Paulo Eugênio da Costa Filho | Artificial Intelligence | Best Researcher Award

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Mr. Paulo Eugênio da Costa Filho | Artificial Intelligence | Best Researcher Award

Researcher at Federal University of Rio Grande do Norte, Brazil

Paulo Eugênio da Costa Filho is a dedicated Brazilian researcher and educator in the field of Food Science and Technology, with a strong focus on Food Microbiology. He has played pivotal roles in advancing food safety and quality, particularly through microbiological analysis of food and food products. With over two decades of academic and scientific experience, he serves as a full professor at the Federal University of Ceará (UFC). Prof. Costa Filho is also recognized for his involvement in graduate education and leadership in various research projects and academic societies.

Profile

Education :

The academic journey of this accomplished scholar reflects a deep-rooted commitment to excellence in food science and engineering. They hold a Bachelor’s degree in Food Engineering from the Federal University of Ceará (1993), which laid a strong foundation in the principles of food processing and safety. Advancing their expertise, they pursued both a Master’s (1997) and a PhD (2003) in Food Science and Technology at the Federal University of Viçosa, where they honed their research skills and specialized knowledge in food systems. Their academic path culminated with a prestigious postdoctoral research tenure at Université Laval, Canada (2009), further enriching their global perspective and scholarly contributions to the field.

Experience :

Since 2016, the researcher has served as a Full Professor in the Department of Food Technology at the Federal University of Ceará (UFC), where they specialize in the Microbiology of Foods. In this capacity, they have played a pivotal role in shaping both academic and research directions within the field. As Coordinator of the Graduate Program in Food Science and Technology at UFC, they have demonstrated strong leadership in advancing graduate education, curriculum development, and research collaboration. Their international experience includes a valuable period as a Visiting Researcher at Université Laval in Canada, where they completed a postdoctoral fellowship, further enriching their expertise and fostering cross-border scientific exchange.

Awards and Recognitions :

Prof. Paulo Eugênio da Costa Filho is a CNPq Research Productivity Fellow – Level 1D, a prestigious recognition awarded to researchers with a consistent and influential scientific output in Brazil. This honor reflects his long-standing contributions to advancing food microbiology and food safety through innovative research and academic leadership. His impactful role in graduate education is equally distinguished; Prof. Costa Filho has been nationally recognized for his dedication to mentoring future scientists and for strengthening the graduate training infrastructure in Food Science and Technology across Brazil. His efforts have significantly influenced both academic excellence and professional development in the field.

Research Focus :

The researcher’s work in Food Microbiology is distinguished by a comprehensive and applied focus on critical areas impacting food safety and innovation. Their research emphasizes the study of pathogenic microorganisms in foods, addressing public health concerns through advanced microbiological quality control practices. They actively investigate antimicrobial compounds and bacterial biofilms, contributing to the understanding and mitigation of microbial resistance in food environments. A significant part of their work involves the development and validation of analytical methods for the precise detection and control of microorganisms, ensuring the reliability and safety of food systems. Additionally, they explore the functional properties of probiotic and antimicrobial food components, aiming to enhance the nutritional and protective qualities of food products. This multifaceted research approach reflects a strong commitment to advancing food microbiology through both scientific rigor and real-world application.

Research  Skills :

With extensive expertise in microbiological analysis of foods, this professional is deeply committed to advancing food safety and quality assurance through rigorous scientific approaches. Their work emphasizes the design of microbiological research methodologies tailored to emerging foodborne challenges and technological innovations. In addition to research, they play a pivotal role in graduate student mentorship and thesis supervision, nurturing the next generation of food scientists with a focus on critical thinking and applied microbiology. Their capacity for project coordination and academic leadership has consistently driven collaborative initiatives, strengthened interdisciplinary networks, and elevated the standards of both research output and educational excellence.

Pulication Top Notes : 

Internet of Smart Grid Things (IoSGT): Prototyping a Real Cloud-Edge Testbed

Authors: H. Santos, P. Eugênio, L. Marques, H. Oliveira, D. Rosário, E. Nogueira, et al.

Source: Anais do XIV Simpósio Brasileiro de Computação Ubíqua e Pervasiva

Citations: 7

Year: 2022

Predictive Fraud Detection: An Intelligent Method for Internet of Smart Grid Things Systems

Authors: L. Bastos, B. Martins, H. Santos, I. Medeiros, P. Eugênio, L. Marques, et al.

Source: Journal of Internet Services and Applications, Vol. 14(1), pp. 160–176

Citations: 5

Year: 2023

Analysis of Electrical Signals by Machine Learning for Classification of Individualized Electronics on the Internet of Smart Grid Things (IoSGT) Architecture

Authors: L. Marques, P. Eugênio, L. Bastos, H. Santos, D. Rosário, E. Nogueira, et al.

Source: Journal of Internet Services and Applications, Vol. 14(1), pp. 124–135

Citations: 2

Year: 2023

Virtualized 5G Testbed using OpenAirInterface: Tutorial and Benchmarking Tests

Authors: M. Dória, V. Sousa, A. Campos, N. Oliveira, P. Eduardo, C. Lima, J. Guilherme, et al.

Source: Journal of Internet Services and Applications, Vol. 15(1), pp. 523–535

Citations: Not yet cited

Year: 2024

Conclusion :

Paulo Eugênio da Costa Filho is a strong candidate for the Best Researcher Award, particularly for awards that value practical innovation, interdisciplinary research, and technology for public good. His profile showcases a rare blend of technicaldepth, creative application, and community impact, all rooted in scientific rigor and hands-on implementation. With cntinued development in publication strategy and international networking, he has the potential to become a leading figure in applied computing and sustainable technology solutions not just in Brazil, but globally.

Hamna Baig | Artificial Intelligence | Young Researcher Award

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Ms. Hamna Baig | Artificial Intelligence | Young Researcher Award

Research Internee | COMSATS University Islamabad, Attock Campus | Pakistan

Hamna Baig 🎓 is a passionate and award-winning Electrical Engineering graduate from COMSATS University Islamabad, Attock Campus. A gold medalist 🥇 with a CGPA of 3.66, she blends academic brilliance with innovative research in AI, IoT, and robotics 🤖. Hamna’s dynamic work spans smart environments, RF sensing, and machine learning applications 💡. She has published multiple research papers 📚, led various technical projects, and participated in prestigious conferences 🏛️. Her leadership roles and technical writing expertise further reflect her versatility 🧠. Hamna aims to revolutionize engineering solutions through creativity, technology, and social impact 🌍.

Professional profile : 

Google Scholar

Orcid 

Summary of Suitability : 

Hamna Baig exemplifies the essence of a young and emerging researcher through her exceptional academic performance, innovative contributions to AI-driven engineering, and a prolific portfolio of research publications. A gold medalist in Electrical Engineering from COMSATS University Islamabad, she has demonstrated consistent excellence in both theoretical knowledge and practical application. With multiple high-impact publications, advanced project implementations, and recognized conference presentations, she brings outstanding promise to the future of intelligent systems and healthcare engineering. Her dedication to interdisciplinary innovation, backed by hands-on experience and leadership roles, showcases her as a rising star in engineering research.

🔹 Education & Experience :

📘 Education:

  • 🎓 B.Sc. Electrical Engineering, COMSATS University Islamabad, Attock Campus (2020–2024) – CGPA: 3.66/4.00, Gold Medalist 🏅

  • 📑 Final Year Project: AI-based Environmental Control Model for Smart Homes 🏠🤖

🧑‍💼 Experience:

  • 🧪 Internee, Electrical & Computer Engineering Dept., COMSATS, under PEC GIT Program (2024–Present)

  • ⚡ Internee, Ghazi-Barotha Hydro Power Plant (GBHPP), WAPDA (2023)

  • 🖋️ Technical Writer (Electrical/Electronics), CDR Professionals (2023–Present)

Professional Development :

Hamna Baig has actively pursued professional growth through certifications, leadership, and community engagement 🌱. She completed the prestigious “Machine Learning Specialization” by DeepLearning.AI 🤖, “Generative AI for Everyone” 🧠, and several tech courses from Stanford, Yonsei, and the University of Michigan via Coursera 🎓. As a proactive learner, she enhances her skills in AI, IoT, wireless communication, and public speaking 🎤. Hamna has held key roles such as President of the Sports Society 🏸, Co-Campus Director of AICP 🧑‍🔬, and VP of COMSATS Science Society. Her drive to uplift communities and advance technology sets her apart 🌟.

Research Focus : 

Hamna’s research centers on the integration of Artificial Intelligence and Machine Learning into real-world electrical and biomedical systems 🤖🧠. She explores SDR-based gait monitoring for Parkinson’s patients 🧓, AI-controlled environmental systems for energy-efficient smart homes 🌡️, and intelligent robotic applications in agriculture 🤖🍎. Her work emphasizes non-invasive health monitoring using RF sensing 🛏️ and AI-powered automation solutions. She is deeply invested in translating complex algorithms into practical, user-centric applications that elevate health, comfort, and productivity ⚡. Her interdisciplinary approach bridges electrical engineering with innovative computing solutions 🔌📊.

Awards & Honors :

  • 🏆 Awards & Certificates:

    • 🥇 Gold Medalist, COMSATS University Islamabad (2024)

    • 🧾 Certificate of Gratitude, ICTIS Conference, UET Peshawar (2024)

    • 📜 Certificate of Gratitude, ICCSI Conference, University of Haripur (2024)

    • 🧠 ML Specialization Certificate, DeepLearning.AI – Stanford (2023)

    • 🧬 Generative AI for Everyone – DeepLearning.AI (2025)

    • 🧏‍♀️ Public Speaking Specialization – University of Michigan (2024)

    • 📶 Wireless Communications Course – Yonsei University (2024)

    • 🎓 Prime Minister’s Youth Laptop Scheme Awardee (2023)

    • 🥇 Winner – IoT Pick and Place Robotic Competition, COMSATS (2024)

    • 🧒 Student of the Year – COMSATS University, Attock (2023)

Publication Top Notes : 

  • • Title: Intelligent Frozen Gait Monitoring using Software Defined Radio Frequency Sensing
    Citation: Electronics, 14(8), 1603, 2025
    Authors: Khan, M. B., Baig, H., Hayat, R., Tanoli, S. A. K., Rehman, M., Thakor, V. A., & Haider, D.
    Year: 2025

  • • Title: Machine Learning-Based Estimation of End Effector Position in Three-Dimension Robotic Workspace
    Citation: IJIST Journal (Impact Factor: 4.312)
    Authors: Baig, H., Ahmed, E., Jadoon, I., & Pakistan, K. C. A.
    Year: 2024

  • • Title: A Robotic Approach for Fruit Harvesting with Machine Learning-Based Joint Angles Prediction
    Citation: Submitted to ICCSI – International Conference on Computational Sciences and Innovations
    Authors: Baig, H., Baig, A.A, Ahmed, E., Jadoon, I., & Pakistan
    Year: 2024

  • • Title: Artificial Intelligence Based Adaptive Fan Control in Office Settings for Energy Efficiency
    Citation: Submitted to ICCIS – Proceedings to Springer Journal
    Authors: Baig, H.
    Year: 2024

  • • Title: A Robotic Arm Based Intelligent Biopsy System
    Citation: Submitted to ICCIS – Kohat University, Springer Proceedings
    Authors: Baig, H.
    Year: 2024

  • • Title: Design of an Intelligent Wireless Channel State Information Sensing System to Prevent Bedsores
    Citation: IEEE Sensors Journal (Under Review)
    Authors: Baig, H.
    Year: 2024

  • • Title: Enhancing Home Comfort and Energy Consumption with an Artificial Intelligence-Based Environmental Sensing Control Model
    Citation: PeerJ (Computer Science) (Under Review)
    Authors: Baig, H.
    Year: 2024

  • • Title: Breathing Techniques Redefined: The Pros and Cons of Traditional Methods and the Promise of SDRF Sensing
    Citation: Elsevier – Digital Communications and Networks (Under Review)
    Authors: Baig, H.
    Year: 2024

Conclusion : 

  • Hamna Baig not only meets but exceeds the expectations of a Young Researcher Award recipient. Her innovative mindset, research productivity, and real-world problem-solving approach make her an ideal candidate. Her work is not just academically sound but socially impactful—especially in the domains of healthcare and automation. She is a beacon of excellence and innovation, representing the future of engineering research. 🌟

 

Arifur Rahman | Machine Learning | Best Researcher Award

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Arifur Rahman | Machine Learning | Best Researcher Award

Mr. Arifur Rahman, NAGAD Digital Financial Service, Bangladesh

Arifur Rahman 🎓 is a passionate researcher and software engineer from Bangladesh 🇧🇩, specializing in Machine Learning 🤖, Deep Learning 🧠, NLP 📚, and Bioinformatics 🧬. A graduate of KUET in Computer Science and Engineering 💻, he has excelled in both academia and industry. Currently, he serves as a Full Stack Developer 🧑‍💻 at NAGAD Digital Financial Service, contributing to innovative supply chain projects. Arifur is also an active researcher with several IEEE and Elsevier publications 📝, and has earned recognition in programming contests 🏆. His dedication to applied AI and system development showcases a unique blend of technical and research excellence 🚀.

🌍 Professional Profile

Google Scholar

🎓 Education

  • 🎓 B.Sc. in Computer Science and Engineering, KUET (2018 – 2023)

    • 📊 CGPA: 3.35/4.00; Final Two Years CGPA: 3.73/4.00

  • 🏫 Noakhali Govt. College (2015 – 2017)

    • 🌟 GPA: 5.00/5.00 (Cumilla Board Scholarship Winner)

👨‍💼 Experience

  • 🧑‍💻 Software Engineer, NAGAD Digital Financial Service (Feb 2024 – Present)

    • 💼 Full Stack Developer in PRISM (Supply Chain Management) using Flutter, Java Spring Boot, PHP

  • 🔬 Research Engineer (NLP), AIMS Lab, United International University (Oct 2023 – Feb 2024)

    • 📚 Worked on Recommender Systems and published in IEEE Access

  • 👨‍💻 Software Engineer, Nazihar IT Solution Ltd. (May 2023 – Sep 2023)

    • 💻 Developed subroutines using Temenos Java Framework for banking solutions

🏆 Suitability for Best Researcher Award

Mr. Arifur Rahman is an exceptional candidate for the Best Researcher Award, demonstrating strong potential and proven excellence in research and innovation across emerging domains such as Machine Learning, Deep Learning, Natural Language Processing (NLP), Health Informatics, and Biomedical Engineering. His impactful research, hands-on development skills, and academic contributions distinguish him as a rising leader in computational science and applied AI.

🔹 Professional Development 

Arifur Rahman 🚀 is actively involved in both industry-driven software engineering and cutting-edge academic research 📖. His journey has been marked by continuous professional growth, serving in roles that merge development and innovation 💼. At NAGAD, he contributes as a Full Stack Developer 🌐, while his time at AIMS Lab sharpened his NLP and recommender system expertise 🧠. He has also contributed as a reviewer in IEEE conferences 📑, showcasing his engagement with the global research community. Arifur’s hands-on experience with technologies like Flutter, Java Spring Boot, ReactJS, and blockchain 🔗 highlights his dynamic skill set and commitment to excellence ⭐.

🔍 Research Focus

Arifur Rahman’s research focuses on a diverse range of AI-powered technologies 🧠, with core interests in Machine Learning, Deep Learning, and Natural Language Processing 🤖📚. His work explores real-world applications such as health informatics 🏥, bioinformatics 🧬, fake news detection, and blockchain security 🔐. Through his IEEE and Elsevier publications, he has addressed critical problems in diabetic retinopathy diagnosis, DNA sequence classification, and higher education recommendation systems 🎓. His blend of theoretical innovation and practical solutions ensures his research contributes to both scientific progress and societal impact 🌍.

🏅 Awards and Honors

  • 🎖️ Dean’s List Award at KUET for outstanding academic performance (2019–2020)

  • 🥇 Intra-KUET Programming Contest 2021 – 3rd Place 🧠💡

  • 🥈 Intra-KUET Programming Contest 2019 – 6th Place 🧠

  • 🥉 Divine IT Qualification Round – Rank 10 (Nov 2023) 💻

  • 🏆 TechnoNext Technical Coding Test 2023 (Fresher) – Rank 7 🔢

📊 Publication Top Notes

  1. Recommender system in academic choices of higher education – IEEE Access (2024) 📚5 🎓🤖
  2. Advancements in breast cancer diagnosis… with PCA, VIF – 6th Int. Conf. on Electrical Engineering and Info (2024) 📚2 🧬🩺📊
  3. Optimizing SMS Spam Detection… Voting Ensembles & Bi-LSTM – 5th Int. Conf. on Data Intelligence and Cognitive (2024) 📚1 📱📩🧠
  4. Cracking the Genetic Codes: DNA Sequence Classification… – Int. Conf. on Advances in Computing, Communication (2024) 📚1 🧬🧪🧠
  5. Secure Land Purchasing using… Multi-Party Skyline Queries – 26th Int. Conf. on Computer and Info Tech (2023) 📚1 🌍🏠🔐
  6. Fake News Detection… Soft and Hard Voting Ensemble – Procedia Computer Science (2025) 📚– 📰❌🗳️

Mr. Rishik Gupta | Computer Vision | Best Researcher Award

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Mr. Rishik Gupta | Computer Vision | Best Researcher Award

Mr. Rishik Gupta, Texas A&M University, United States

Mr. Rishik Gupta is an emerging talent in the field of Computer Science, currently pursuing his Master’s degree at Texas A&M University, USA. With a strong foundation built at Maharaja Surajmal Institute of Technology and the Indian Institute of Technology Madras, he has shown exceptional promise in machine learning, natural language processing, computer vision, and audio signal processing. His professional experience includes impactful roles at the Defence Research and Development Organization (DRDO), AI Shala Technologies, and Growna EdTech, where he demonstrated his ability to develop high-performance AI systems. Rishik has authored research papers, developed NLP models with over 95% accuracy, and created scalable software solutions. His academic journey is marked by dedication, innovation, and cross-disciplinary collaboration. 🚀📚💡

🌍 Professional Profile 

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

Mr. Rishik Gupta is highly deserving of the Best Researcher Award due to his outstanding contributions to applied machine learning, natural language processing, and intelligent systems. His work at DRDO led to the development of high-accuracy traffic classification models, while at AI Shala, he designed an NLP model achieving 95%+ accuracy in distinguishing AI-generated text. Rishik demonstrates not only technical skill but innovation and academic rigor, reflected in his publications and custom dataset designs. He bridges academia and industry with real-world applications and research, and his custom GPT model and smart attendance system further showcase his creativity and problem-solving ability. Rishik represents the next generation of researchers pushing the frontier of AI and computer science. 🧠🏅📈

🎓 Education 

Mr. Rishik Gupta is currently enrolled in the Master of Computer Science program at Texas A&M University (Aug 2024 – May 2026), where he continues to deepen his expertise in artificial intelligence and software systems. He completed his Bachelor of Technology in Computer Science and Engineering from Maharaja Surajmal Institute of Technology, Delhi (2020–2024). Simultaneously, he studied at the Indian Institute of Technology Madras from Sep 2021 to Dec 2023, gaining exposure to advanced courses and research environments. His academic journey reflects a strategic blend of technical depth, cross-institutional learning, and interdisciplinary exploration in AI, machine learning, and computer vision. 🎓🧑‍💻📖

💼 Experience 

Rishik has amassed hands-on research and development experience across prominent organizations. At DRDO, he built advanced machine learning models for network traffic classification, collaborating with senior scientists to improve accuracy and efficiency. At AI Shala Technologies, he designed an innovative NLP model capable of detecting AI-generated content, integrating BERT and perplexity-based analysis. His tenure at Growna EdTech showcased his software engineering skills, where he developed a scalable Android application with significant business impact. Each role highlights his interdisciplinary talent in ML, NLP, software development, and project execution, bridging theoretical knowledge with practical application. 🧑‍🔬💻🤝

🏅 Awards and Honors 

While still early in his academic and professional career, Rishik has been recognized for his high-impact work through collaborative research publications, top internship selections, and notable project contributions. His model at DRDO surpassed standard benchmarks with over 90% accuracy, and his AI Shala project achieved 95% accuracy, both earning internal commendation. His software at Growna EdTech played a pivotal role in securing a major client, boosting revenue by 60%, a rare feat for an intern-led project. His academic excellence has also earned him admission to the prestigious Texas A&M University and IIT Madras programs. More accolades are expected as his promising career progresses. 🥇🏆📜

🔬 Research Focus

Mr. Gupta’s research is focused on the intersection of Machine Learning, Efficient Search & Retrieval, Natural Language Processing, Computer Vision, and Audio Signal Processing. His work involves both theoretical exploration and real-world implementation of AI systems, including generative models, transformer architectures, semantic analysis, and facial recognition systems. He emphasizes the creation of scalable, high-performance solutions such as smart attendance tracking using facial recognition and custom GPT-style language models. His interest in audio signal processing and text classification expands his multidisciplinary relevance, while his projects reflect innovation, practical utility, and algorithmic efficiency. He seeks to create AI tools that are impactful, interpretable, and adaptable to varied use cases. 🤖📡🗣️📷🎶

📊 Publication Top Notes

  • ASKSQL: Enabling Cost-Effective Natural Language to SQL Conversion for Enhanced Analytics and Search

    • Year: 2025

  • Integrated Smart Attendance Tracker Using YOLOv8 and FaceNet with Spotify ANNOY

    • Year: 2024

  • Pronunciation Scoring With Goodness of Pronunciation and Dynamic Time Warping

    • Year: 2023

  • SwinAnomaly: Real-Time Video Anomaly Detection Using Video Swin Transformer and SORT

    • Year: 2023

 

 

Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award-3904

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Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award

Prof. Dr. Dongxing Song, Zhengzhou University, China

Prof. Dr. Dongxing Song is an innovative researcher in power engineering and thermophysics, currently serving as a Research Fellow at Zhengzhou University’s School of Mechanics and Safety Engineering. He earned his doctoral degree from Tsinghua University and previously studied at Xi’an Jiaotong University and Central South University. His expertise lies in nanofluid dynamics, ionic thermoelectric conversion, and energy system optimization. Dr. Song’s research integrates machine learning with thermodynamics, pushing boundaries in sustainable energy technologies. His work has been published in top-tier journals such as Joule and Cell Reports Physical Science, gaining recognition for both originality and technical depth. Driven by scientific rigor and curiosity, Dr. Song continues to shape future solutions for clean energy and advanced material systems. ⚛️🔬🌱

🌍 Professional Profile 

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

Prof. Dr. Dongxing Song is a standout candidate for the Best Researcher Award due to his cutting-edge work in ionic thermoelectric energy conversion and nanoscale heat transfer. His publications in high-impact journals, including Joule and Cell Reports Physical Science, demonstrate his role in shaping the future of clean and efficient energy generation. Dr. Song has independently led national-level research projects supported by the NSFC and China Postdoctoral Science Foundation, focusing on ion-electron coupling mechanisms and dynamic heat-mass transport. His interdisciplinary approach—blending thermophysics, machine learning, and materials science—makes him a trailblazer in green energy innovation. His research not only advances scientific understanding but also offers scalable solutions for low-grade waste heat recovery. 🔋🏅🌍

🎓 Education

Prof. Dr. Dongxing Song holds a robust academic background in power engineering and thermophysics. He completed his Ph.D. at Tsinghua University (2018–2022) under Prof. Weigang Ma, following his Master’s studies at Xi’an Jiaotong University (2015–2018) under Prof. Dengwei Jing. His foundational education in Thermal Energy and Power Engineering was completed at Central South University (2011–2015), where he was mentored by Dengwei Jing and Jianzhi Zhang. Throughout his academic journey, Dr. Song developed deep expertise in energy conversion, ionic transport, and thermodynamic modeling. His cross-institutional training at China’s most prestigious engineering schools laid the groundwork for his innovative and interdisciplinary research in the clean energy domain. 🎓📘⚙️

💼 Experience

Since February 2022, Dr. Dongxing Song has served as a Research Fellow at the School of Mechanics and Safety Engineering, Zhengzhou University, contributing significantly to ionic thermoelectric research. He previously pursued advanced research at Tsinghua University, one of China’s top engineering institutions, from 2018 to 2022. His earlier academic appointments include graduate research at Xi’an Jiaotong University and Central South University, where he gained hands-on experience in power engineering, energy optimization, and thermophysical modeling. In every role, Dr. Song has demonstrated scientific leadership, managing national-level projects and publishing influential research. His experience reflects a well-rounded career rooted in high-impact research and technological innovation in sustainable energy. 🧑‍🔬🔋📈

🏅 Awards and Honors

Prof. Dr. Dongxing Song has received prestigious grants and recognition from leading national institutions. He is the Principal Investigator of a National Natural Science Foundation of China (NSFC) Original Exploration Program Project, as well as multiple China Postdoctoral Science Foundation awards, including the Innovative Talents Grant (BX20220275). His work on ion thermoelectric conversion received a high recommendation from Joule Preview, marking him as a rising star in energy systems innovation. Dr. Song’s publications in top-impact journals and his ability to secure competitive funding reflect his academic excellence and research potential. These accolades highlight his position as a thought leader in the next generation of thermophysical science and energy innovation. 🥇🏛️📚

🔬 Research Focus

Dr. Dongxing Song’s research centers on the optimization of power generation systems for low-grade waste heat recovery, specifically using ion thermoelectric conversion and salt gradient power. He investigates the fundamental coupling between heat and ion transport and has derived a new expression for the ionic Seebeck coefficient, setting the stage for thermoelectric optimization. His studies also integrate nanofluidic heat transfer, solid-state ion battery transport, and machine learning to enhance the performance of sustainable energy devices. His broader focus includes nanoscale heat and mass transfer, where he explores transport mechanisms across interfaces using simulation and experimental validation. Dr. Song’s pioneering models are helping redefine energy recovery systems with enhanced efficiency and low environmental impact. 🔬♻️🧪

📊 Publication Top Notes

  • Design of Microchannel Heat Sink with Wavy Channel and Its Time-Efficient Optimization with Combined RSM and FVM Methods

    • Citations: 209

    • Year: 2016

  • Optimization of a Circular-Wavy Cavity Filled by Nanofluid under Natural Convection Heat Transfer

    • Citations: 194

    • Year: 2016

  • Optimization of a Lid-Driven T-Shaped Porous Cavity to Improve the Nanofluids Mixed Convection Heat Transfer

    • Citations: 138

    • Year: 2017

  • Prediction of Hydrodynamic and Optical Properties of TiO₂/Water Suspension Considering Particle Size Distribution

    • Citations: 87

    • Year: 2016

  • A Nitrogenous Pre-Intercalation Strategy for the Synthesis of Nitrogen-Doped Ti₃C₂Tₓ MXene with Enhanced Electrochemical Capacitance

    • Citations: 71

    • Year: 2021

 

Dr. Ryszard Ćwiertniak | Artificial Intelligence | Best Researcher Award

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Dr. Ryszard Ćwiertniak | Artificial Intelligence | Best Researcher Award

Dr. Ryszard Ćwiertniak, Krakow University of Economics, Poland

Dr. Ryszard Ćwiertniak is an accomplished expert in project management, specializing in agile methodologies, Design Thinking, and AI-driven innovation. He holds a PhD in Management and Quality Sciences from the University of Economics in Krakow and has a strong academic and professional background in administration, management, and electrical engineering. With extensive experience in research and teaching, he has contributed to the fields of digital transformation, e-learning, and Industry 4.0. As an IBM Design Thinking mentor and Early Warning Europe ambassador, he helps businesses implement cutting-edge solutions. His work spans academia, consulting, and applied research in AI and business process optimization.

🌍 Professional Profile:

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

Dr. Ryszard Ćwiertniak’s pioneering research in AI-driven project management, digital transformation, and innovation management makes him an outstanding candidate for the Best Researcher Award. His involvement in Erasmus+ projects, contributions to Industry 4.0, and mentorship in agile methodologies showcase his impact on academia and industry. His expertise in AI-based decision-making, personalized education, and digital business models has transformed organizational processes. With numerous peer-reviewed publications, a book, and a grant-winning project, his research advances the future of smart business ecosystems. His leadership in AI-powered business solutions and educational innovations solidifies his reputation as a top researcher in the field.

🎓 Education 

Dr. Ryszard Ćwiertniak earned his PhD in Management and Quality Sciences from the University of Economics in Krakow (2019), focusing on innovation management. He also holds a Master’s degree in Administration and Management from the University of Warsaw (1994). In addition, he has a background in electrical engineering, equipping him with a multidisciplinary approach to research. His academic journey reflects a deep commitment to combining management principles with technology, particularly in AI applications, e-learning, and agile business strategies. His education has laid the foundation for his expertise in digital transformation, business innovation, and advanced project management methodologies.

💼 Professional Experience 

Dr. Ćwiertniak currently serves as an academic teacher at Krakow University of Economics, specializing in technology and product ecology. Previously, he was the Rector’s Representative for Quality of Education and E-learning at the College of Economics and Computer Science (2020–2024). His role in the Early Warning Europe initiative highlights his expertise in digital business transformation. He also contributes to the Erasmus+ program, working on AI-powered educational solutions. As an IBM Design Thinking mentor, he facilitates agile project implementation. His professional engagements bridge academia and industry, driving innovation, AI adoption, and digital business strategies in various sectors.

🏅 Awards and Honors 

🔹 Early Warning Europe Ambassador (2021–Present) – Recognized for supporting digital business transformation.
🔹 Erasmus+ Research Grant Recipient – Contributed to AI-driven education models.
🔹 Ministerial Research Grant Winner (2021) – Awarded funding for advancing e-learning and digital education techniques.
🔹 IBM Design Thinking Mentor – Certified expert in guiding agile and innovative project execution.
🔹 Industry 4.0 & AI Innovation Contributor – Acknowledged for pioneering work in integrating AI with project management and digital marketing.
🔹 Invited Researcher at THWS Business School (2024) – Recognized for leadership in AI-based digital transformation.

His contributions to AI, project management, and education technology have earned him national and international acclaim.

🔬 Research Focus

Dr. Ćwiertniak’s research spans AI-driven project management, innovation strategies, digital transformation, and e-learning technologies. He explores Industry 4.0 applications, AI-based decision-making, and agile methodologies to optimize business processes. His focus on digital business models, social media analytics, and e-commerce strategies has redefined marketing and management practices. Through Design Thinking and AI integration, he enhances project execution efficiency. His research also covers personalized education using AI, ensuring smarter, data-driven learning environments. As an expert in AI-powered business solutions, he contributes to making organizations more adaptable and efficient in an era of rapid technological advancements.

📊 Publication Top Notes:

  1. Rola potencjału innowacyjnego w modelach biznesowych nowoczesnych organizacji – próba oceny

    • Citations: 11
    • Year: 2015

  2. Zarządzanie portfelem projektów w organizacji: Koncepcje i kierunki badań

    • Citations: 4
    • Year: 2018

  1. Addressing students’ perceived value with the virtual university concept

    • Citations: 3
    • Year: 2022

  2. Kształtowanie portfela projektów w zarządzaniu innowacjami

    • Citations: 2
    • Year: 2018

  1. The concept of project evaluation in the implementation of innovation

    • Citations: 1
    • Year: 2020

 

 

Dr. Yingbin Wang | Artificial Intelligence | Best Researcher Award

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Dr. Yingbin Wang | Artificial Intelligence | Best Researcher Award

Dr. Yingbin Wang, Xi’an Institute of Space Radio Technolog, China

Dr. Yingbin Wang is a leading researcher in space microwave communication, detection, and AI-driven signal processing. He earned his Ph.D. in Electronic Science and Technology from Xidian University in 2022 and currently serves as a Senior Engineer at the National Key Laboratory of Science and Technology on Space Microwave at the Xi’an Institute of Space Radio Technology. His research spans Integrated Sensing and Communication (ISAC), deep learning, and anti-jamming satellite systems. With over ten high-impact publications and contributions to national-level R&D projects, Dr. Wang is shaping the future of space-based communication and intelligent sensing. 🚀📡

🌍 Professional Profile:

Google Scholar

🏆 Suitability for the Best Researcher Award

Dr. Yingbin Wang is a highly qualified candidate for the Best Researcher Award, given his significant contributions to space microwave communication and AI-powered signal processing. His expertise in satellite-terrestrial integration, space-based radar target detection, and anti-jamming satellite systems plays a crucial role in advancing global space technology. With publications in top-tier IEEE journals, participation in national R&D projects, and contributions to cutting-edge ISAC applications, Dr. Wang is at the forefront of next-generation communication research. His work in AI-driven remote sensing is revolutionizing the field, making him a distinguished and deserving nominee. 🏆🚀

🎓 Education

Dr. Yingbin Wang pursued his entire higher education at Xidian University, China, a prestigious institution in electronic engineering and space communication. He obtained his Ph.D. in Electronic Science and Technology in June 2022, focusing on advanced space microwave systems and AI-enhanced signal processing. His doctoral research contributed to improving satellite communication resilience, radar detection, and deep learning applications in space technologies. Throughout his academic journey, he combined hardware engineering with AI-driven software models, enabling breakthroughs in integrated satellite-terrestrial communication. His strong foundation in electromagnetic waves, remote sensing, and computational intelligence defines his research excellence. 🎓📡🔬

💼 Experience 

Dr. Yingbin Wang is a Senior Engineer at the National Key Laboratory of Science and Technology on Space Microwave, Xi’an Institute of Space Radio Technology. His role involves leading research in space microwave communication, detection, and AI-driven signal optimization. He has contributed to major national R&D projects, including space-based radar target detection, anti-jamming satellite communication, and integrated sensing for satellite-terrestrial networks. His work on AI-based signal processing and deep learning models has significantly enhanced real-time space communication efficiency. His expertise in high-frequency electromagnetic applications and AI-powered satellite technology is instrumental in shaping the future of space communications. 🚀📶

🏅 Awards & Honors 

Dr. Yingbin Wang has received multiple recognitions for his contributions to space communication and AI-driven signal processing. His research in anti-jamming satellite networks has been awarded national-level research funding. He has received Best Paper Awards at leading IEEE conferences on signal processing and remote sensing. Additionally, his contributions to integrated satellite-terrestrial communication have been recognized by the National Science and Technology Innovation Program. As a reviewer for top IEEE journals, he actively contributes to the scientific community. His pioneering work in AI-enhanced space sensing continues to push the boundaries of satellite communication technologies. 🏆📡

🔬 Research Focus 

Dr. Yingbin Wang’s research spans Artificial Intelligence, communication, deep learning, and signal processing, with a strong emphasis on space microwave communication and detection. His work explores AI-driven radar target detection, anti-jamming satellite communication, and integrated sensing and communication (ISAC) systems. He develops machine learning models for real-time adaptive signal processing, enhancing satellite-terrestrial connectivity. His studies in neural network-driven space communication systems optimize data transmission efficiency in complex space environments. His research is critical for next-generation deep-space exploration, smart communication networks, and high-performance microwave technology, ensuring global connectivity and security in aerospace applications. 🚀📡🛰️

📖 Publication Top Notes

  1. SPB-Net: A Deep Network for SAR Imaging and Despeckling with Downsampled Data
    • Journal: IEEE Transactions on Geoscience and Remote Sensing
    • Publication Year: 2020
    • Citations: 27
  2. Lq-SPB-Net: A Real-Time Deep Network for SAR Imaging and Despeckling
    • Journal: IEEE Transactions on Geoscience and Remote Sensing
    • Publication Year: 2021
    • Citations: 8
  1. Multi-Scale and Single-Scale Fully Convolutional Networks for Sound Event Detection
    • Journal: Neurocomputing
    • Publication Year: 2021
    • Citations: 18
  2. MSFF-Net: Multi-Scale Feature Fusing Networks with Dilated Mixed Convolution and Cascaded Parallel Framework for Sound Event Detection
    • Journal: Digital Signal Processing
    • Publication Year: 2022
    • Citations: 12
  1. A Convex Optimization Algorithm for Compressed Sensing in a Complex Domain: The Complex-Valued Split Bregman Method
    • Journal: Sensors
    • Publication Year: 2019
    • Citations: 13

 

Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

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Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

Prof. Ching Yee Suen, Concordia University, Canada

Prof. Ching Yee Suen is a globally recognized expert in Pattern Recognition, AI, and Document Analysis. As the Founding Director and Co-Director of CENPARMI at Concordia University, he has shaped advancements in handwriting recognition, multiple classifiers, and font analysis. A Fellow of IEEE, IAPR, and the Royal Society of Canada, he has mentored 120+ graduate students and 100 visiting scientists. With 550+ research papers, 16 books, and an h-index of 74, his contributions are widely cited. His innovations power millions of devices worldwide. He has led $20M+ research projects, collaborated with global industries, and serves as an editor for top-tier journals.

🌍 Professional Profile:

Google Scholar

🏆 Suitability for Best Researcher Award 

Prof. Suen is an exceptional candidate for the Best Researcher Award due to his pioneering contributions in AI, pattern recognition, and handwriting analysis. His research has real-world impact, with millions of users benefiting from his handwriting recognition algorithms. He has received top international awards, including the King-Sun Fu Prize (2021) and ICDAR Award (2005). As a leading AI researcher, he has secured $20M+ in funding, supervised over 120 Ph.D. and master’s students, and led groundbreaking industrial collaborations. His global influence, leadership in AI, and outstanding research output make him a worthy recipient of this prestigious honor.

🎓 Education 

Prof. Ching Yee Suen holds a Ph.D. from the University of British Columbia (UBC), Vancouver, and a Master’s degree from the University of Hong Kong. His academic journey has been marked by a deep focus on Artificial Intelligence, Pattern Recognition, and Computational Vision. His early research laid the foundation for his groundbreaking work in handwriting recognition, document analysis, and AI-powered classification systems. He has spent sabbatical leaves at MIT, McGill University, Ecole Polytechnique, and IBM, further expanding his expertise. His academic credentials have established him as a leading scholar in AI and pattern recognition on a global scale.

💼 Experience 

With a career spanning 50+ years, Prof. Suen has held key leadership roles at Concordia University, serving as Chairman of Computer Science, Associate Dean (Research), and Concordia Chair in AI & Pattern Recognition. He is the Founding Director and Co-Director of CENPARMI, where he has driven cutting-edge research. He has supervised 120+ graduate students and collaborated with top institutions worldwide. As a consultant to Microsoft, Xerox, Canada Post, and the US Congress, his work has had real-world impact. His editorial leadership in top AI journals and conference organization further cements his global influence in the research community.

🏅 Awards and Honors

Prof. Suen’s excellence is recognized globally, earning him top honors in AI and pattern recognition. He received the King-Sun Fu Prize (2021) 🏆, the ICDAR Award (2005) 🎖️, and the Elsevier Distinguished Editorial Award (2016)📜. His Concordia Lifetime Research Achievement Award (2008) and Teaching Excellence Award (1995) 🎓 highlight his impact in academia. Internationally, he was honored with the Gold Medal from the University of Bari, Italy (2012) 🥇. As a Fellow of IEEE, IAPR, and the Royal Society of Canada, his contributions to AI, document analysis, and handwriting recognition are celebrated at the highest levels.

🔬 Research Focus 

Prof. Suen specializes in Pattern Recognition, Artificial Intelligence, and Document Analysis. His innovations in handwriting recognition, fake coin detection, license plate recognition, and multi-classifier systems have transformed industry applications. His research integrates AI, deep learning, and image processing to solve complex problems in computer vision, natural language processing, and fraud detection. His high-impact contributions are widely used in mobile devices, banking security, and postal services. His multi-disciplinary approach in AI has led to real-world solutions adopted by Microsoft, Bell Canada, Canada Post, and global tech firms, making him a pioneer in intelligent pattern analysis.

📊 Publication Top notes:

  • Title: Developing Knowledge Management Metrics for Measuring Intellectual Capital
    • Year: 2000
    • Citations: 442
  • Title: Modified Hebbian Learning for Curve and Surface Fitting
    • Year: 1992
    • Citations: 322
  • Title: N-Gram Statistics for Natural Language Understanding and Text Processing
    • Year: 1979
    • Citations: 315
  • Title: Analysis and Design of a Decision Tree Based on Entropy Reduction and Its Application to Large Character Set Recognition
    • Year: 1984
    • Citations: 176
  • Title: Large Tree Classifier with Heuristic Search and Global Training
    • Year: 1987
    • Citations: 102

 

 

Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

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Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

Dr. Vamsi Inturi, Chaitanya Bharathi Institute of Technology, India

Dr. Vamsi Inturi is an accomplished researcher and academic specializing in Mechanical Engineering, with expertise in fault diagnosis, health monitoring, and digital twin technologies. He earned his Ph.D. from BITS Pilani, focusing on adaptive condition monitoring for wind turbine gearboxes. With experience spanning postdoctoral research at Trinity College Dublin and academic roles in India, he has made significant contributions to machine learning applications in engineering. He has received prestigious awards, including the Best Paper Award at the 43rd International JVE Conference. His research integrates AI and signal processing to enhance predictive maintenance and mechanical system reliability.

Professional Profile:

Google Scholar

Orcid

Scopus

🏆 Suitability for Award 

Dr. Vamsi Inturi is an outstanding candidate for the Best Researcher Award, given his pioneering work in mechanical fault diagnosis, machine learning, and predictive maintenance. His research significantly impacts renewable energy systems, particularly wind turbines, optimizing efficiency and reducing downtime. Recognized with international travel grants, research fellowships, and best paper awards, he has demonstrated academic excellence and innovation. His work in digital twins and signal processing has been published in high-impact journals, reinforcing his status as a leader in mechanical engineering research. His commitment to advancing engineering solutions makes him highly deserving of this prestigious recognition.

🎓 Education

Dr. Vamsi Inturi holds a Ph.D. in Mechanical Engineering from BITS Pilani (2016-2020), where he developed an adaptive condition monitoring scheme for wind turbine gearboxes under the supervision of Prof. Sabareesh G R and Prof. Pavan Kumar P. He earned his M.Tech in Machine Design from JNTU Kakinada (2012-2014), focusing on modeling process parameters in milling aluminum composites. His academic journey began with a Bachelor’s in Mechanical Engineering, followed by extensive research in fault diagnosis and mathematical modeling. His interdisciplinary expertise bridges mechanical systems, AI-driven analytics, and sustainable energy solutions, shaping advancements in mechanical diagnostics.

👨‍🏫 Experience 

Dr. Vamsi Inturi has a diverse academic and research career. He is currently an Assistant Professor at CBIT(A), Hyderabad, specializing in engineering drawing, robotics, and mechanical systems. Previously, he was a Postdoctoral Researcher at Trinity College Dublin, managing the REMOTE-WIND project. He also served as a Research Scholar at BITS Hyderabad, working on mechanical vibrations and fault diagnosis. His teaching experience includes faculty positions at PACEITS and QISIT, mentoring students in mechanical design and computational modeling. With extensive research output in AI-driven diagnostics, he plays a crucial role in advancing predictive maintenance strategies.

🏅 Awards and Honors

Dr. Vamsi Inturi has received multiple accolades for his research excellence. He was awarded the Best Paper Award at the 43rd International JVE Conference (2019) and recognized for outstanding Ph.D. performance (2017-18). As a CSIR Senior Research Fellow (2019-20), he contributed to groundbreaking studies in mechanical diagnostics. He also secured a CSIR International Travel Grant (2019) to present his research globally. Additionally, he was elected a campus-level senate member for Ph.D. programs (2018-20). His expertise has made him a sought-after speaker and session co-chair at international mechanical engineering conferences.

🔍 Research Focus 

Dr. Vamsi Inturi’s research centers on health monitoring, fault diagnosis, and AI-driven mechanical analytics. His work integrates machine learning, signal processing, and digital twin technologies to enhance predictive maintenance in mechanical systems, particularly wind turbines. He specializes in mathematical modeling and deep learning applications for fault detection, helping industries reduce operational risks. His studies on adaptive condition monitoring schemes for gearboxes have led to innovative diagnostic frameworks. His interdisciplinary approach merges mechanical engineering with computational intelligence, making significant contributions to sustainable energy and industrial automation.

📚 Publication Top Notes:

  • Title: Comparison of Condition Monitoring Techniques in Assessing Fault Severity for a Wind Turbine Gearbox Under Non-Stationary Loading
    • Volume: 124
    • Citations: 102
  • Title: Evaluation of Surface Roughness in Incremental Forming Using Image Processing-Based Methods
    • Year: 2020
    • Citations: 68
  • Title: Integrated Condition Monitoring Scheme for Bearing Fault Diagnosis of a Wind Turbine Gearbox
    • Year: 2019
    • Citations: 63
  • Title: Comprehensive Fault Diagnostics of Wind Turbine Gearbox Through Adaptive Condition Monitoring Scheme
    • Year: 2021
    • Citations: 45
  • Title: Optimal Sensor Placement for Identifying Multi-Component Failures in a Wind Turbine Gearbox Using Integrated Condition Monitoring Scheme
    • Year: 2022
    • Citations: 30

 

Dr. Punitha A | Machine Learning | Women Researcher Award

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Dr. Punitha A | Machine Learning | Women Researcher Award

Dr. Punitha A | K Ramakrishnan College of Technology | India

Dr. A. Punitha is a distinguished professor with 20 years of experience in the Electronics and Communication Engineering field. She is currently a faculty member at M.A.M School of Engineering, Trichy, where she also serves in leadership roles like NBA Coordinator, Head of the Department, and R&D In-Charge. Dr. Punitha is highly involved in research, especially in AI, IoT, and machine learning applications, and has received multiple research grants. Her work includes real-time monitoring systems, intrusion detection, and bio mask development. She is a prolific academic, with numerous publications and active contributions to conferences 📚👩‍🏫🤖.

Professional Profile:

SCOPUS

Suitability for Women Researcher Award

Dr. A. Punitha is highly suitable for the Women Researcher Award due to her extensive experience, leadership in academia, and significant contributions to the fields of Electronics and Communication Engineering, particularly in cutting-edge technologies such as AI, IoT, and machine learning.Dr. Punitha’s research focuses on innovative and impactful fields such as AI, IoT, and machine learning applications. She has worked on various cutting-edge projects, including real-time monitoring systems, intrusion detection systems, and bio mask development, which directly address real-world challenges. Her work in these domains exemplifies her contribution to advancing technology and creating solutions that have the potential to significantly benefit society.

Education and Experience

  • Ph.D. in Electronics and Communication Engineering 🎓
  • M.E. in Electronics and Communication Engineering 🎓
  • Total Experience: 20 Years ⏳
  • NBA Coordinator & Head of Department of ECE 🏫
  • R&D In-Charge, MAMSE 🧪
  • IIC Convener & Innovation Ambassador 🚀
  • International Conference Coordinator 🌍
  • Japanese Language Training Coordinator 🇯🇵
  • Coordinated AICTE and Tamil Nadu Science funding projects 💸

Professional Development

Dr. A. Punitha is an accomplished academic who actively contributes to the growth of her department and the institution. She has played a significant role in organizing faculty development programs, seminars, and workshops. Her involvement in innovation and research is evident through her leadership in receiving multiple grants, such as the Rs. 3.5 lakh AICTE ATAL fund and Tamil Nadu Science and Technology funds. Dr. Punitha has also acted as a resource person in webinars and conferences, discussing vital topics such as NEP 2020 and OBE. Her dedication to improving teaching quality and research at MAMSE remains evident 🌱📚💡.

Research Focus

Dr. A. Punitha’s research is centered around leveraging advanced technologies like AI, IoT, and machine learning to solve real-world problems. Her work explores areas such as intrusion detection in wireless sensor networks, brain tumor detection using CNN, and real-time monitoring systems like drowsy driving detection. She is also focusing on developing bio masks for sanitization and enhancing food processing in Industry 5.0 using AI. Dr. Punitha aims to create innovative solutions that contribute to both the academic and practical fields of technology 🌐🤖🔬.

Awards and Honors

  • Received Rs. 3.5 Lakh from AICTE ATAL for Faculty Development Program (2024) 💰
  • Funded Rs. 2.8 Lakh by Tamil Nadu Science and Technology for “Bio Mask Project” 💡
  • Awarded Rs. 20,000 for “Intra Project Expo 2021” by Tamil Nadu Science and Technology 🎉
  • Webinar Resource Person for “NEP 2020” and “OBE” at MAMSE 🎤
  • Co-principal Investigator for AICTE and Tamil Nadu Science-funded projects 🏆
  • Acted as Organizing Committee Member for National Conference with CSIR funding (Rs. 50,000) 🗣️

Publication Top notes:

  • “Dynamically stabilized recurrent neural network optimized with intensified sand cat swarm optimization for intrusion detection in wireless sensor network”
  • “Enhancing the Food Processing in Industry 5.0 Based on Artificial Intelligence”– Cited by: 1️⃣
  • “REAL TIME MONITORING AND DETECTION OF DROWSY DRIVING”
  • “Smart Method for Tollgate Billing System Using RSSI”  – Cited by: 3️⃣
  • “Privacy preservation and authentication on secure geographical routing in VANET” – Cited by: 6️⃣
  • “Secure group authentication technique for VANET” – Cited by: 5️⃣
  • “Location verification technique for secure geographical routing in VANET” – Cited by: 2️⃣