic Subcarrier Activation for VLC – IEEE Photonics Journal, 2020

    • Cited by: 40+

    • DOI: 10.1109/JPHOT.2020.2964744

  4. A Generalized Dimming Control Scheme for Visible Light Communications – IEEE Transactions on Communications, 2021

    • Cited by: 60+

    • DOI: 10.1109/TCOMM.2020.3038665

  5. SIC-based Precoding Scheme with Sub-connected Architecture for MIMO VLC Systems – IEEE GLOBECOM, 2022

    • Cited by: 15+

    • DOI: 10.1109/GLOBECOM48099.2022.10003233

  6. Generalized Dimming Control Scheme with Optimal Dimming Control Pattern for VLC – IEEE WCNC, 2020

    • Cited by: 25+

    • DOI: 10.1109/WCNC45663.2020.9118991

 

Mr. Md Saifur Rahman | Mathematical | Best Researcher Award

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Mr. Md Saifur Rahman | Mathematical | Best Researcher Award

Assistant Professor, RAJUK Uttara Model College, Bangladesh

Md Saifur Rahman is an accomplished Assistant Professor of Mathematics at RAJUK Uttara Model College, Dhaka, Bangladesh, with over 15 years of experience in academia. He is currently pursuing his Ph.D. at Bangladesh University of Engineering and Technology (BUET), focusing on the mathematical modeling and optimal control of brain encephalitis. He has made notable contributions in mathematical biology, computational modeling, and infectious disease epidemiology. His interdisciplinary work bridges mathematics with real-world biomedical problems, and he actively presents his research across national and international platforms.

Publication Profile

ORCID

🎓 Education Background

Md Saifur Rahman earned his MPhil in Mathematics from the Military Institute of Science and Technology (MIST), and his MS in Applied Mathematics from the University of Chittagong. He is currently pursuing a Ph.D. in Mathematical Modeling at BUET, Dhaka, Bangladesh, where his doctoral research explores the transmission dynamics and control strategies for brain encephalitis using mathematical and computational tools.

💼 Professional Experience

Currently serving as an Assistant Professor at RAJUK Uttara Model College, Dhaka, he has dedicated over 15 years to teaching and academic development. His expertise extends into scientific computing using COMSOL Multiphysics and MATLAB. He has delivered invited lectures on ICT-enabled education and continues to influence the educational landscape through both innovation and research.

🏆 Awards and Honors

Md Saifur Rahman received the Best Teacher Award in 2011 for his innovative use of multimedia content in teaching. He has also been recognized for delivering invited talks in ICT and education, and his academic influence spans several conferences across Bangladesh, Nepal, and Canada.

🔬 Research Focus

His research focuses on mathematical biology, fluid dynamics, and epidemiology, particularly modeling the transmission of infectious diseases like viral and bacterial encephalitis. He has developed mathematical models incorporating optimal control strategies to aid public health interventions. His work involves advanced computational tools such as COMSOL, Tecplot, and MATLAB to simulate disease spread and evaluate mitigation techniques.

🔚 Conclusion

Md Saifur Rahman is a dedicated scholar blending theoretical mathematics with applied health science, creating a meaningful impact in the fields of disease modeling and educational innovation. Through his interdisciplinary contributions and international presentations, he continues to build bridges between computation, biology, and societal well-being.

📚 Top Publications

  1. Mathematical Modeling and Optimal Control of Viral Encephalitis
    🔗 Published in MDPI Mathematics (2024)
    🗓 Year: 2024
    📊 Cited by: 4 articles on ResearchGate
    📌 Summary: This paper presents an optimal control model for viral encephalitis and its implications for intervention strategies.

  2. Numerical Study of Heat and Mass Transfer in Nanofluid Flow Through Lid-Driven Porous Cavity
    🔗 Published in Scopus-indexed conference proceedings (2022)
    🗓 Year: 2022
    📊 Cited by: 2 articles
    📌 Summary: Investigates nanofluid behavior using computational simulations with practical applications in energy systems.

  3. Computational Modeling of Japanese Encephalitis Transmission Dynamics
    🔗 Preprint on ResearchGate (2023)
    🗓 Year: 2023
    📊 Cited by: 1 article
    📌 Summary: Extends previous research to analyze vector-borne transmission and optimal interventions.

  4. Epidemiological Insights into Bacterial Encephalitis Using Mathematical Tools
    🔗 Under review, MDPI Mathematics
    🗓 Year: 2025 (expected)
    📌 Summary: Explores bacterial encephalitis modeling to enhance public health strategy development.

 

Dr. Yirga Yayeh Munaye | security | Best Researcher Award

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Dr. Yirga Yayeh Munaye | secuirty | Best Researcher Award

PhD, Director of e-learning management unit, Injibara University, Ethiopia.

Dr. Yirga Yayeh Munaye is an Ethiopian academic and researcher with expertise in Electrical Engineering, Computer Science, and Information Technology. He currently serves as an Assistant Professor and Director of the E-learning Management Unit at Injibara University, Ethiopia. With a Ph.D. from National Taipei University of Technology, Taiwan, Dr. Munaye is known for his significant contributions in wireless communication, AI, and UAV-assisted resource management. His leadership in academia spans various universities, reflecting his passion for teaching, research, and community service.

Publication Profile

Google Scholar

🎓 Education Background

Dr. Munaye earned his Ph.D. in Electrical Engineering and Computer Science from National Taipei University of Technology (NTUT), Taiwan, in 2021 with a dissertation graded Excellent (91.4/100). Prior to that, he obtained an M.Sc. in Information Science from Addis Ababa University, Ethiopia, in 2014 and a B.Sc. in Information Technology from Bahir Dar University in 2009. His academic training reflects consistent excellence and specialization in advanced communication and AI applications.

👨‍🏫 Professional Experience

Dr. Munaye has served in various academic roles, including as Assistant Professor and Researcher at Injibara University since 2022, where he also coordinated postgraduate and community research services. Previously, he held teaching and research positions at Bahir Dar Institute of Technology and Assosa University. He has mentored Master’s and Ph.D. students, led network and internet chair units, and participated in proposal writing and journal editing, contributing significantly to Ethiopia’s higher education landscape.

🏆 Awards and Honors

Dr. Munaye has received numerous certificates and awards recognizing his academic contributions. These include participation in the Foundations for Excellence in Teaching Online masterclass (2023), the Science and Engineering Research training by AWB (2022), and international ICT training at XIDIAN University, China (2017). He has also earned honors for research writing, project proposal development, and higher diploma program achievements, underlining his commitment to continuous academic development.

🔬 Research Focus

Dr. Munaye’s research focuses on AI and wireless communication systems, UAV deployment strategies, mobile communications, and cybersecurity. He is especially passionate about the intersection of deep learning with resource management in next-generation networks. His work spans across emerging technologies including IoT security, biomedical sensors, and machine learning applications, reflecting a strong interdisciplinary and future-oriented research profile.

✅ Conclusion

With a career rooted in excellence, leadership, and innovation, Dr. Yirga Yayeh Munaye exemplifies the qualities of a modern researcher and educator. His contributions to teaching, mentoring, and groundbreaking research continue to make a lasting impact on Ethiopian academia and global knowledge systems.

📚 Top Publications Notes

  1. Cyber security: State of the art, challenges and future directions
    Cyber Security and Applications, 2024
    Cited by: 184

  2. UAV positioning for throughput maximization using deep learning approaches
    Sensors, 2019
    Cited by: 60

  3. An indoor and outdoor positioning using a hybrid of support vector machine and deep neural network algorithms
    Journal of Sensors, 2018
    Cited by: 58

  4. Applying Deep Neural Network (DNN) for large-scale indoor localization using feed-forward neural network (FFNN) algorithm
    IEEE ICASI Conference Proceedings, 2018
    Cited by: 38

  5. Big data: security issues, challenges and future scope
    International Journal of Computer Engineering & Technology, 2016
    Cited by: 37

  6. Deep-reinforcement-learning-based drone base station deployment for wireless communication services
    IEEE Internet of Things Journal, 2022
    Cited by: 33

  7. Indoor localization using K-nearest neighbor and artificial neural network back propagation algorithms
    WOCC Conference Proceedings, 2018
    Cited by: 33

  8. Convolutional neural networks and histogram-oriented gradients: a hybrid approach for automatic mango disease detection and classification
    International Journal of Information Technology, 2024
    Cited by: 32

 

Mr. Ayush Roy | Computer Vision | Young Researcher Award

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Mr. Ayush Roy | Computer Vision | Young Researcher Award

PhD, University at Buffalo, United States

Ayush Roy is an emerging researcher and innovator in the field of Electrical Engineering with a deep interest in AI, computer vision, and biomedical image analysis. Currently pursuing his B.E. at Jadavpur University, he has demonstrated exceptional potential through interdisciplinary research, AI-driven solutions, and impactful contributions to both academia and real-world applications. With multiple international publications and recognitions, Ayush is a dynamic force in the intersection of deep learning, signal processing, and intelligent systems.

Publication Profile

Google Scholar

🎓 Education Background

Ayush Roy is a final-year undergraduate student at Jadavpur University, West Bengal, India, enrolled in the Bachelor of Engineering (Electrical) program with an SGPA of 8.1/10 (2020–2024). He completed his schooling from Bhartiya Vidya Bhavan, West Bengal under the CBSE board, scoring 90.6% in Class 12 and a perfect CGPA of 10 in Class 10.

💼 Professional Experience

Ayush’s research journey began at Jadavpur University, working under renowned professors in Audio Signal Processing, Reinforcement Learning, and Image Segmentation. As a research intern at the Indian Statistical Institute, he contributed to dataset development and text detection models. He furthered his research as an intern at the University of Malaya on transformer-based networks and at IISc Bangalore on CLIP for image quality assessment. His work integrates deep learning models like YOLO, Swin Transformer, UNet, and CLIP with novel architectures and real-world applications.

🏆 Awards and Honors

Ayush has earned several accolades such as the Most Innovative Solution award at Hack-a-Web by NIT Bhopal (2021), 3rd Prize at FrostHack, IIT Mandi (2022), Top 10 in Cloud Community Hackday by GDG Cloud, and became a Finalist in both the IEEE R10 Robotics Competition and 404 Resolved hackathon at IIT Delhi.

🔬 Research Focus

His primary research areas include computer vision, medical image segmentation, scene text detection, and real-time AI systems. He is especially focused on lightweight models, attention mechanisms, domain adaptation, and hybrid approaches combining deep learning and signal processing. He has created multiple datasets for benchmarking including those for drone license plate detection, underwater text, water meter digit recognition, and circuit component recognition.

📌 Conclusion

Ayush Roy stands as a committed and creative researcher, blending electrical engineering fundamentals with cutting-edge AI methodologies. His work not only adds value to academic literature but also paves the way for practical, socially impactful AI systems. With an impressive early-career portfolio, Ayush continues to show immense promise for future contributions to science and technology.

📚 Top Publication Notes 

AWGUNet: Attention-aided Wavelet Guided U-net for nuclei segmentation in histopathology images

Year: 2024

Journal/Conference: ISBI 2024

Cited By: 2 articles (Google Scholar)

A Wavelet Guided Attention Module for Skin Cancer Classification

Year: 2024

Journal/Conference: ISBI 2024

Cited By: 1 article (Google Scholar)

A New Lightweight Attention-based Model for Emotion Recognition Using Distorted Social Media Images

Year: 2023

Journal/Conference: ACPR 2023

Cited By: 3 articles

Fourier Feature-based CBAM and Vision Transformer for Text Detection in Drone Images

Year: 2023

Conference: ICDAR WML 2023

Cited By: 1 article

A Lightweight Script Independent Scene Text Style Transfer Network

Year: 2024

Journal: International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)

Cited By: 1 article

Identification and Classification of Human Mental Stress using Physiological Data

Year: 2022

Conference: IEEE CATCON 2022

Cited By: 4 articles

Adapting a Swin Transformer for License Plate Number and Text Detection in Drone Images

Year: 2023

Journal: Artificial Intelligence and Applications (AIA)

Cited By: 2 articles

An Attention-based Fusion of ResNet50 and InceptionV3 Model for Water Meter Digit Recognition

Year: 2023

Journal: Artificial Intelligence and Applications (AIA)

Cited By: 1 article

DAU-Net: Dual Attention-aided U-Net for Segmenting Tumor Region in Breast Ultrasound Images

Year: 2023

Journal: PLOS ONE

Cited By: 6 articles

 

 

Dr. Yan WU | Data Cleaning | Best Researcher Award

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Dr. Yan WU | Data Cleaning | Best Researcher Award

Lecturer, Department of Foundational Courses Dujiangyan Campus, Sichuan Agricultural University, China

Yan Wu is a dedicated statistician and lecturer at Sichuan Agricultural University, specializing in the intersection of statistics and data science. With a strong academic foundation and international research exposure, Yan focuses on innovative statistical methods applied to environmental science and knowledge base correction.

Publication Profile

Google Scholar

🎓 Education Background

Yan Wu earned a PhD in Statistics from Southwest University in 2023 under Professor Zili Zhang. During the PhD, Yan expanded research expertise as a visiting scholar at the University of Luxembourg’s Big Data Group. Prior to this, Yan completed a Master’s in Probability and Mathematical Statistics at Chengdu University of Technology and a Bachelor’s degree in Mathematics and Applied Mathematics from Southwest University of Science and Technology with high honors.

💼 Professional Experience

Yan Wu currently serves as a lecturer at Sichuan Agricultural University, Department of Foundational Courses. Yan’s research includes guided inductive logic programming and 3D geological modeling, contributing to cross-disciplinary projects in statistics, artificial intelligence, and environmental modeling. Yan has also been involved in several national and international research projects integrating big data and machine learning techniques.

🏆 Awards and Honors

Yan has been recognized multiple times, including the prestigious CSC-funded Visiting PhD Scholar position at the University of Luxembourg in 2018, outstanding trainee awards in Sichuan Higher Education Teacher Qualification Program, and several academic scholarships and innovation awards during graduate studies. Notably, Yan won third prize in a campus-wide mathematical modeling competition, highlighting strong analytical and problem-solving skills.

🔍 Research Focus

Yan Wu’s research focuses on statistical modeling for environmental issues such as carbon emission markets, as well as the application of guided inductive logic programming to clean and correct large knowledge bases. This interdisciplinary work bridges environmental science, data science, and artificial intelligence to create efficient, data-driven solutions.

🔚 Conclusion

With a robust educational background, diverse research experience, and notable academic achievements, Yan Wu is a promising early-career researcher contributing significantly to statistical science and its applications in environmental and knowledge systems.

📚 Publication Top Notes

  1. Reducing greenhouse gas emissions: a duopoly market pricing competition and cooperation under the carbon emissions cap
    M Jian, H He, C Ma, Y Wu, H Yang
    Environmental Science and Pollution Research 26, 16847-16854 (2019)
    Cited by 31 article

  2. A green production strategies for carbon-sensitive products with a carbon cap policy
    C Ma, X Liu, H Zhang, Y Wu
    Advances in Production Engineering & Management 11(3), 216-226 (2016)
    Cited by 19 articles

  3. Guided inductive logic programming: Cleaning knowledge bases with iterative user feedback
    Y Wu, J Chen, P Haxhidauti, V Ellampallil Venugopal, M Theobald
    6th Global Conference on Artificial Intelligence (GCAI 2020) (2020)
    Cited by 2 articles

  4. Correcting large knowledge bases using guided inductive logic learning rules
    Y Wu, Z Zhang, G Wang
    PRICAI 2021: Trends in Artificial Intelligence (2021)
    Cited by 1 article

  5. An Inductive Logical Model with Exceptional Information for Error Detection and Correction in Large Knowledge Bases
    Z Wu, Yan and Lin, Xiao and Lian, Haojie and Zhang
    Mathematics 13(11), Article 187 (2025)

 

Prof. Hong Xiang | Diseases | Best Researcher Award

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Prof. Hong Xiang | Diseases | Best Researcher Award

Associate Researcher, First Affiliated Hospital of Dalian Medical University, China

Dr. Hong Xiang is an accomplished researcher specializing in integrated medicine intervention for exocrine pancreatic diseases. With a strong track record of pioneering multi-omics platforms and 3D pancreatic organoid co-culture technologies, Dr. Xiang has contributed significantly to discovering new therapeutic targets and developing innovative peptide drugs and mRNA vaccines. He is a recognized member of several prestigious scientific societies, actively advancing pancreatic disease research.

Publication Profile

Scopus

ORCID

Education Background 🎓

Dr. Xiang holds advanced degrees in biomedical sciences and has undergone extensive training in multi-omics platforms and organoid technology, which form the foundation of his cutting-edge research in pancreatic diseases.

Professional Experience 💼

Currently engaged in cutting-edge research, Dr. Xiang has published 24 journal articles in top-tier SCI and Scopus-indexed journals, authored multiple patents (13), and contributed to several books. He holds memberships in notable professional bodies such as the American Pancreatic Association and Chinese Society of Inventions, reflecting his leadership in translational medicine and drug development.

Awards and Honors 🏆

Among his accolades, Dr. Xiang received the Dalian Science and Technology Talent Innovation Support Program Project award for Outstanding Young Science and Technology Talents (2022RY16). His innovative work in integrated medicine and pancreatic disease treatment continues to earn him recognition in academic and scientific communities.

Research Focus 🔬

Dr. Xiang’s primary research focus lies in integrated medicine for exocrine pancreatic diseases, with key discoveries targeting S100A9, RFTN1, and HTRA1 proteins implicated in pancreatitis and cancer transformation. His development of attenuated peptide drugs and mRNA vaccines highlights a promising therapeutic frontier in pancreatic oncology and inflammation.

Conclusion ✨

Dr. Hong Xiang exemplifies a leading figure in pancreatic disease research, merging innovative technology platforms with translational medicine. His contributions pave the way for novel therapies that can revolutionize treatment paradigms, securing his status as a deserving candidate for the Best Researcher Award.

Publication Top Notes 📚

  1. Prospect of Gold Nanoparticles in Pancreatic Cancer
    Pharmaceutics, 2024 | DOI:10.3390/pharmaceutics16060806
    Co-authors: Tianyi Yin, Jingrun Han, Yuying Cui, Dong Shang, Hong Xiang

  2. Vanin1 (VNN1) in chronic diseases: Future directions for targeted therapy
    European Journal of Pharmacology, 2024 | DOI:10.1016/j.ejphar.2023.176220
    Co-authors: Hao Yu, Yuying Cui, Fangyue Guo, YuTong Zhu, Xiaonan Zhang, Dong Shang, Deshi Dong, Hong Xiang

  3. Carfilzomib relieves pancreatitis-initiated pancreatic ductal adenocarcinoma by inhibiting high-temperature requirement protein A1
    Cell Death Discovery, 2024 | DOI:10.1038/s41420-024-01806-w
    Co-authors: Fangyue Guo, Xufeng Tao, Yu Wu, Deshi Dong, Yanna Zhu, Dong Shang, Hong Xiang

  4. Tryptophan metabolite norharman secreted by cultivated Lactobacillus attenuates acute pancreatitis as an antagonist of histone deacetylases
    BMC Medicine, 2023 | DOI:10.1186/s12916-023-02997-2
    Co-authors: Qi Zhou, Xufeng Tao, Fangyue Guo, Yu Wu, Dawei Deng, Linlin Lv, Deshi Dong, Dong Shang, Hong Xiang

  5. Health Impacts of High BMI in China: Terrible Present and Future
    International Journal of Environmental Research and Public Health, 2022 | DOI:10.3390/ijerph192316173
    Co-authors: Hong Xiang, Runjuan Yang, Jiaxin Tu, Xi Guan, Xufeng Tao

  6. Activated Pancreatic Stellate Cells Promote Acinar Duct Metaplasia by Disrupting Mitochondrial Respiration and Releasing Reactive Oxygen Species
    Current Chinese Science, 2022 | DOI:10.2174/2210298101666210928122952
    Co-authors: Hong Xiang, Fangyue Guo, Qi Zhou, Xufeng Tao, Deshi Dong

  7. Bacterial community mapping of the intestinal tract in acute pancreatitis rats based on 16S rDNA gene sequence analysis
    RSC Advances, 2019 | DOI:10.1039/C8RA09547G
    Co-authors: Xufeng Tao, Fangyue Guo, Qi Zhou, Fenglin Hu, Hong Xiang, Gary Guishan Xiao, Dong Shang

 

Assist. Prof. Dr. Sachin Pawar | Medicine | Best Researcher Award

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Assist. Prof. Dr. Sachin Pawar | Medicine | Best Researcher Award

Assistant Professor,Pharmaceutical Quality Assurance Manipal College of Pharmaceutical Sciences Manipal Academy of Higher Education, India

Dr. Sachin Dattram Pawar is an accomplished pharmaceutical scientist and Assistant Professor at the Department of Pharmaceutical Quality Assurance, Manipal College of Pharmaceutical Sciences, MAHE, India. With a Ph.D. in Pharmaceutical Sciences and extensive expertise in analytical chemistry, formulation development, and plant metabolomics, he has contributed significantly to advanced pharmaceutical research. His international exposure includes a postdoctoral fellowship at Sorbonne University, France, and prior industrial experience as a mass spectrometry specialist. He is recognized for innovative work in LC-MS/MS, GC-MS, and MALDI-TOF analysis, contributing to impactful publications and patent filings, showcasing a deep commitment to scientific advancement.

Publication Profile

Google Scholar

ORCID

Scopus

🎓 Education Background

Dr. Pawar holds a Ph.D. in Pharmaceutical Sciences (2024) from the National Institute of Pharmaceutical Education and Research, Guwahati (NIPER-G), where he investigated the pharmacokinetics of antidepressants in combination with herbal compounds. He earned his M.Pharm in Quality Assurance (2017–2019) with distinction from Swami Ramanand Teerth Marathwada University, Nanded, and completed his B.Pharm from the same university in 2017. His academic journey reflects consistent excellence in pharmaceutical education and research training.

🧪 Professional Experience

Dr. Pawar has over four years of combined academic and industrial experience. He is currently serving as an Assistant Professor at Manipal College of Pharmaceutical Sciences. He worked as a Postdoctoral Research Fellow at Sorbonne University, France (2024), and served as a mass spectrometry specialist at Waters India Pvt. Ltd. (2023–2024). His earlier roles include Executive QA at Daewoong Pharmaceuticals and Ph.D. research fellowship at NIPER-G. Throughout his career, he has engaged in interdisciplinary work involving formulation, pharmacokinetics, plant metabolomics, and analytical development.

🏅 Awards and Honors

Dr. Pawar is a recipient of certificates of appreciation from the National Dope Testing Laboratory, New Delhi, and NIPER-G for his contributions to anti-doping research. He qualified the national-level GPAT (2019) with AIR 1549 and secured a Ph.D. fellowship through NIPER-JEE (2020). He also held a leadership role as General Secretary at Nanded Pharmacy College during his undergraduate years, reflecting his dedication to both academic excellence and student leadership.

🔬 Research Focus

Dr. Pawar’s research centers on analytical and bioanalytical method development using hyphenated techniques like LC-MS/MS, GC-MS, and MALDI-TOF. His focus areas include drug metabolism and pharmacokinetics, solid lipid nanoparticles for drug delivery, endocrine-disrupting chemical analysis, and plant metabolomics using HRMS. He has published extensively on novel formulations, bioavailability enhancement, anti-doping reference standards, and natural compound profiling, with a multidisciplinary approach bridging pharmaceutical chemistry and modern analytical tools.

🧾 Conclusion

With a rapidly growing academic and research profile, Dr. Sachin D. Pawar represents a new generation of pharmaceutical scientists contributing to quality assurance, advanced drug delivery systems, and innovative analytical methodologies. His global exposure, cutting-edge expertise, and dedication to both education and research make him a strong contender for the Best Researcher Award.

📚 Top Publication Notes

  1. Amoxapine-Loaded Solid Lipid Nanoparticles with Superior Preclinical Pharmacokinetics for Better Brain Delivery (2023) – ACS Chemical Neuroscience
    ➤ Cited by: 18 | Co-authors: Kulhari H., Kumar P., Gawali K., Murty US
    ➤ Highlight: Demonstrated enhanced brain targeting and delivery using SLNs with robust LC-MS/MS data.

  2. Synthesis and Characterization of Octopamine Sulfate, Norfenefrine Sulfate, and Etilefrine Sulfate Reference Materials (2023) – Journal of Chemical Technology & Biotechnology
    ➤ Cited by: 10 | Co-authors: Kalita SJ, Vernekar P, Sethi KK, Sahu PL, Murty US
    ➤ Highlight: Developed vital anti-doping standards using advanced analytical techniques.

  3. Physicochemical Characterization and Pharmacokinetic Assessment of Bergamottin Solid Lipid Nanoparticles (2024) – Journal of Drug Delivery Science and Technology
    ➤ Cited by: 5 | Co-authors: Jat S., Singh P., Datusalia AK, Kumar P
    ➤ Highlight: Investigated enhanced bioavailability and delivery performance of herbal bioactives.

  4. Amphiphilic Dynamic Covalent Polymer Vectors of siRNA (2024) – Chemical Science
    ➤ Cited by: 3 | Co-authors: Trousselier P., Bessin Y., Bettache N., Ulrich S.
    ➤ Highlight: Showcased innovative siRNA delivery using DCP systems, reflecting interdisciplinary prowess.

  5. Process Development for the Total Synthesis of Carboxy Toremifene as a Standard for Anti-Doping (2022) – Drug Testing and Analysis
    ➤ Cited by: 11 | Co-authors: Kumar GJ, Dubey S, Murty US, Radhakrishnanand P
    ➤ Highlight: Pioneered synthesis and characterization of doping control metabolites.

 

 

Dr. vassilios lekidis | Engineering | Best Researcher Award

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Dr. vassilios lekidis | Engineering | Best Researcher Award

HEAD OF EARTHQUAKE RESISTANT BRANCH, OASP-ITSAK, Greece

Dr. Vassilios Lekidis is a distinguished Greek civil engineer and expert in earthquake engineering, with over four decades of professional and academic experience. Based in Thessaloniki, Greece, he has served as the General Director of the Institute of Engineering Seismology and Earthquake Engineering (ITSAK) across multiple terms, guiding key national and international seismic risk management projects. His contributions span leadership, engineering consulting, and high-impact research, particularly in structural dynamics and seismic vulnerability assessments.

Publication Profile

Scopus

🎓 Education Background

Dr. Lekidis holds a Ph.D. in Earthquake Engineering and Finite Elements (1995) and a B.Sc. in Engineering (1997) from the Aristotle University of Thessaloniki. He also earned an M.Sc. in Engineering from Delft University of Technology, Netherlands (1998), specializing in static and dynamic structural analysis. His educational foundation merges deep theoretical mechanics with advanced computational methods.

🏗️ Professional Experience

Beginning his career in the early 1980s, Dr. Lekidis led construction operations at top-tier Greek contracting firms like AKTOR and SARANTOPOULOS. He later transitioned to a consulting engineer role, focusing on seismic resilience for buildings, bridges, and silos. Most notably, he served three terms as General Director of ITSAK, contributing to policy, structural safety, and international seismic risk reduction efforts. He has been involved in major infrastructure evaluations, including bridges like the Evripos cable-stayed bridge.

🏅 Awards and Honors

Dr. Lekidis has held numerous prestigious appointments, such as Vice President of the Technical Chamber of Greece (Central Macedonia, 2009–2012), member of Greece’s Permanent Earthquake Planning Committee, and board member of ITSAK and EGNATIA SA. He has also participated in forming national seismic codes and organized engineering congresses. His esteemed reputation in seismology and engineering has been recognized by both scientific and governmental institutions.

🔬 Research Focus

His research expertise encompasses seismic behavior of structures, vulnerability assessment, remote sensing for structural monitoring, and the finite element analysis of infrastructure. He has led or contributed to European and NATO-supported projects including SERINA, EUROSEISTEST, and HiPER-CRACK. His scholarly work bridges theory and application, especially for seismic instrumentation and performance of reinforced concrete and bridge systems under seismic load.

🧩 Conclusion

Dr. Vassilios Lekidis exemplifies excellence in structural engineering and seismic safety. His leadership in ITSAK, robust academic portfolio, and dedication to earthquake risk reduction underscore his impact on both engineering practice and public safety. As a visionary and veteran in the field, his ongoing legacy continues to shape modern earthquake engineering in Greece and beyond.

Publication Top Notes

Experimental evaluation of a practical methodology for assessing the seismic demand from acceleration-sensitive secondary systems installed in R.C. buildings

 

Prof. Dr. Metin Zontul | Machine Learning | Best Researcher Award

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Prof. Dr. Metin Zontul | Machine Learning | Best Researcher Award

Dean, Sivas University of Science and Technology, Turkey

Prof. Dr. Metin Zontul is a seasoned academic and researcher in the fields of machine learning, data mining, and intelligent systems, currently serving as Professor and Dean at the Faculty of Engineering and Natural Sciences, Sivas University of Science and Technology, Turkey. With over 30 years of academic experience, he has held various esteemed positions at several universities in Turkey and contributed significantly to national-level research projects, innovation in artificial intelligence, and academic leadership.

Publication Profile

Google Scholar

ORCID

🎓 Education Background

He earned his Ph.D. in Quantitative Methods in Business Administration (2004) from the Institute of Social Sciences, focusing his dissertation on clustering countries trading with Turkey using SOM-type artificial neural networks. He holds an M.Sc. in Computer-Aided Design, Manufacturing, and Programming (1996), where he analyzed local area network access protocols, and a B.Sc. in Computer Engineering (1993) from Middle East Technical University.

💼 Professional Experience

Prof. Zontul has held multiple academic ranks, starting as a Lecturer at Cumhuriyet University (1994–2005) and advancing to Assistant, Associate, and then Professor at institutions such as Istanbul Aydın University, Arel University, Ayvansaray University, and Topkapi University. He has been a key academic leader, serving as Dean and Department Chair across several faculties. Since 2023, he has led the Faculty of Engineering and Natural Sciences at Sivas UST. He also supervises graduate theses and collaborates on research with TUBITAK and other industry-linked projects.

🏆 Awards and Honors

Prof. Zontul has received Publication Incentive Awards from Istanbul Aydın University in 2014 and 2016 for his scholarly contributions. He is a former member of IEEE and holds a 2024 patent for a Personnel Assignment and Routing System related to unit failure and maintenance operations.

🔬 Research Focus

His research interests span machine learning, deep learning, data mining, signal processing, natural language processing, and intelligent systems. He has contributed extensively to the scientific community through 25+ peer-reviewed journal articles, 20+ conference papers, and collaborative projects involving academia and industry. His supervision of numerous theses and his involvement in over 30 national research projects reflect his commitment to practical and academic advancements in AI.

🔚 Conclusion

Prof. Dr. Metin Zontul stands as a multifaceted academician blending research, leadership, and innovation. His significant contributions to AI, education, and national research initiatives have cemented his reputation as a leading scholar in his field.

📚 Top Publications 

  1. Application of artificial intelligence neural network modeling to predict the generation of domestic, commercial and construction wastes (2021)
    Journal: Waste Management & Research
    Cited by: 92
    Co-authors: G. Coskuner, M.S. Jassim, S. Karateke

  2. Comparative performance analysis of support vector regression and artificial neural network for prediction of municipal solid waste generation (2022)
    Journal: Waste Management & Research
    Cited by: 49
    Co-authors: M.S. Jassim, G. Coskuner

  3. Urban bus arrival time prediction: A review of computational models (2013)
    Journal: International Journal of Recent Technology and Engineering (IJRTE)
    Cited by: 123
    Co-author: M. Altinkaya

  4. Measuring the efficiency of telecommunication sectors of OECD countries using data envelopment analysis (2005)
    Journal: CU Journal of Economics and Administrative Sciences
    Cited by: 41
    Co-authors: O. Kaynar, H. Bircan

  5. Wind speed forecasting using reptree and bagging methods in Kirklareli-Turkey (2013)
    Journal: Journal of Theoretical and Applied Information Technology
    Cited by: 35
    Co-authors: F. Aydin, G. Dogan, S. Sener, O. Kaynar

  6. The prediction of the ZnNi thickness and Ni% of ZnNi alloy electroplating using a machine learning method (2021)
    Journal: Transactions of the IMF
    Cited by: 34
    Co-authors: R. Katirci, H. Aktas

  7. A smart and mechanized agricultural application: From cultivation to harvest (2022)
    Journal: Applied Sciences
    Cited by: 31
    Co-authors: F. Kiani, G. Randazzo, I. Yelmen, A. Seyyedabbasi, S. Nematzadeh, F.A. Anka, et al.

 

 

Mr. Saurabh Pahune | Generative AI | Best Researcher Award

Posted on by Computer Scientists Awards

Mr. Saurabh Pahune | Generative AI | Best Researcher Award

Techncial Architect, Cardinal health, Ohio, United States

Saurabh Pahune (SMIEEE) is a highly skilled business automation analyst and AI/ML researcher with over 11 years of diverse industry and academic experience. He currently serves as a peer reviewer and editorial board member for reputed journals and is frequently invited as a guest speaker on AI/ML-driven supply chain automation. Known for his innovative work in large language models, generative AI, and intelligent systems, he has published several impactful papers and is a Senior Member of the IEEE. His work seamlessly blends technology with business, improving operational efficiency and driving enterprise transformation across healthcare and logistics domains.

Publication Profile

Google Scholar

ORCID

Scopus

🎓 Education Background

Saurabh holds a Master of Science in Electrical and Computer Engineering from the University of Memphis, USA (2016–2019). He earned his M.Tech in VLSI from RTMNU, Nagpur (2013–2015), and a Bachelor of Engineering in Electronics and Telecommunication from SGBAU, Amravati (2009–2013). His strong academic foundation underpins his technical expertise in AI, ML, and supply chain technologies.

💼 Professional Experience

Saurabh is currently leading AI and automation initiatives as an independent researcher and analyst at Tata Consultancy Services and previously at Vivid Technologies. His experience spans roles at Evolent Health, iSkylar Technologies, and the University of Memphis, where he conducted advanced research in intelligent systems. He specializes in LLMOps, GenAI, RPA, NLP, knowledge graphs, and automation frameworks, contributing significantly to process optimization in healthcare and logistics.

🏆 Awards and Honors

As a recognized Senior Member of IEEE, Saurabh has actively contributed as a reviewer for IEEE Transactions and Taylor & Francis journals. He has also earned multiple professional certifications, including IBM Chatbot Builder, Agile Planning, and Advanced RPA Professional by Automation Anywhere, and was awarded the Accredited Project Manager Certification (APRM) by the International Organization for Project Management.

🔬 Research Focus

Saurabh’s research centers around Artificial Intelligence, Machine Learning, Generative AI, Natural Language Processing, and their integration with business systems like supply chain and healthcare automation. His work explores scalable LLMOps, predictive analytics, knowledge graphs, and ontology-driven architectures. With over 100 citations, his contributions continue to shape cutting-edge applications in AI-enhanced business intelligence.

🔚 Conclusion

Saurabh Pahune exemplifies the synergy between research excellence and industry innovation. With strong technical acumen and strategic insight, he contributes to the academic community while driving AI-powered transformation across sectors. His commitment to continuous learning and cross-functional collaboration makes him a standout candidate for advanced research awards and leadership in AI and automation.

📚 Top Publications –Mr. Saurabh Pahune

  1. Several categories of large language models (LLMs): A short survey
    Year: 2023
    Journal: arXiv preprint arXiv:2307.10188
    Cited by: 36
    Co-author(s): M. Chandrasekharan

  2. Accelerating neural network training: A brief review
    Year: 2024
    Journal: Proceedings of the 2024 8th International Conference on Intelligent Systems
    Cited by: 22
    Co-author(s): S. Nokhwal, P. Chilakalapudi, P. Donekal, S. Nokhwal

  3. EMBAU: A novel technique to embed audio data using shuffled frog leaping algorithm
    Year: 2023
    Journal: Proceedings of the 2023 7th International Conference on Intelligent Systems
    Cited by: 21
    Co-author(s): S. Nokhwal, A. Chaudhary

  4. Quantum Generative Adversarial Networks: Bridging Classical and Quantum Realms
    Year: 2024
    Journal: Proceedings of the 2024 8th International Conference on Intelligent Systems
    Cited by: 18
    Co-author(s): S. Nokhwal, A. Chaudhary

  5. Large Language Models and Generative AI’s Expanding Role in Healthcare
    Year: 2024
    Journal: ResearchGate
    Cited by: 12
    Co-author(s): N. Rewatkar

  6. A Brief Overview of How AI Enables Healthcare Sector Rural Development
    Year: 2024
    Journal: ResearchGate
    Cited by: 8
    Co-author(s): S.A. Pahune

  7. The Importance of AI Data Governance in Large Language Models
    Year: 2025
    Journal: Big Data and Cognitive Computing 9(6), 147
    Cited by: 5
    Co-author(s): Z. Akhtar, V. Mandapati, K. Siddique

  8. Investigating the application of quantum-enhanced generative adversarial networks in optimizing supply chain processes
    Year: 2024
    Journal: International Research Journal of Engineering and Technology (IRJET)
    Cited by: 4
    Co-author(s): N. Rewatkar

  9. Cognitive automation in the supply chain: Unleashing the power of RPA vs. GenAI
    Year: 2024
    Journal: ResearchGate
    Cited by: 4
    Co-author(s): N. Rewatkar

  10. Healthcare: A Growing Role for Large Language Models and Generative AI
    Year: 2023
    Journal: International Journal for Research in Applied Science and Engineering
    Cited by: 4
    Co-author(s): N. Rewatkar