Prof. Khaled Shaban | Data Science | Best Researcher Award

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Prof. Khaled Shaban | Data Science | Best Researcher Award

Prof. Khaled Shaban, Qatar University, Qatar

Prof. Khaled Shaban is a distinguished researcher and professor in Computer Science and Engineering at Qatar University. With expertise in Computational Intelligence, Machine Learning, and Data Science, he has significantly contributed to advancing pattern recognition, cloud computing, and cybersecurity. A senior member of IEEE and ACM, he has received multiple accolades for his groundbreaking research. He also holds an adjunct professorship at the University of Waterloo, reinforcing his global academic influence. His work focuses on AI-driven disease prediction, smart systems, and optimization techniques, making him a leader in intelligent computing innovations.

🌍 Professional Profile:

Google Scholar

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Scopus

🏆 Suitability for Best Researcher Award

Prof. Khaled Shaban’s research excellence, innovative contributions, and global recognition make him an ideal candidate for the Best Researcher Award. His pioneering work in Machine Learning, AI, and Computational Intelligence has led to influential publications and prestigious awards, such as the Best Paper Award at IRICT 2021. His ability to merge theory and application in AI, cloud computing, and cybersecurity has significantly impacted academia and industry. His leadership in top-tier conferences and IEEE/ACM communities underscores his commitment to advancing knowledge, making him a highly deserving candidate for this distinguished recognition.

🎓 Education

Prof. Khaled Shaban holds a Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada (2006), specializing in Pattern Recognition and Machine Intelligence. His academic journey began with an M.Sc. in Engineering Systems and Computing (2002) from the University of Guelph, Canada, where he developed a strong foundation in computational intelligence and optimization. His interdisciplinary education has enabled him to integrate machine learning, data science, and engineering systems into cutting-edge research. His expertise in algorithms and computing theory has positioned him as a global leader in AI and intelligent systems research.

💼 Experience

Prof. Khaled Shaban has an extensive academic career, currently serving as a Professor at Qatar University’s College of Engineering (since April 2021). He previously held roles as Associate Professor (2016-2021) and Assistant Professor (2008-2016). Additionally, he is an Adjunct Professor at the University of Waterloo (2021-2027), collaborating on AI-driven computing innovations. His professional affiliations with IEEE, ACM, and international research communities enhance his impact on global technological advancements. Over the years, he has mentored numerous students and led transformative research in Artificial Intelligence, Data Science, and Optimization.

🏅 Awards & Honors

  • 🏆 Best Paper Award – IRICT 2021 for “C-SAR: Class-Specific and Adaptive Recognition for Arabic Handwritten Cheques”
  • 🏅 Nomination for Best Paper Award – ICVS 2021 for “MARL: Multimodal Attentional Representation Learning for Disease Prediction”
  • 🎖 Promoted to Professor – Qatar University, 2021
  • 🔬 Senior Member, IEEE & ACM – Recognized for contributions to AI and Computational Intelligence
  • 🌍 International Collaborations – Adjunct Professor at the University of Waterloo, fostering global research partnerships

🔬 Research Focus

Prof. Khaled Shaban’s research lies at the intersection of Artificial Intelligence, Computational Intelligence, and Data Science. His work in Machine Learning-driven healthcare analytics, particularly in disease prediction and medical image analysis, is widely recognized. He has also made significant contributions to cybersecurity, cloud computing, and smart grid systems. His studies on optimization and knowledge discovery enhance IoT, AI-based automation, and intelligent computing solutions. Through numerous publications and projects, he has addressed real-world challenges in AI, energy-efficient computing, and adaptive learning systems, making his research impactful across academia and industry.

📖 Publication Top Notes

  • Urban Air Pollution Monitoring System with Forecasting Models

    • Year: 2016
    • Citations: 341

  • Fault Detection, Isolation, and Service Restoration in Distribution Systems: State-of-the-Art and Future Trends

    • Year: 2016
    • Citations: 321

  • Delay-Aware Scheduling and Resource Optimization with Network Function Virtualization

    • Year: 2016
    • Citations: 266

  • A Reliability-Aware Network Service Chain Provisioning with Delay Guarantees in NFV-Enabled Enterprise Datacenter Networks

    • Year: 2017
    • Citations: 224

  • Deep Learning Models for Sentiment Analysis in Arabic

    • Year: 2015
    • Citations: 150

 

 

Dr. Tanushree Bhattacharjee | Emerging Technologies | Best Researcher Award

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Dr. Tanushree Bhattacharjee | Emerging Technologies | Best Researcher Award

Dr. Tanushree Bhattacharjee, GRIDsentry Private Limited, India

Dr. Tanushree Bhattacharjee is a distinguished cybersecurity expert specializing in substation automation, OT security, and intrusion detection systems (IDS). With a Ph.D. in Electrical Engineering from Jamia Millia Islamia, she has over seven years of experience securing critical infrastructure. As Sr. R&D Manager at GRIDsentry Pvt. Ltd., Bengaluru, she leads cutting-edge research in forensic analysis, deep packet inspection, and AI-powered threat modeling. Dr. Bhattacharjee has played a vital role in national and international cybersecurity testbeds, contributing to the advancement of IEC 61850, power grid security, and microgrid protection. Her expertise in AI/ML-based anomaly detection ensures the resilience of modern power systems. 🔐⚡

🌍 Professional Profile:

Google Scholar

Orcid

Scopus

🏆 Suitability for the Best Researcher Award 

Dr. Tanushree Bhattacharjee is an outstanding candidate for the Best Researcher Award, given her pioneering work in substation automation security and digital transformation. She has made significant contributions to intrusion detection, vulnerability assessment, and OT security in power grids. Her leadership in developing IDS/IPS solutions, coupled with her expertise in AI-powered anomaly detection, positions her as a key innovator in cyber-physical security. With a strong background in threat modeling, forensic analysis, and protocol security, her research directly impacts critical infrastructure protection. Her proven ability to bridge AI with cybersecurity makes her a deserving nominee for this prestigious recognition. 🏆🔍

🎓 Education

Dr. Tanushree Bhattacharjee holds a Ph.D. in Electrical Engineering from Jamia Millia Islamia, New Delhi (2017-2022), where she focused on substation automation and microgrid protection. She completed her Master’s in Power Systems at the Indian Institute of Engineering Science & Technology, Shibpur (2012-2014). Her academic work involved IEC 61850 protocols, cybersecurity in digital substations, and AI-driven security frameworks. Through hands-on research in power system modeling, microgrid security, and forensic analysis, she has contributed to cybersecurity innovations in critical infrastructure. Her education has provided a robust foundation for her advancements in intrusion detection and digital protection strategies. 🎓⚡🔬

💼 Experience 

As Sr. R&D Manager at GRIDsentry Pvt. Ltd., Bengaluru, Dr. Bhattacharjee leads research on intrusion detection systems (IDS), AI-driven threat modeling, and forensic analysis. Previously, as a Product Manager, she specialized in deep packet inspection and anomaly detection. She also worked as a Power System Security Engineer, focusing on IPS/IDS development and OT cybersecurity. Her tenure at Jamia Millia Islamia involved substation automation, protocol security, and microgrid testing. With expertise in vulnerability assessments, access control, and live cybersecurity testing, she has significantly contributed to the security of modern power infrastructures. 🔒💡🚀

🏅 Awards & Honors 

Dr. Bhattacharjee has received multiple accolades for her contributions to power system cybersecurity. She has been recognized for her outstanding research in IDS and AI-driven security mechanisms. Her work on IEC 61850-based intrusion detection won Best Paper Awards at leading cybersecurity conferences. She has been acknowledged by cybersecurity organizations for her role in developing AI-based threat detection tools. Additionally, she has contributed to national security projects, earning commendation from government agencies and industry leaders. Her expertise in forensic analysis, digital substation security, and OT cybersecurity has positioned her as a trailblazer in the field. 🏆🔍⚡

🔬 Research Focus

Dr. Bhattacharjee’s research integrates emerging technologies with cybersecurity, focusing on power system protection, IEC 61850 protocols, and digital substation automation. Her expertise includes intrusion detection, AI-based anomaly detection, and forensic security analysis. She explores cyber-physical system security, ensuring resilience against DDoS, MITM, and replay attacks. Her work in deep learning for security event detection enhances smart grid protection. She also specializes in protocol security, AI-driven attack mitigation, and operational technology (OT) cybersecurity. Through machine learning, threat modeling, and real-time testing, her research aims to fortify modern power infrastructures against evolving cyber threats. 🛰️🔐⚙️

📖 Publication Top Notes

  1. Hardware Development and Interoperability Testing of a Multivendor-IEC-61850-Based Digital Substation
    • Citations: 11
    • Year: 2022
  2. Planning of Renewable DGs for Distribution Network Considering Load Model: A Multi-Objective Approach
    • Citations: 9
    • Year: 2014
  1. Designing a Controller Circuit for Three-Phase Inverter in PV Application
    • Citations: 6
    • Year: 2018
  2. Digital Substations with the IEC 61850 Standard
    • Citations: 3
    • Year: 2021
  3. Power Quality Improvement of Grid Integrated Distributed Energy Resource Inverter
    • Citations: 2
    • Year: 2021

 

Prof. Jiantao Shi | Information Technology | Best Researcher Award

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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

 

Prof Dr. Weixu liu | Big Data Award | Best Researcher Award

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Prof Dr. Weixu liu | Big Data Award | Best Researcher Award

Prof Dr. Weixu liu, Anhui Medical University, China

Associate Professor Weixu Liu of Anhui Medical University’s Department of Computer Science earned his Ph.D. from Zhejiang University in 2022. Specializing in big data analysis, machine learning, non-destructive evaluation, and structural health monitoring, Dr. Liu has published over 20 peer-reviewed articles and holds numerous patents and software copyrights. A senior member of the China Instrument and Control Society and the Chinese Society for Vibration Engineering, he has been recognized with multiple teaching awards, including a third-class prize in Anhui Province. His leadership in significant projects, such as the Anhui Provincial Outstanding Young Talent Project, and his involvement in national key R&D plans underscore his impactful contributions to the field of computer science and engineering.

Professional Profile:

Scopus

Suitability for the Research for Best Researcher Award

Assoc. Prof. Dr. Weixu Liu is a highly suitable candidate for the Research for Best Researcher Award due to his significant contributions to the fields of big data analysis, machine learning, non-destructive evaluation, and structural health monitoring. His academic achievements, extensive research activities, and innovative contributions highlight his excellence in research and development.

🎓 Academic Expertise

Associate Professor, Department of Computer Science, Anhui Medical University 🎓
Weixu Liu is an accomplished Associate Professor, Deputy Director, and Master Supervisor at Anhui Medical University’s Department of Computer Science. He earned his Ph.D. from Zhejiang University in 2022.

Research Interests and Contributions

Dr. Liu’s research focuses on big data analysis, machine learning, non-destructive evaluation, and structural health monitoring. He has published over 20 peer-reviewed journal articles and holds more than ten national invention patents, twenty utility model patents, and ten national computer software copyrights. His work has been supported by various government and corporate grants.

Professional Achievements

Dr. Liu is a senior member of the China Instrument and Control Society and a member of the Chinese Society for Vibration Engineering. He has received multiple awards for his teaching achievements, including a third-class prize in Anhui Province. He has led several significant projects, including Anhui Provincial Outstanding Young Talent Project and various municipal and national science and technology projects.

Innovations and Impact

Dr. Liu’s research has resulted in substantial scientific and technological advancements, including a conversion of achievements worth 500,000 RMB. His involvement in national key R&D plans and extensive project experience highlights his significant role in advancing the field of computer science and engineering.

Publication Top Notes:

  • Title: Multi-Feature Integration and Machine Learning for Guided Wave Structural Health Monitoring: Application to Switch Rail Foot
    • Citations: 20
    • Year: 2021
  • Title: Numerical Investigation of Locating and Identifying Pipeline Reflectors Based on Guided-Wave Circumferential Scanning and Phase Characteristics
    • Year: 2020
    • Open Access: Yes
  • Title: Sprouting Potato Recognition Based on Deep Neural Network GoogLeNet
    • Citations: 5
    • Year: 2018
  • Title: Phase Characteristic Analysis and Experimental Study on the Guided Wave Reflected from Expressway Guardrail Posts
    • Citations: 3
    • Year: 2017
  • Title: Numerical Simulation and Experimental Investigation on Ultrasonic Guided Waves in Multilayered Pipes Based on SAFE
    • Citations: 14
    • Year: 2014

 

 

Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

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Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

Prof. Jianfeng Guo, University of Chinese Academy of Sciences, China

Prof. Jianfeng Guo is a distinguished professor at the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has been a key figure since 2010 and has served as a professor since 2018. He earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in 2007 and completed postdoctoral research at Tsinghua University. Jianfeng’s research spans Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management. He has led over 60 significant projects, including collaborations with Baidu Big Data Lab and Ant Financial Services Group, and has published more than 90 papers and holds multiple patents and software copyrights. His international experience includes visits to top institutions and collaborations with global software companies.

🌍 Professional Profile

Scopus

🎓 Education

Jianfeng Guo earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in December 2007. He completed postdoctoral research at the CIMS Engineering Research Center of Tsinghua University from January 2008 to December 2009. He was a Senior Visiting Scholar at NEC China Research Institute from August 2009 to March 2010.

🔬 Research Interests

Jianfeng specializes in Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management.

🏢 Current Position

Since March 2010, Jianfeng has been with the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has served as a professor since 2018. He is also the Director of the Research Department for Think Tank Construction at the Institutes of Science and Development, CAS.

🌐 Notable Projects & Collaborations

Jianfeng has led over 60 projects, including NSFC projects, national programs, and enterprise-commissioned projects. He has collaborated with Baidu Big Data Lab and Ant Financial Services Group, contributing to advancements in big data and financial security.

📝 Publications & Patents

He has published more than 90 papers, including over 60 in international journals, and holds 4 invention patents and 15 computer software copyrights.

🌍 International Experience

Jianfeng has visited prestigious institutions such as the University of Oldenburg, Imperial College, and Cambridge University, and worked with international software companies like ASCORA and TIE.

Publication Top Notes:

  • Title: Graph-based algorithm for exploring collaboration mechanisms and hidden patterns among top scholars
    • Cited by: 1
    • Year: 2024
  • Title: A framework of cloud-edge collaborated digital twin for flexible job shop scheduling with conflict-free routing
    • Cited by: 3
    • Year: 2024
  • Title: Simulation research on the evolution pathway planning of energy supply and demand in China under the dual carbon targets
    • Cited by: 2
    • Year: 2023
  • Title: Electric vehicle adoption and local PM2.5 reduction: Evidence from China
    • Cited by: 7
    • Year: 2023
  • Title: Pathways for municipalities to achieve carbon emission peak and carbon neutrality: A study based on the LEAP model
    • Cited by: 53
    • Year: 2023

 

 

 

Prof. Mamede de Carvalho | Big Data Awards | Best Researcher Award

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Prof. Mamede de Carvalho | Big Data Awards | Best Researcher Award

Prof. Mamede de Carvalho, Faculdade de Medicina , Universidade de Lisboa, Portugal

Prof. Mamede de Carvalho is a distinguished medical professional renowned for his contributions to neurology and physiology. He obtained his MD from Nova Lisbon University in 1985, specializing in Neurology at the University Hospital in Lisbon in 1993. He earned his PhD in Neurology from the University of Lisbon in 2000, followed by a Habilitation in Neurosciences in 2007. Since 2010, he has served as a Full Professor of Physiology at the University of Lisbon, where he has made significant advancements in clinical neurology, particularly in ALS and neuromuscular disorders. Prof. de Carvalho’s leadership roles include Vice-Dean at the Faculty of Medicine and President of the Reynaldo dos Santos Technological Center in Lisbon. He also directed the Neuromuscular Unit at CHLN – Hospital de Santa Maria from 2009 to 2019, further cementing his impact on neurology research and practice.

🌐 Professional Profile:

Scopus

Orcid

Google Scholar

🎓 Education

Prof. Mamede de Carvalho is a distinguished medical professional with a robust academic background. He obtained his MD from Nova Lisbon University in Lisbon, Portugal, in 1985, followed by specialization in Neurology at the University Hospital in Lisbon in 1993. He earned his PhD in Neurology from the University of Lisbon in 2000 and completed his Habilitation in Neurosciences at the same institution in 2007. Since 2010, he has served as a Full Professor of Physiology at the University of Lisbon, contributing significantly to the fields of neurology and neuroscience through his research and academic leadership.

🌐 Professional Experience & Leadership

Prof. Mamede de Carvalho is a distinguished figure in neurology and physiology, having served as the President of the Reynaldo dos Santos Technological Center in Lisbon, Portugal, from 2017 to 2022. Prior to this, he held the position of Vice-Dean at the Faculty of Medicine – University of Lisbon from 2015 to 2022. With extensive expertise, he also served as the Director of the Neuromuscular Unit at CHLN – Hospital de Santa Maria in Lisbon from 2009 to 2019, contributing significantly to advancements in clinical neurology and neuromuscular disorders.

🔬 Clinical Research & Funding

Prof. Mamede de Carvalho is a pioneering figure in clinical neurology research, renowned for his contributions to advancements like Transcranial Magnetic Stimulation and the Threshold Technique for Axonal Excitability. His leadership has been instrumental in securing significant funding for projects focused on amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases, including grants from JPND and FCT.

Publication Top Notes:

 

 

 

 

Prof. Gui Gui | Big Data Analysis Awards | Best Scholar Award

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Prof. Gui Gui | Big Data Analysis Awards | Best Scholar Award

Prof. Gui Gui, Central South University, China

🎓 Prof. Gui Gui, a distinguished scholar 📚 hailing from Central South University 🇨🇳, boasts a stellar academic journey, culminating in a Ph.D. in Computer Science from the University of Essex 🎓. As a Full Professor at the School of Automation, her expertise in artificial intelligence and big data systems 🤖 propels groundbreaking research, enriching the global academic landscape 🔬. Beyond her role in academia, Gui Gui’s leadership 🌟 and commitment to knowledge dissemination 🌐 shape the future of computer science, inspiring generations of researchers and professionals.

🌐 Professional Profile:

Orcid

🎓 Education

Gui Gui holds a Bachelor of Engineering and a Master of Science in Computer Science from Central South University, Changsha, China. She furthered her education by obtaining a Ph.D. in Computer Science from the University of Essex, Colchester, UK, in 2007, showcasing her commitment to academic excellence and research.

🔬 Research Focus

As a distinguished Full Professor at the School of Automation, Central South University, China, Gui Gui’s research interests revolve around cutting-edge fields such as artificial intelligence, data modeling, and big data systems. Her work contributes significantly to advancing knowledge and innovation in these rapidly evolving domains.

💼 Professional Accomplishments

Gui Gui’s journey in academia has seen her rise to the esteemed position of Full Professor, reflecting her expertise, leadership, and dedication to the field of automation. Her leadership role underscores her influence in shaping the next generation of researchers and professionals in the realm of computer science.

🌐 Contributions & Impact

Gui Gui’s contributions extend beyond the classroom and laboratory, as she actively engages in scholarly activities, collaborations, and knowledge dissemination. Through her research, publications, and academic engagements, she continues to make a profound impact on the global academic community.

Publication Top Notes:

Object detection on low-resolution images with two-stage enhancement
  • Journal: Knowledge-Based Systems
  • Year: 2024-09

 

 

 

 

Dr. Luigi De Simio | Big Data Analysis | Excellence in Research

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Dr. Luigi De Simio | Big Data Analysis | Excellence in Research

Dr. Luigi De Simio, Consiglio Nazionale delle Ricerche, Italy

👨‍🔬 Dr. Luigi De Simio, born on 11/22/1978 in Benevento, Italy, is a distinguished researcher at the Institute of Sciences and Technologies for Sustainable Energy and Mobility (STEMS) of the National Research Council. He earned his Master’s and PhD degrees in Mechanical Engineering from the University of Naples Federico II. With expertise in alternative propulsion systems, he focuses on optimizing internal combustion engines with hydrogen-based fuels and hybrid solutions. Dr. De Simio has authored over 50 technical papers and holds a European patent for a thermal-electric hybrid propulsion system. He has contributed significantly to national projects like GREEN POWERTRAIN and TRIM, as well as international endeavors such as MhyBus and BEAUTY. His dedication to sustainable energy solutions has earned him recognition as a reviewer for top journals and an evaluator for projects funded by the Italian Ministry of Economic Development. 🌱🔧📚

🌐 Professional Profiles :

Scopus

Orcid

Google Scholar

🎓 Education:

Dr. Luigi De Simio is a distinguished scholar 🎓 whose academic journey has been marked by a relentless pursuit of excellence in mechanical engineering. Graduating with a Master’s degree from the prestigious University of Naples Federico II in 2006, he swiftly ascended to the realm of doctoral studies, obtaining his PhD in the same discipline in 2010. 🚀 With a foundation built upon rigorous scholarship and a passion for innovation, Dr. De Simio continues to illuminate the field with his expertise and dedication. 🌟

💼 Work:

Dr. Luigi De Simio embarked on an illustrious journey in the realm of research following his doctoral studies, undertaking impactful postdoctoral work at CNR from 2010 to 2012. 🌟 His dedication and expertise led him to transition into a full-time researcher role at CNR, where he continues to push the boundaries of knowledge in his field with unwavering determination and passion. 🔬 Dr. De Simio’s contributions stand as a testament to his commitment to advancing scientific understanding and driving innovation forward. 🚀

📝 Achievements:

Dr. Hamin Chong’s career is adorned with remarkable achievements, including the publication of over 50 technical papers, which stand as a testament to his scholarly prowess and contributions to the field of mechanical engineering 📄. Notably, his ingenuity has been recognized with the granting of a European patent in 2021 for a groundbreaking thermal-electric hybrid propulsion system, underscoring his innovative spirit and commitment to advancing sustainable technologies 🌱🚀. Dr. Chong’s achievements serve as inspiration for aspiring engineers and researchers worldwide, reflecting his unwavering dedication to driving impactful change through cutting-edge research and development.

🧠Research Interests :

Dr. Luigi De Simio’s remarkable career is adorned with numerous achievements that underscore his profound impact in the field of mechanical engineering. With a prolific output, he has authored over 50 technical papers, cementing his reputation as a leading scholar in his domain. 📄 Furthermore, his innovative spirit and groundbreaking research culminated in the granting of a European patent in 2021 for his pioneering work on a thermal-electric hybrid propulsion system, marking a significant milestone in sustainable transportation technology. 🌍⚡ Dr. De Simio’s contributions continue to shape the landscape of engineering and inspire future generations of innovators. 🌟

📚 Publication Impact and Citations :

Scopus Metrics:

  • 📝 Publications: 31 documents indexed in Scopus.
  • 📊 Citations: A total of 402 citations for his publications, reflecting the widespread impact and recognition of Dr. Luigi De Simio’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 578 📖
    • h-index: 10 📊
    • i10-index: 11 🔍
  • Since 2018:
    • Citations: 300 📖
    • h-index: 8 📊
    • i10-index: 7 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications Top Notes  :

1.  Combustion efficiency and engine out emissions of a SI engine fueled with alcohol/gasoline blends

Published  Year – 2013, Published in Applied Energy, cited by 206 articles.

2.  Numerical simulation and experimental test of dual fuel operated diesel engines

Published  Year – 2014, Published in Applied Thermal Engineering, cited by 93 articles.

3.  A numerical and experimental study of dual fuel diesel engine for different injection timings

Published  Year – 2016, Published in Applied Thermal Engineering, cited by 50 articles.

4.  Combined numerical-experimental study of dual fuel diesel engine

Published  Year – 2014, Published in Energy Procedia, cited by 43 articles.

5.  Possible transport energy sources for the future

Published  Year – 2013,  Published in Transport Policy, cited by 27 articles.

 

 

 

 

 

Mr. Hamin Chong | Big Data Analysis | Best Researcher Award

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Mr. Hamin Chong | Big Data Analysis | Best Researcher Award

Mr. Hamin Chong, Ls Mtron, South Korea

Mr. Hamin Chong is a skilled computer vision expert with a master’s degree in Industrial Data Engineering from Hanyang University. Currently serving as a Research Engineer at LS Mtron, a major player in agricultural machinery manufacturing, he specializes in AI-based technology research and system development. Hamin has excelled in developing anomaly detection and object detection models, contributing to quality improvement in manufacturing processes. His innovative work includes creating a real-time leakage inspection support system and a lightweight engine exterior inspection model, showcasing his ability to enhance model accuracy with limited data. With a background in mechanical engineering and experience at the Advanced Manufacturing Laboratory, Hamin is dedicated to smart manufacturing systems and has actively contributed to standardizing data in continuous process industries. His expertise extends to unsupervised and integrated ensemble learning algorithms for anomaly detection, as evidenced by publications and patents. Proficient in Python, SQL, and Tableau, Hamin is a dynamic professional who continually seeks to bridge the evolving boundaries between natural language processing and computer vision.

🌐 Professional Profiles :

Scopus

🛠️ Experience:

  1. LS Mtron (Research Engineer)
    • AI-based technology research and system development.
    • Real-time leakage inspection support system with a high accuracy model (f1 score: 0.92).
    • Development of lightweight engine exterior inspection model with a 90% size reduction.
  2. Advanced Manufacturing Laboratory
    • Smart manufacturing systems developer contributing to industry competitiveness.
    • Standardization of shared data in continuous process industries.
    • Development of unsupervised and integrated ensemble learning-based automatic labeling and anomaly detection algorithm.

📚 Education:

  • Master’s degree in Industrial Data Engineering, Hanyang University.
  • Bachelor’s degree in Mechanical Engineering, Sungkyunkwan University.

📝 Paper & Patent:

  • Method for detecting welding defects and learning method for detecting welding defects (2022).
  • Data-fused and concatenated-ensemble learning for in-situ anomaly detection in wire and arc-based direct energy deposition, Journal of Manufacturing Processes (2024).

🚀 Skills:

  • Language: Python, SQL.
  • Big Data Analyst, Data Analysis Associate, SQL Developer.
  • BI: Tableau (Training Completion: Oct-Nov 2023).

🧠Research Interests :

Hamin Chong is a visionary computer vision expert with a fervent interest in transforming data landscapes. 🌐 Armed with a master’s degree in Industrial Data Engineering, he excels in developing innovative solutions for anomaly detection and object recognition. As a Research Engineer at LS Mtron, he played a pivotal role in AI-based technology research, enhancing manufacturing processes through real-time leakage inspection support systems and lightweight engine exterior inspection models. Hamin’s journey extends to the Advanced Manufacturing Laboratory, where he contributed to standardizing shared data in continuous process industries and pioneered unsupervised ensemble learning for automatic labeling and anomaly detection. 🚀 With a robust skill set in Python, SQL, and Tableau, he embraces challenges in Big Data Analysis, embodying a commitment to shaping the future of smart factories. 📊✨

Publications Top Notes  :

Title: Data-fused and concatenated-ensemble learning for in-situ anomaly detection in wire and arc-based direct energy deposition

Authors: Kim, D.B., Chong, H., Mahdi, M.M., Shin, S.-J.

Published Year: 2024

Journal: Journal of Manufacturing Processes

 

 

 

 

Mr. Jiajun Pang | Big Data Analysis | Best Researcher Award

Published on by Network Awards

Mr. Jiajun Pang | Big Data Analysis | Best Researcher Award

Mr. Jiajun Pang, University at Buffalo, United States

🎓 Mr. Jiajun Pang is an avid academician currently pursuing his Ph.D. in Transportation Engineering at the University at Buffalo, SUNY, expected to complete in July 2025. Holding a Master’s degree in Transportation Engineering from Beijing University of Technology (June 2019) and a Bachelor’s degree from the same institution (June 2016), his educational journey showcases a profound commitment to advancing knowledge in the field. 🚗🚦 As a Research Assistant in the Transportation Research Lab since February 2020, Jiajun applies his expertise to delve into winter traffic safety intricacies, contributing to the analysis of the autonomous vehicles market and exploring the impacts of the Winter Intelligent Road Information System. His diverse research spans from game theory in global maritime transportation to driving simulation data for tourism sign effectiveness evaluation. 🚗📊 Jiajun’s dynamic role illuminates his dedication to unraveling transportation dynamics, and his research interests in Big Data Analysis and Traffic Safety promise innovative contributions to data-driven decision-making in the realm of transportation. 🧠🚗✨

🎓 Education : 

🎓 Mr. Jiajun Pang is on an academic journey, currently pursuing his Ph.D. in Transportation Engineering at the University at Buffalo, SUNY, with an expected completion date in July 2025. His passion for the field is evident in his previous academic achievements, holding a Master’s degree in Transportation Engineering from Beijing University of Technology (June 2019) and a Bachelor’s degree in the same discipline from the same institution (June 2016). Jiajun’s commitment to advancing his knowledge in transportation engineering showcases a trajectory of academic excellence and dedication to the field of study. 🚗🚦

🌐 Professional Profiles : 

ORCID

Scopus

🔍 Experience :

✨ Mr. Jiajun Pang brings valuable expertise as a Research Assistant in the Transportation Research Lab within the Civil, Structural, and Environmental Engineering domain since February 2020. His dynamic role involves delving into the intricacies of winter traffic safety through the application of the random parameter hazard duration model. Jiajun also contributes to the analysis of the autonomous vehicles market, employing the random parameter ordered probit model. His innovative contributions extend to designing and exploring the potential impacts of the Winter Intelligent Road Information System on winter travel. Using paired t-tests on data from self-designed stated preference surveys, he investigates travel behaviors in winter weather. Additionally, Jiajun applies game theory to model the competition in global maritime transportation and utilizes driving simulation data to evaluate the effectiveness of tourism signs. His diverse skill set and research pursuits illuminate his dedication to advancing the understanding of transportation dynamics. 🚗📊

🧠 Research Interests 🔬🌐 :

🔍 Mr. Jiajun Pang’s research interests form a compelling intersection of Big Data Analysis and Traffic Safety. His academic pursuits reflect a commitment to unraveling insights from vast datasets, contributing to the realm of data-driven decision-making. 📊 Passionate about enhancing transportation systems, Jiajun focuses on leveraging big data to analyze and improve traffic safety. His research endeavors promise to bring innovative solutions to the dynamic landscape of transportation, ensuring safer and more efficient journeys for all. 🚗✨

Citations : 

Scopus Metrics:

  • 📝 Publications: 3 documents indexed in Scopus.
  • 📊 Citations: A total of 26 citations for his publications, reflecting the widespread impact and recognition of Mr. Jiajun Pang’s research within the academic community.

Publications Top Notes  :

1.  A temporal instability analysis of environmental factors affecting accident occurrences during snow events: The random parameters hazard-based duration model with means and variances heterogeneity

Journal: Analytic Methods in Accident Research, 2022, 34, 100215

Cited by: 22

2.  Semi-buspool: Demand-driven Scheduling for Intercity Bus Based on Smart Card Data

Conference: 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, pp. 752–757, 2019

3.  Road Network Capacity Based on the Time-Space Consumption and the Traffic Operation Efficiency Theory 

Journal: Journal of Beijing University of Technology, 2019, 45(9), pp. 895–903

Cited by: 4