Arifur Rahman | Machine Learning | Best Researcher Award

Published on by Network Awards

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) 📚– 📰❌🗳️

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

Published on by Network Awards

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. Han Wang | Artificial Intelligence | Best Researcher Award

Published on by Network Awards

Dr. Han Wang | Artificial Intelligence | Best Researcher Award

Dr. Han Wang, China Academy of Safety Science and Technology, China

Wang Han is an accomplished engineer and researcher specializing in mechanical engineering, control systems, and predictive maintenance. With a strong academic foundation and a proven track record of innovative research, Wang has made significant contributions to the fields of fault diagnosis, structural health monitoring, and advanced control methodologies. His work reflects a commitment to addressing complex engineering challenges through cutting-edge research and practical applications.

Profile:

Scopus

Education:

Wang Han’s academic journey began at Yanshan University, where he earned his Bachelor’s degree, followed by a Master’s degree from the same institution. His passion for advancing engineering knowledge led him to Beijing University of Chemical Technology, where he completed his Doctorate. This solid academic background has equipped him with a deep understanding of both theoretical principles and practical engineering applications. 🎓

Experience:

Since September 2029, Wang Han has been serving as an engineer at the China Academy of Safety Science and Technology, where he applies his research expertise to develop advanced safety technologies and engineering solutions. His previous academic and research roles have honed his skills in experimental design, data analysis, and innovative problem-solving, positioning him as a leader in his field. 🏗️

Research Interests:

Wang Han’s research interests are diverse, encompassing predictive maintenance, bearing fault diagnosis, control engineering, and advanced modeling techniques. He focuses on developing predictive models using deep learning, improving fault detection methods in mechanical systems, and designing resilient control algorithms for industrial applications. His work contributes to enhancing the reliability and efficiency of critical engineering systems. 🔬

Awards:

While Wang Han’s contributions are primarily recognized through his research publications and patents, his innovative work has significantly impacted engineering practices. His dedication to advancing safety science and technology has been acknowledged within academic and professional circles, showcasing his role as a thought leader in his field. 🏆

Publications:

Wang Han has authored several influential publications in reputable journals, highlighting his expertise in engineering research. Here are some of his key works:

  1. “Research on Two-Dimensional Digital Map Modeling Method Based on UAV Aerial Images” (2025) – Applied Sciences 🌍 (Cited by 18 articles)
  2. “A Predictive Sliding Local Outlier Correction Method with Adaptive State Change Rate Determining for Bearing Remaining Useful Life Estimation” (2022) – Reliability Engineering & System Safety ⚙️ (Cited by 45 articles)
  3. “A Novel Multiscale Deep Health Indicator with Bidirectional LSTM Network for Bearing Performance Degradation Trend Prognosis” (2020) – Shock and Vibration 🚀 (Cited by 37 articles)
  4. “Experimental Research on Predictive Fuzzy PID Control in Atmospheric and Vacuum Distillation Unit” (2020) – Control Engineering 🔍 (Cited by 29 articles)
  5. “Limited Fault Data Augmentation with Compressed Sensing for Bearing Fault Diagnosis” (2023) – IEEE Sensors Journal 📡 (Cited by 33 articles)
  6. “Multiple Time-Frequency Curve Classification for Tacho-Less and Resampling-Less Compound Bearing Fault Detection Under Time-Varying Speed Conditions” (2021) – IEEE Sensors Journal 🛠️ (Cited by 40 articles)
  7. “An Adaptive State Change Rate Determining Method for Bearing Fault Diagnosis” (2021) – Journal of Mechanical Science 🏭 (Cited by 25 articles)

Conclusion:

Wang Han’s academic achievements, innovative research, and contributions to engineering sciences position him as an outstanding candidate for the Best Researcher Award. His work not only advances theoretical knowledge but also translates into practical solutions that enhance the safety, efficiency, and reliability of engineering systems. Through his publications, patents, and engineering contributions, Wang Han continues to inspire the next generation of researchers and practitioners in the field. 🌟

Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

Published on by Network Awards

Dr. Abdulrahman Alnaim | Technology | Excellence in Research Award

Dr. Abdulrahman Alnaim | Technology – Associate Professor at King Faisal University, Saudi Arabia

Dr. Abdulrahman Khalid Alnaim is an accomplished academic and researcher specializing in computer science and information security. With a strong foundation in computer information systems and management information systems, he has dedicated his career to advancing research in emerging technologies such as cybersecurity, cloud computing, and network architecture. His work is characterized by innovative approaches to securing next-generation networks and optimizing system performance, reflecting a commitment to both academic excellence and practical applications in the tech industry.

Profile:

Google Scholar

Education:

Dr. Alnaim earned his Ph.D. in Computer Science from Florida Atlantic University, USA, where he focused on developing secure and efficient computing models. He also holds a Master’s in Management Information Systems from Nova Southeastern University, USA, which enriched his understanding of integrating technology with business strategies. His academic journey began at King Faisal University, Saudi Arabia, where he completed his Bachelor’s degree in Computer Information Systems, laying the groundwork for his passion for research and technology. This diverse educational background has enabled him to approach complex problems with a multidisciplinary perspective.

Experience:

Dr. Alnaim has served at King Faisal University, Saudi Arabia, in various academic roles. Starting as a Teacher Assistant in 2012, he quickly advanced to become a Lecturer and later an Assistant Professor in the Management Information Systems Department within the School of Business. Throughout his tenure, he has contributed significantly to curriculum development, academic research, and student mentorship. His professional journey reflects a consistent commitment to fostering an environment of academic growth, research innovation, and knowledge dissemination.

Research Interests:

Dr. Alnaim’s research interests lie in the domains of cloud technologies, cybersecurity, and network architecture, with a particular focus on emerging trends like 5G/6G networks, network function virtualization (NFV), and edge computing. His work explores the development of robust security frameworks, optimized resource management strategies, and innovative architectures for next-generation networks. His research not only addresses theoretical challenges but also provides practical solutions for enhancing cybersecurity, system efficiency, and data integrity in complex digital environments.

Awards:

While Dr. Alnaim’s distinguished academic career is marked by numerous achievements, his contributions to research have earned him recognition within the academic community. His work has been cited extensively, reflecting its influence on contemporary studies in cybersecurity and network technologies. His dedication to research excellence is evident through his continuous pursuit of knowledge, innovative problem-solving, and commitment to advancing the field of computer science.

Publications 📚:

  1. “Zero Trust Strategies for Cyber-Physical Systems in 6G Networks” (2025) – Mathematics
    This paper discusses advanced security models tailored for cyber-physical systems in 6G environments. 🚀

  2. “Securing 5G Virtual Networks: A Critical Analysis of SDN, NFV, and Network Slicing Security” (2024) – International Journal of Information Security
    The article provides an in-depth analysis of security vulnerabilities and countermeasures in 5G networks. 🔐

  3. “Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework” (2024) – Sensors
    This research introduces the CyberGuard framework for enhancing trust management in edge and fog computing environments. 🌐

  4. “Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities” (2024) – Sensors
    A strategic approach to optimizing network slicing for IoT applications in smart cities. 🏙️

  5. “Classification of Alzheimer’s Disease Using MRI Data Based on Deep Learning Techniques” (2024) – Journal of King Saud University – Computer and Information Sciences
    This study leverages deep learning models to improve the early detection of Alzheimer’s disease using MRI data. 🧠

  6. “Machine-Learning-Based IoT–Edge Computing Healthcare Solutions” (2023) – Electronics
    Focuses on integrating machine learning with IoT and edge computing to enhance healthcare services. 💡

  7. “A Misuse Pattern for Modifying Non-Control Threats in NFV” (2022) – Future Internet
    Proposes a model to identify and mitigate non-control threats in network function virtualization environments. 🖥️

These publications have collectively garnered significant citations, underscoring their impact on academic research and industry practices. 📈

Conclusion:

Dr. Abdulrahman Khalid Alnaim exemplifies the qualities of an outstanding researcher, with a robust academic background, extensive research contributions, and a commitment to advancing the field of computer science and information security. His work in cybersecurity, cloud technologies, and network architecture has not only enriched academic discourse but also provided practical solutions to real-world challenges.

His innovative approach, combined with a strong publication record and active involvement in academic and research communities, makes him a deserving candidate for the Excellence in Research Award. Dr. Alnaim’s contributions reflect the values of academic rigor, intellectual curiosity, and a relentless pursuit of knowledge that this prestigious award seeks to honor.

Prof. Dr. Wen-Chung Tsai | Internet of Things | Best Researcher Award

Published on by Network Awards

Prof. Dr. Wen-Chung Tsai | Internet of Things | Best Researcher Award

Prof. Dr. Wen-Chung Tsai, National Taichung University of Science and Technology, Taiwan

Prof. Dr. Wen-Chung Tsai is an esteemed academic and researcher specializing in Embedded Systems, Internet of Things (IoT), Artificial Intelligence (AI), and Information Security. He earned his Ph.D. in Electronics Engineering from National Taiwan University in 2011 and has since contributed significantly to academia and industry. Dr. Tsai has held key roles at National Taichung University of Science and Technology and Chaoyang University of Technology, where he has mentored students and advanced research in wireless networks, software-hardware integration, and communication protocols. His industry experience includes serving as Deputy Manager at VIA Technologies and as a researcher at the Industrial Technology Research Institute (ITRI), Taiwan. With an extensive publication record, he continues to shape the future of computing and communication technologies.

🌍 Professional Profile 

Orcid

🏆 Suitability for Best Researcher Award 

Dr. Wen-Chung Tsai is a highly qualified candidate for the Best Researcher Award due to his outstanding contributions in Embedded Systems, IoT, AI, and Wireless Communication Protocols. His extensive experience in academia and industry enables him to conduct cutting-edge research while ensuring practical applications in technological advancements. His work in software-hardware integration and information security has paved the way for more secure and efficient digital ecosystems. Having served as an Associate Professor and Researcher, he has led multiple projects that enhance computing, connectivity, and cybersecurity. His ability to bridge theory with real-world implementation demonstrates his excellence in research, making him a deserving recipient of this prestigious award.

🎓 Education 

Dr. Wen-Chung Tsai pursued his Ph.D. in Electronics Engineering from National Taiwan University (2006-2011), where he focused on advanced computing architectures and embedded system design. Before that, he completed his Master’s in Electrical Engineering from National Cheng Kung University (1996-1998), where he specialized in networking protocols and wireless communication technologies. His strong academic foundation in software-hardware integration, AI-driven embedded systems, and IoT security has guided his research endeavors. With interdisciplinary expertise spanning computer science, electronics, and telecommunications, he has consistently contributed to technological innovation and engineering advancements. His academic journey is a testament to his commitment to pushing the boundaries of technology through rigorous research and innovation.

💼 Experience 

Dr. Wen-Chung Tsai has a rich professional background that blends academic excellence with industrial innovation. He currently serves as an Associate Professor at National Taichung University of Science and Technology (2022–Present). Prior to this, he was an Associate Professor at Chaoyang University of Technology (2020–2022) and an Assistant Professor in the same institution (2013–2020). His industry experience includes roles as Deputy Manager at VIA Technologies (2000–2009), Engineer at the Industrial Technology Research Institute (2011–2013), and Visiting Scholar at the University of Wisconsin-Madison (2010). His diverse experience in academia, research institutions, and corporate sectors enables him to drive impactful innovations in IoT, AI, and cybersecurity.

🔬 Research Focus

Dr. Wen-Chung Tsai’s research revolves around cutting-edge technologies in Embedded Systems, IoT, AI, and Cybersecurity. His work in software-hardware integration aims to develop optimized and secure computing environments. His contributions to wireless networks and communication protocols enhance the efficiency of 5G, IoT, and edge computing applications. His AI-driven security models focus on protecting IoT ecosystems from cyber threats. With expertise in real-time embedded computing, he works on power-efficient architectures for smart devices and intelligent networks. His multidisciplinary approach combines electronics, AI, and cybersecurity to develop scalable and resilient technological solutions for future smart cities, industrial automation, and digital transformation.

📊 Publication Top Notes 

  • Field-Programmable Gate Array-Based Implementation of Zero-Trust Stream Data Encryption for Enabling 6G-Narrowband Internet of Things Massive Device Access

    • Year: 2024

  • Anticipative QoS Control: A Self-Reconfigurable On-Chip Communication

    • Year: 2022

  • Automatic Key Update Mechanism for Lightweight M2M Communication and Enhancement of IoT Security: A Case Study of CoAP Using Libcoap Library

    • Year: 2022

  • Network-Cognitive Traffic Control: A Fluidity-Aware On-Chip Communication

    • Year: 2020

 

Prof. Jiantao Shi | Information Technology | Best Researcher Award

Published on by Network Awards

Prof. Jiantao Shi | Information Technology | Best Researcher Award

Prof. Jiantao Shi, Njing Tech University, China

Prof. Jiantao Shi is a distinguished researcher in control science and information technology, currently serving as a Professor at Nanjing Tech University. He holds a Ph.D. in Control Science and Engineering from Tsinghua University and has extensive experience in multi-robot cooperative control, fault diagnosis, and UAV learning control. His research has been published in leading IEEE journals, and he has significantly contributed to distributed system reliability. With a strong academic background and practical research experience, he has advanced intelligent control methodologies for autonomous systems. His contributions have positioned him as a leader in modern automation and robotics.

🌍 Professional Profile:

ORCID

🏆 Suitability for Best Researcher Award 

Prof. Jiantao Shi is an outstanding candidate for the Best Researcher Award due to his pioneering contributions to intelligent control systems, multi-robot cooperation, and UAV learning control. His work integrates cutting-edge AI techniques with control science, enabling the development of robust and fault-tolerant autonomous systems. With over 60 high-impact journal and conference papers in prestigious IEEE and SCI-indexed publications, he has made fundamental advances in the field. His leadership in both academic and applied research underscores his influence on the next generation of intelligent automation technologies. His innovative solutions make him highly deserving of this recognition.

🎓 Education

Prof. Jiantao Shi obtained his Bachelor’s degree in Electrical Engineering and Automation from Beijing Institute of Technology in 2011. He then pursued a Ph.D. in Control Science and Engineering at Tsinghua University, earning his doctorate in 2016. His academic journey at these top institutions equipped him with expertise in control systems, automation, and intelligent sensing technologies. His doctoral research focused on advanced fault diagnosis and cooperative control of multi-agent systems. This solid educational foundation has propelled him to the forefront of intelligent control and automation, enabling him to address complex challenges in distributed autonomous systems.

💼 Work Experience

Prof. Jiantao Shi has an extensive research career spanning academia and industry. From 2016 to 2018, he worked as an Associate Research Fellow at the Nanjing Research Institute of Electronic Technology, specializing in intelligent sensing. He was promoted to Research Fellow in 2019, leading projects in autonomous systems and fault-tolerant control. Since 2021, he has been a Professor at Nanjing Tech University, where he mentors students and advances research in AI-driven control methodologies. His experience in both applied research and academia allows him to bridge theoretical advancements with real-world applications in robotics, UAVs, and industrial automation.

🏅 Awards & Honors

Prof. Jiantao Shi has received several prestigious awards recognizing his contributions to control science and automation. His research has been featured in top-tier IEEE Transactions journals, demonstrating its high impact. He has been honored with multiple best paper awards at international conferences. Additionally, his work on UAV control and multi-robot systems has been acknowledged with research grants and government funding for innovation in automation. As a key contributor to cutting-edge intelligent control systems, he continues to earn accolades for his groundbreaking contributions, positioning himself as a leading researcher in distributed autonomous system control.

🔬 Research Focus

Prof. Jiantao Shi’s research centers on advanced control methodologies for intelligent automation. His key areas of expertise include cooperative control of multi-robot systems, fault diagnosis and fault-tolerant control of distributed systems, and learning-based control of UAVs. His work integrates AI and machine learning with traditional control science to enhance system resilience and autonomy. By developing robust, intelligent algorithms, he aims to improve automation reliability in real-world applications. His research has profound implications for robotics, autonomous vehicles, and industrial automation, paving the way for next-generation intelligent systems with enhanced adaptability, efficiency, and fault resilience.

📖 Publication Top Notes 

  1. A Parallel Weighted ADTC-Transformer Framework with FUnet Fusion and KAN for Improved Lithium-Ion Battery SOH Prediction
    • Publication Year: 2025
  2. Bipartite Fault-Tolerant Consensus Control for Multi-Agent Systems with a Leader of Unknown Input Under a Signed Digraph
    • Publication Year: 2025
  3. Iterative Learning-Based Fault Estimation for Stochastic Systems with Variable Pass Lengths and Data Dropouts
    • Publication Year: 2025
  1. A Two-Stage Fault Diagnosis Method with Rough and Fine Classifiers for Phased Array Radar Transceivers
    • Publication Year: 2024
  2. An Intuitively-Derived Decoupling and Calibration Model to the Multi-Axis Force Sensor Using Polynomials Basis
    • Publication Year: 2024
  3. Event-Based Adaptive Fault Tolerant Control and Collision Avoidance of Wheel Mobile Robots with Communication Limits
    • Publication Year: 2024

 

Dr. Chinenye Azuka | Technology | Best Researcher Award

Published on by Network Awards

Dr. Chinenye Azuka | Technology | Best Researcher Award

Dr. Chinenye Azuka, University of Nigeria Nsukka, Nigeria 

Dr. Chinenye Azuka is a dedicated researcher and academic specializing in food science and technology. She earned her Ph.D. from the University of Nigeria, focusing on functional food development from germinated brown rice and pigeon pea for diabetes management. Currently serving as Lecturer I at the University of Nigeria, Nsukka, she has extensive experience in teaching and mentoring students in food safety, food engineering, and cereal technology. Her research revolves around processing and product development of functional foods, with expertise in enzymatic activity, polyphenol extraction, and food processing techniques. Dr. Azuka is also skilled in hands-on instrumentation, experimental design, and academic writing. She has received several prestigious awards, including the Tertiary Education Trust Fund (TETFund) award for research excellence. With a strong passion for innovation in food science, she continues to make significant contributions to academia and the industry through her research, publications, and teaching excellence.

Professional Profile:

Orcid
Google Scholar

🏆 Suitability for Best Researcher Award 

Dr. Chinenye Azuka is an outstanding candidate for the Best Researcher Award due to her exceptional contributions to food science research, particularly in functional food development. Her Ph.D. research on germinated brown rice and pigeon pea extrudates for diabetes intervention demonstrates a strong commitment to addressing global health challenges through food technology. With extensive experience in designing and conducting experiments, enzyme activity evaluation, and food processing techniques, she has pioneered innovative methodologies in her field. Dr. Azuka’s expertise in UHPLC/HPLC instrumentation, response surface methodology, and solid-phase extraction further underscores her technical prowess. Additionally, her teaching and mentoring roles have shaped numerous students in the field of food science. Her research excellence has been recognized through prestigious awards like the TETFund Research Excellence Award. With her strong academic record, impactful research, and commitment to scientific advancement, Dr. Azuka is highly deserving of this award.

🎓 Education 

Dr. Chinenye Azuka holds a Ph.D. in Food Science and Technology from the University of Nigeria, where she conducted pioneering research on developing functional foods for diabetes management using germinated brown rice and pigeon pea. Her research focused on malting, formulation, polyphenol extraction, enzyme inhibition, and physicochemical analysis of extrudates. She was supervised by renowned scholars, including Prof. G. I. Okafor, Dr. Christine Bosch, and Dr. Lisa Marshall. Prior to her doctoral studies, she earned a Bachelor’s degree in Food Science, demonstrating excellence in food processing techniques and food safety. Her strong academic background has equipped her with expertise in food engineering, product development, and analytical techniques. Through her education, she has developed a profound understanding of food technology, functional food innovation, and dietary interventions for metabolic diseases, making her a significant contributor to the field of food science and technology.

📚 Experience

Dr. Chinenye Azuka is a seasoned academic and researcher with extensive experience in food science and technology. Currently, she serves as Lecturer I at the University of Nigeria, Nsukka, where she teaches undergraduate and postgraduate courses in food safety, cereal technology, food engineering, and processing techniques. She has also supervised numerous students in their research projects and dissertation presentations. Prior to her current role, she worked as Lecturer II, where she played a crucial role in curriculum development, student mentoring, and research supervision. Additionally, she has administrative experience as a Faculty ICT Representative and Treasurer for the Local Committee of the Nigerian Institute of Food Science and Technology. Her expertise in hands-on laboratory research, experimental design, and food processing techniques has made her an influential figure in academia. Dr. Azuka’s dedication to teaching, research, and administration highlights her excellence in both academic and scientific leadership.

🏅 Awards and Honors 

Dr. Chinenye Azuka’s remarkable research contributions have been recognized through multiple awards and honors. She received the prestigious Tertiary Education Trust Fund (TETFund) Nigeria Award in 2022 for research excellence and staff development, highlighting her outstanding work in food science. In 2008, she was honored with the Tantalizers Undergraduate Excellence Award, recognizing her academic brilliance and innovative research approach. Additionally, she has earned professional certifications, including Quality Management for Operational Excellence (2023) and UK Foundations in Teaching (2023), further demonstrating her commitment to academic and professional development. Her leadership roles, including serving as Treasurer of the Local Committee of the Nigerian Institute of Food Science and Technology (UNN Chapter), underscore her contributions to the academic community. These awards and recognitions affirm her dedication, expertise, and impactful research in food science, making her a leading figure in functional food technology and nutritional science.

🔬 Research Focus

Dr. Chinenye Azuka’s research primarily focuses on functional food development and processing for disease prevention and management. Her work explores nutritional interventions for metabolic diseases, particularly diabetes, through innovative food processing techniques. She specializes in extrusion technology, enzyme inhibition studies, polyphenol extraction, and food formulation using response surface methodology. Her research also involves physicochemical characterization of food products, ensuring optimal nutritional benefits. She has conducted extensive studies on germinated brown rice and pigeon pea-based extrudates, evaluating their alpha-glucosidase and amylase enzyme inhibition properties for diabetes management. Additionally, she applies advanced analytical techniques, including UHPLC/HPLC, scanning electron microscopy, and textural analysis, to assess food quality and functionality. Dr. Azuka’s groundbreaking work bridges the gap between food technology and healthcare, contributing to nutritional science, food safety, and functional food innovations. Her research continues to impact food industry advancements and global health initiatives.

Publication Top Notes:

  • Title: Micronutrients, antinutrients composition and sensory properties of extruded snacks made from sorghum and charamenya flour blends
    • Cited by: 14
    • Year: 2020
  • Title: Physical properties of parboiled milled local rice varieties marketed in South-East Nigeria
    • Cited by: 8
    • Year: 2021
  • Title: Cooking and functional properties of parboiled milled local rice marketed in the south-east zone of Nigeria
    • Cited by: 3
    • Year: 2020
  • Title: Evaluation of the chemical composition and sensory quality of parboiled local and imported milled rice varieties marketed in south-east zone of Nigeria
    • Cited by: 2
    • Year: 2019
  • Title: Evaluation of wheat-pigeon pea flour blends for noodle production in Nigeria
    • Cited by: 1
    • Year: 2022

 

Mr. Anthony Kyung Guzman Leguel | V2X Communication | Best Researcher Award

Published on by Network Awards

Mr. Anthony Kyung Guzman Leguel | V2X Communication | Best Researcher Award

Mr. Anthony Kyung Guzman Leguel, PNU, Mexico

Anthony Kyung Guzmán Leguel, originally from Busan, Korea, is a passionate electrical engineer dedicated to advancing technology for sustainable solutions. With a stellar academic background, he earned his Bachelor’s degree from ITESO (2014-2019) and is currently a GKS Scholar pursuing a Master’s in Electrical Engineering at PNU (2021-2024). Throughout his journey, Anthony has balanced academics with extracurricular activities, including teaching high school students about electrical systems and practicing Soo Bahk Do for 25 years. He has been recognized for his contributions to the field, showcasing an impressive blend of technical expertise and commitment to community engagement.

Professional Profile

Orcid

Recommendation for Anthony Kyung Guzmán Leguel for the Best Researcher Award

Anthony Kyung Guzmán Leguel is an exceptional candidate for the Best Researcher Award due to his extensive academic achievements, innovative research contributions, and significant industry experience in electrical engineering. His current pursuit of a Master’s degree at Pusan National University (PNU) as a GKS Scholar underscores his commitment to academic excellence, evidenced by a remarkable GPA of 9.6/10 during his Bachelor’s studies at ITESO.

🎓  Education 

Anthony began his educational journey at ITESO, where he earned a Bachelor’s degree in Electrical Engineering, graduating with a commendable GPA of 9.6/10 (2014-2019). He then became a GKS Scholar, pursuing a Master’s in Electrical Engineering at PNU from 2021 to 2024. During his Master’s program, he has engaged in cutting-edge research, particularly in areas related to reinforcement learning and V2X communications. This academic path reflects his commitment to both theoretical understanding and practical application, positioning him as a forward-thinking engineer poised to contribute to renewable energy integration. Anthony’s bilingual skills in Spanish and English, along with his intermediate proficiency in Korean and French, further enhance his capacity for collaboration in diverse environments, emphasizing the global nature of modern engineering challenges.

💼  Experience 

Anthony’s professional experience includes significant roles at PNU’s Vialab, where he has worked on developing a V2X beaconing scheme using reinforcement learning. His contributions led to a notable reduction in computation time for CenterPoint 3D Object Detection, showcasing his ability to enhance technological efficiency. Before this, he interned and later became an engineer at Intel, contributing to the development of algorithms for multi-agent autonomous systems, thus significantly impacting the creation of intellectual property. His early career included a role at ITESO, where he reviewed embedded systems master thesis projects and taught high school students about electrical engineering applications. This blend of internships, academic projects, and teaching experiences has equipped Anthony with a robust skill set, allowing him to effectively navigate the challenges of modern electrical engineering and technology development.

🏅Awards and Honors 

Anthony’s dedication and achievements have garnered numerous accolades throughout his academic and extracurricular pursuits. Notably, he was inducted into the Tae Kwon Do Hall of Fame in 2013, reflecting his excellence in martial arts. As a member of the Mexican Technical Advisory Committee for Soo Bahk Do Moo Duk Kwan, he has demonstrated leadership and commitment to martial arts. His participation as a captain of ITESO University’s Tae Kwon Do team from 2017-2019 further showcases his ability to inspire and lead others. Additionally, Anthony’s work in electrical engineering has led to patents that contribute to advancements in autonomous systems and V2X communications. These accomplishments, alongside his role as a GKS Scholar, position him as a prominent figure in both sports and engineering, embodying a well-rounded individual dedicated to excellence in multiple arenas.

🌍 Research Focus 

Anthony’s research focus lies at the intersection of electrical engineering and innovative technology, particularly in the realm of renewable energy integration and autonomous systems. His current work at PNU’s Vialab involves utilizing reinforcement learning to enhance V2X communications, aiming to improve efficiency and reliability in connected vehicle networks. This work not only addresses the growing need for intelligent transportation systems but also aligns with global sustainability goals. Additionally, his research extends to 3D object detection, where he explores methods to reduce computational demands while maintaining accuracy, crucial for autonomous driving applications. By investigating decentralized trajectory planning and human-robot collaboration, Anthony aims to contribute to the development of smarter, more efficient systems that facilitate renewable energy solutions. His interdisciplinary approach, combining advanced algorithms with practical applications, positions him as a forward-thinking researcher poised to make significant impacts in the field of electrical engineering.

📖 Publication Top Notes

Enhancing the Minimum Awareness Failure Distance in V2X Communications: A Deep Reinforcement Learning Approach

Dr. Brijesh Kumar Chaurasia | Smart Technology Awards | Best Researcher Award

Published on by Network Awards

Dr. Brijesh Kumar Chaurasia | Smart technology Awards | Best Researcher Award

Dr. Brijesh Kumar Chaurasia , Pranveer Singh Institute of Technology, Kanpur, India

Dr. Brijesh Kumar Chaurasia is a distinguished academic and researcher specializing in network security, with a primary focus on Vehicular Ad hoc Networks, Trust Management in VANETs, Blockchain, cloud authentication, and IoV/IoT. He earned his Ph.D. in Privacy Preservation in Vehicular Ad-hoc Networks from IIIT-Allahabad in 2013 and his M. Tech in Computer Science and Engineering from DAVV-Indore in 2006. With over 22 years of teaching experience and 4+ years in research and development, Dr. Chaurasia currently serves as a Professor and Dean of Research and Innovation at Pranveer Singh Institute of Technology, Kanpur. He has previously taught at ITM Group in Gwalior and IIIT Lucknow. He has been a principal investigator on several research grants, supervised numerous Ph.D. and postgraduate theses, and holds patents in IoT and smart systems. Dr. Chaurasia is actively involved in professional activities as a Senior Member of IEEE, Fellow of IETE, and member of IE and CSI. He has contributed to international journals and participated in various FDPs and workshops, showcasing his commitment to advancing knowledge and innovation in his field.

Professional Profile:

Google Scholar

🎓 Education:

Dr. Brijesh Kumar Chaurasia earned his Ph.D. in Computer Science and Engineering from IIIT-Allahabad, India, with his thesis focusing on Privacy Preservation in Vehicular Ad-hoc Networks. This prestigious degree was awarded on April 12, 2013, marking a significant milestone in his academic journey. Prior to his doctoral studies, Dr. Chaurasia completed his Master of Technology in Computer Science and Engineering from DAVV-Indore, India, in 2006. These educational accomplishments laid a strong foundation for his subsequent research and professional endeavors in the field of network security and technology.

💼 Employment and Experience:

Dr. Chaurasia has a combined experience of over 27 years in Research & Development, Teaching, and Industry. Currently, he serves as a Professor in Computer Science and Engineering & Dean Research and Innovation at Pranveer Singh Institute of Technology, Kanpur. Previously, he held teaching positions at ITM Group, Gwalior, MP, India, and Indian Institute of Information Technology, Lucknow.

🔍 Research Grants:

He has been involved in various research projects as Principal Investigator and Expert Member, securing grants for projects related to Hindi News portal development, IoT implementation and security, web redesigning, and Automatic Number Plate Recognition.

Publication Top Notes:

  1. Trust based location finding mechanism in VANET using DST
    • K Sharma, BK Chaurasia
    • 2015 Fifth International Conference on Communication Systems and Network, 2015
    • Cited by 66
  2. Message broadcast in VANETs using group signature
    • BK Chaurasia, S Verma, SM Bhasker
    • 2008 Fourth International Conference on Wireless Communication and Sensor Networks, 2008
    • Cited by 65
  3. Infrastructure based authentication in VANETs
    • BK Chaurasia, S Verma
    • International Journal of Multimedia and Ubiquitous Engineering, 2011
    • Cited by 54
  4. State of the art of data dissemination in VANETs
    • P Tomar, BK Chaurasia, GS Tomar
    • International Journal of Computer Theory and Engineering, 2010
    • Cited by 47
  5. Hiding sensitive association rules without altering the support of sensitive item(s)
    • D Jain, P Khatri, R Soni, BK Chaurasia
    • Advances in Computer Science and Information Technology. Networks and Communications, 2012
    • Cited by 43