Boyu Wang | Cybersecurity | Best Researcher Award

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Dr. Boyu Wang | Cybersecurity | Best Researcher Award

Assistant professor at Beijing University of Civil Engineering and Architecture, China

Dr. Boyu Wang is a Principal Data Scientist at Tacoma Public Utilities in Washington, USA, where he leads energy and peak forecasting, financial modeling, and power operations. He holds a Ph.D. in Electrical Engineering from Louisiana State University, as well as Master’s degrees in Electrical Engineering and Computer Science. Dr. Wang has extensive experience in applying advanced data science techniques, including deep learning and blockchain, to optimize energy management systems. His research focuses on power flow prediction, decentralized micro-grids, and grid stability, and he has contributed to several publications and patents. He is committed to enhancing energy stability and resiliency through innovative data-driven solutions.

 

Profile

SCOPUS

GOOGLE SCHOLAR

Education

Dr. Boyu Wang holds a Ph.D. in Electrical Engineering from Louisiana State University, Baton Rouge, LA, USA, which he completed from August 2014 to August 2018. Prior to his doctoral studies, he earned a Master of Science in Electrical Engineering from the same institution, Louisiana State University, during the period from August 2012 to August 2014. In addition to his background in electrical engineering, Dr. Wang expanded his expertise by obtaining a Master of Science in Computer Science from the Georgia Institute of Technology, where he studied from January 2020 to May 2022. His multidisciplinary academic training provides a solid foundation for his research and contributions in energy systems, machine learning, and data science.

 Experience

Dr. Boyu Wang currently serves as a Principal Data Scientist at Tacoma Public Utilities in Washington, USA, where he leads the annual energy and peak forecasting for resource planning, financial modeling, and power operations. His responsibilities include supporting various teams with data collection, cleaning, and manipulation, as well as developing risk models and automation tools to improve reporting efficiency. Dr. Wang has played a key role in assisting with project management strategies and energy stability efforts. Prior to this, he worked as a Power Engineer Intern at Entergy, where he conducted analysis on renewable energy integration into distribution systems. Throughout his career, Dr. Wang has leveraged his expertise in deep learning, blockchain, and data science to contribute to various innovative research projects, particularly in energy management and grid stability.

Research Interests

Dr. Boyu Wang’s research interests lie at the intersection of energy systems, machine learning, and advanced technologies. His work primarily focuses on applying deep learning techniques, such as convolutional neural networks (CNN) and long short-term memory (LSTM) models, to predict power flow and optimize grid stability in real-time. Additionally, Dr. Wang has explored blockchain-based energy management for decentralized micro-grids, developing dynamic pricing strategies and decision-making algorithms to enhance energy distribution and trading. He is also passionate about developing novel methods for power grid stability, including multi-layer constrained spectral clustering for post-contingency problems and dynamic programming-based control systems for micro-grids. His research aims to advance the resilience and efficiency of energy systems through the integration of cutting-edge computational techniques.

Skills

Dr. Boyu Wang possesses a robust skill set in programming, data analysis, and energy systems optimization. He is proficient in Python, R, and SQL, which he utilizes for data manipulation, analysis, and model development. Dr. Wang is also experienced with platforms and software such as Tableau, DBeaver, Snowflake, and Databricks, enabling him to work efficiently with large datasets and develop impactful visualizations and analytics solutions. His technical expertise extends to deep learning, where he has applied convolutional neural networks (CNN) and long short-term memory (LSTM) models for power flow prediction, as well as blockchain technology for decentralized energy management in micro-grids. These skills, combined with his background in electrical and computer engineering, allow him to tackle complex challenges in energy systems and grid stability.

 

Publication

Cybersecurity Enhancement of Power Trading within the Networked Microgrids Based on Blockchain and Directed Acyclic Graph Approach

  • Authors: B. Wang, M. Dabbaghjamanesh, A. Kavousi-Fard, S. Mehraeen
  • Journal: IEEE Transactions on Industry Applications
  • Volume: 55, Issue 6, Pages 7300-7309
  • Publication Year: 2019
  • Cited by: 188

A Novel Two-Stage Multi-Layer Constrained Spectral Clustering Strategy for Intentional Islanding of Power Grids

  • Authors: M. Dabbaghjamanesh, B. Wang, A. Kavousi-Fard, S. Mehraeen, …
  • Journal: IEEE Transactions on Power Delivery
  • Volume: 35, Issue 2, Pages 560-570
  • Publication Year: 2019
  • Cited by: 70

Blockchain-Based Stochastic Energy Management of Interconnected Microgrids Considering Incentive Price

  • Authors: M. Dabbaghjamanesh, B. Wang, A. Kavousi-Fard, N.D. Hatziargyriou, …
  • Journal: IEEE Transactions on Control of Network Systems
  • Volume: 8, Issue 3, Pages 1201-1211
  • Publication Year: 2021
  • Cited by: 43

Networked Microgrid Security and Privacy Enhancement by the Blockchain-Enabled Internet of Things Approach

  • Authors: M. Dabbaghjamanesh, B. Wang, S. Mehraeen, J. Zhang, A. Kavousi-Fard
  • Conference: 2019 IEEE Green Technologies Conference (GreenTech)
  • Pages: 1-5
  • Publication Year: 2019
  • Cited by: 37

Superconducting Fault Current Limiter Allocation in Reconfigurable Smart Grids

  • Authors: A.S. Abdollah Kavousi-Fard, Boyu Wang, Omid Avatefipour, Morteza …
  • Conference: IEEE, Berkley University Conference on Smart City and Smart Grid
  • Publication Year: 2019
  • Cited by: 28

Stability Improvement of Microgrids Using a Novel Reduced UPFC Structure via Nonlinear Optimal Control

  • Authors: H. Saberi, S. Mehraeen, B. Wang
  • Conference: 2018 IEEE Applied Power Electronics Conference and Exposition (APEC)
  • Pages: 3294-3300
  • Publication Year: 2018
  • Cited by: 17

Conclusion

Dr. Boyu Wang’s extensive work in energy systems, innovative applications of deep learning and blockchain technologies, and his leadership in power grid optimization make him an excellent candidate for the Research for Best Researcher Award. His research not only advances theoretical knowledge but also provides practical solutions for improving energy efficiency, grid stability, and resilience, aligning with the award’s recognition of impactful, cutting-edge research.

FAN Bo | Data Security Management | Best Researcher Award

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Dr. FAN Bo | Data Security Management | Best Researcher Award

Senior Engineer at Southwest Jiaotong University, China

Dr. Fan Bo is a Senior Engineer and Chief Technical Specialist at the National Engineering Laboratory for Industrial Big Data Application Technology in China. With a Ph.D. and extensive experience in industrial innovation, he also serves as a project manager for the Ministry of Science and Technology’s Key Field Innovation Team and a technical expert for Chongqing Iron & Steel Electronic Co., Ltd. Dr. Fan has participated in over ten national R&D programs, published more than ten research papers, filed ten invention patents, and contributed to national and industrial standards. His groundbreaking work in data governance, business data modeling, and multi-value-chain distributed data spaces has benefited thousands of enterprises, earning him prestigious awards and international recognition.

 

Profile

ORCID

Education

Dr. Fan Bo has a strong academic foundation that underpins his expertise in industrial big data and digital transformation technologies. He earned his Ph.D. in a specialized field, equipping him with advanced knowledge and research skills crucial for tackling complex engineering and technological challenges. His academic journey reflects a commitment to excellence and a focus on integrating theoretical insights with practical applications, which has significantly contributed to his professional accomplishments in industrial innovation and data science.

 Experience

Dr. Fan Bo has a distinguished career marked by leadership and innovation in industrial big data and digital transformation. As Chief Technical Specialist at the National Engineering Laboratory for Industrial Big Data Application Technology, he oversees key technological advancements. He has participated in over ten national R&D programs, including leading a sub-project, and directed four key R&D initiatives in Sichuan Province. Additionally, Dr. Fan managed two horizontal digital transformation projects for China’s National Pipeline Group during the 13th and 14th Five-Year Plans. His concurrent roles as project manager for the Ministry of Science and Technology’s Key Field Innovation Team and technical expert for Chongqing Iron & Steel Electronic Co., Ltd. highlight his multifaceted expertise and ability to drive impactful projects in the field.

Research Interests

Dr. Fan Bo’s research interests focus on the application of industrial big data, data governance, and digital transformation technologies. He is particularly interested in the development and implementation of data governance platforms, business data models, and multi-value-chain distributed data spaces. His work aims to optimize industrial processes through innovative data solutions, particularly in the manufacturing and automotive sectors. Dr. Fan’s research also explores the integration of cloud service technologies and scenario-oriented business models to enhance efficiency and drive economic benefits for industrial enterprises. His contributions continue to shape the future of industrial data applications and digital innovation.

Skills

Dr. Fan Bo possesses a wide range of technical and leadership skills that have contributed to his success in industrial big data and digital transformation. He is highly skilled in data governance, designing and implementing complex data platforms, and developing business data models tailored to specific industrial scenarios. His expertise also extends to multi-value-chain distributed data spaces, enabling optimized data utilization across various industries, particularly in manufacturing and automotive sectors. Additionally, Dr. Fan has strong project management abilities, having led multiple high-impact initiatives under national R&D programs and major industrial projects. His proficiency in cloud service technologies, technical standard development, and innovation in digital transformation underscores his versatility and ability to drive technological advancements.

 

Publication

Title: Optimal Selection Technology of Business Data Resources for Multi-Value Chain Data Space—Optimizing Future Data Management Methods

  • Authors: Bo Fan, Linfu Sun, Dong Tan, Meng Pan
  • Journal: Electronics
  • Volume: 13
  • Issue: 23
  • Article Number: 4690
  • DOI: 10.3390/electronics13234690
  • Year: 2024

Conclusion

Dr. Fan Bo’s substantial research, innovation, and leadership in advancing industrial big data applications make him a deserving candidate for the Research for Best Researcher Award. His contributions not only address critical challenges in digital transformation but also generate tangible economic and industrial benefits, solidifying his position as a leading figure in his field.

Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

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Dr. Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

Senior researcher at Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias, Mexico

Dr. Liliana Aguilar-Marcelino is a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico. With a focus on microbial consortia, biocontrol, biotechnology, and natural product pharmacology, she investigates the bioactivity of fungi, bacteria, insects, mites, and nematodes. Her work includes exploring sustainable pest control strategies through biocontrol agents and metabolomic studies. Dr. Aguilar-Marcelino has contributed extensively to research on the insecticidal properties of metabolites from edible mushrooms and the development of nematocidal compounds. Her innovative research aims to advance agricultural sustainability and environmental health.

 

Profile

Scopus Profile

Google Scholar Profile

ORCID Profile

Education

Dr. Liliana Aguilar-Marcelino holds a distinguished academic background in the field of biological sciences. She completed her undergraduate studies in biology and later pursued advanced education, specializing in microbiology and biotechnology. Dr. Aguilar-Marcelino obtained her graduate degree (Master’s and/or Ph.D.) from a renowned institution, where she honed her expertise in microbial consortia, biocontrol, biotechnology, and the bioactivity of natural products. Her education has been instrumental in shaping her research focus, which spans a wide array of topics including natural product pharmacology, metabolomics, and the development of sustainable pest management solutions. With her strong academic foundation, Dr. Aguilar-Marcelino has become a leading researcher in her field, contributing significantly to the advancement of agricultural science and sustainable biocontrol technologies.

Experience

Dr. Liliana Aguilar-Marcelino has been a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico, since 2008. During her tenure, she has focused on pioneering research in microbial consortia, biocontrol, biotechnology, and metabolomics. She has led multiple studies exploring the bioactivity of fungi, bacteria, insects, mites, and nematodes, contributing to the development of sustainable solutions for pest control and agricultural health. Dr. Aguilar-Marcelino has published numerous research papers on topics such as the insecticidal effects of metabolites from edible mushrooms and the nematocidal properties of natural extracts, further establishing her expertise in the field of biocontrol and natural product pharmacology.

Research Interests

Dr. Liliana Aguilar-Marcelino’s research interests are centered on microbial consortia, biocontrol, and biotechnology, with a particular focus on the bioactivity of natural products. She specializes in metabolomics and the pharmacological potential of fungi, bacteria, insects, mites, and nematodes. Her work explores the development of natural pest control methods and sustainable agricultural practices through the study of bioactive compounds derived from edible mushrooms, fungi, and other microorganisms. Additionally, Dr. Aguilar-Marcelino investigates the potential of natural products for managing plant-parasitic nematodes and other agricultural pests, aiming to provide eco-friendly alternatives to traditional chemical controls.

 

Publication Top Noted

Title: New and future developments in microbial biotechnology and bioengineering: Trends of microbial biotechnology for sustainable agriculture and biomedicine systems: Diversity and applications

  • Authors: AA Rastegari, AN Yadav, N Yadav
  • Publisher: Elsevier
  • Cited by: 136
  • Year: 2020

Title: Micro (nano) plastics in wastewater: A critical review on toxicity risk assessment, behaviour, environmental impact, and challenges

  • Authors: S Singh, TSSK Naik, AG Anil, J Dhiman, V Kumar, DS Dhanjal, et al.
  • Journal: Chemosphere
  • Volume: 290
  • Article Number: 133169
  • Cited by: 71
  • Year: 2022

Title: Plasmodium berghei ookinetes induce nitric oxide production in Anopheles pseudopunctipennis midguts cultured in vitro

  • Authors: A Herrera-Ortíz, H Lanz-Mendoza, J Martínez-Barnetche, et al.
  • Journal: Insect Biochemistry and Molecular Biology
  • Volume: 34
  • Issue: 9
  • Pages: 893-901
  • Cited by: 65
  • Year: 2004

Title: The nematophagous fungus Duddingtonia flagrans reduces the gastrointestinal parasitic nematode larvae population in faeces of orally treated calves maintained under tropical conditions

  • Authors: P Mendoza-de-Gives, ME López-Arellano, L Aguilar-Marcelino, et al.
  • Journal: Veterinary Parasitology
  • Volume: 263
  • Pages: 66-72
  • Cited by: 52
  • Year: 2018

Title: Recent Trends in Mycological Research: Volume 1: Agricultural and Medical Perspective

  • Author: AN Yadav
  • Publisher: Springer International Publishing
  • Cited by: 49
  • Year: 2021

Title: Using molecular techniques applied to beneficial microorganisms as biotechnological tools for controlling agricultural plant pathogens and pests

  • Authors: L Aguilar-Marcelino, P Mendoza-de-Gives, LKT Al-Ani, et al.
  • Book: Molecular Aspects of Plant Beneficial Microbes in Agriculture
  • Pages: 333-349
  • Cited by: 47
  • Year: 2020

Title: Jesús Antonio Pineda-Alegría, José Ernesto Sánchez-Vázquez, Manases González-Cortazar, Alejandro Zamilpa, María Eugenia López-Arellano, Edgar Josué Cuevas-Padilla

  • Authors: P Mendoza-de-Gives, L Aguilar-Marcelino
  • Cited by: 69
  • Year: 2018

Conclusion

Dr. Liliana Aguilar-Marcelino’s innovative research in the areas of biocontrol, biotechnology, and natural product pharmacology has led to the development of several novel approaches for sustainable agricultural pest management. By focusing on natural alternatives to chemical pesticides, her work not only advances scientific understanding but also promotes environmentally friendly practices. Through her groundbreaking studies, Dr. Aguilar-Marcelino has significantly contributed to the field of sustainable agriculture, making her an outstanding candidate for the Research for Best Innovation Award.

Boquan Li | Cyber Threat | Best Researcher Award

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Dr. Boquan Li | Cyber Threat | Best Researcher Award

Assistant Professor at College of Computer Science and Technology, Harbin Engineering University, China

Dr. Boquan Li is a Tenure Track Associate Professor at the College of Computer Science and Technology, Harbin Engineering University, where he has served since January 2024. Prior to this, he was a Research Scientist at the School of Computing and Information Systems, Singapore Management University, from April 2022 to December 2023. Dr. Li holds a Ph.D. in Information Engineering from the University of Chinese Academy of Sciences and a Bachelor of Engineering from Harbin Engineering University. His research interests focus on artificial intelligence, cybersecurity, deepfake detection, and speaker recognition, with numerous publications in leading international conferences and journals. Dr. Li is also an active peer reviewer for prestigious journals like IEEE Transactions on Software Engineering.

Profile:

Education:

Dr. Boquan Li holds a Doctor of Philosophy (Ph.D.) from the University of Chinese Academy of Sciences, where he specialized in Information Engineering at the Institute of Information Engineering. He completed his Ph.D. in January 2022, building a strong foundation in artificial intelligence, cybersecurity, and data science. Prior to his doctoral studies, Dr. Li earned a Bachelor of Engineering degree from the School of Software at Harbin Engineering University in June 2016. His comprehensive academic background has equipped him with expertise in cutting-edge technologies, enabling him to contribute significantly to research in AI and cybersecurity.

Professional Experience:

Dr. Boquan Li has a diverse professional background in both academia and research. Since January 2024, he has been serving as a Tenure Track Associate Professor at the College of Computer Science and Technology, Harbin Engineering University, where he contributes to teaching and research in artificial intelligence and cybersecurity. Prior to this role, Dr. Li worked as a Research Scientist at the School of Computing and Information Systems, Singapore Management University, from April 2022 to December 2023. In this capacity, he was involved in cutting-edge research on deepfake detection, speaker recognition, and digital forensics. His professional experience highlights his expertise in developing innovative solutions to cybersecurity challenges and advancing research in AI-driven technologies.

Research Interests:

Dr. Boquan Li’s research interests focus on cutting-edge areas of artificial intelligence, cybersecurity, and multimedia forensics. He is particularly interested in deepfake detection, where he explores the vulnerabilities and robustness of detection systems across various domains. His work also covers speaker recognition, digital forensics, and adversarial attacks, aiming to develop defense mechanisms against cyber threats. Additionally, Dr. Li has a strong interest in cross-modal fusion techniques, particularly in audio-visual speech recognition, and domain adaptation methods for enhancing the accuracy of AI models across diverse datasets. His research contributes to advancing secure and reliable AI systems.

Skills:

Dr. Boquan Li possesses a diverse skill set that encompasses advanced computational techniques and a robust understanding of artificial intelligence and machine learning algorithms. He is proficient in developing and implementing deep learning models, particularly for applications in image and audio processing. His expertise extends to cybersecurity measures, with a focus on identifying vulnerabilities in AI systems and creating effective defense strategies against adversarial attacks. Additionally, Dr. Li is skilled in data analysis and statistical methods, enabling him to interpret complex datasets and derive meaningful insights. His strong programming skills in languages such as Python and proficiency with machine learning frameworks like TensorFlow and PyTorch further enhance his research capabilities in the field of computer science and technology.

Conclusion:

Dr. Boquan Li’s research addresses critical issues in AI security, deepfake detection, and adversarial defenses, areas of increasing importance in today’s technological landscape. His innovative work, combined with his academic and research experience, positions him as a strong candidate for the Best Researcher Award. His contributions have practical applications in cybersecurity and AI ethics, demonstrating both academic excellence and real-world impact.

Publication Top Noted:

  • How Generalizable are Deepfake Image Detectors? An Empirical Study
  • Two-stage Semi-supervised Speaker Recognition with Gated Label Learning
    • Authors: Xingmei Wang, Jiaxiang Meng, Kong Aik Lee, Boquan Li, Jinghan Liu
    • Year: 2024
    • Conference: International Joint Conference on Artificial Intelligence
    • Type: Conference paper
  • Assessing Backdoor Risk in Deepfake Detectors
    • Authors: Jiawen Wang, Boquan Li, Min Yu, Kam-Pui Chow, Jianguo Jiang, Fuqiang Du, Xiang Meng, Weiqing Huang
    • Year: 2024
    • Conference: IFIP WG 11.9 International Conference on Digital Forensics
    • Type: Conference paper
  • CATNet: Cross-Modal Fusion for Audio–Visual Speech Recognition
    • Authors: Xingmei Wang, Jiachen Mi, Boquan Li, Yixu Zhao, Jiaxiang Meng
    • Year: 2024
    • Journal: Pattern Recognition Letters
    • DOI: 10.1016/j.patrec.2024.01.002
  • A Residual Fingerprint-Based Defense Against Adversarial Deepfakes
  • FakeFilter: A Cross-Distribution Deepfake Detection System with Domain Adaptation
    • Authors: Jianguo Jiang, Boquan Li, Baole Wei, Gang Li, Chao Liu, Weiqing Huang, Meimei Li, Min Yu
    • Year: 2021
    • Journal: Journal of Computer Security
    • DOI: 10.3233/jcs-200124
  • Restoration as a Defense Against Adversarial Perturbations for Spam Image Detection
    • Authors: Jianguo Jiang, Boquan Li, Min Yu, Chao Liu, Weiqing Huang, Lejun Fan, Jianfeng Xia
    • Year: 2019
    • Conference: International Conference on Artificial Neural Networks
    • DOI: 10.1007/978-3-030-30508-6_56

Hafiz Jamil | Cyber Threat | Best Researcher Award

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Dr. Hafiz Jamil | Cyber Threat | Best Researcher Award

Data Scientist at Home, United States

Dr. Hafiz Jamil is a highly accomplished researcher and engineer specializing in Electronic Engineering with a focus on Data Science, AI-driven Intelligent Systems, IoT, and Renewable Energy Solutions. With over nine years of experience, he has led numerous national and international projects, successfully developing advanced energy management systems that incorporate blockchain and AI technologies. Dr. Jamil has a proven track record in optimizing real-time data analytics, enhancing operational efficiency, and driving sustainability in energy systems. He holds a Ph.D. in Electronic Engineering, along with a Master’s in Electrical Engineering and a Bachelor’s in Electronic Engineering. Additionally, he has received multiple awards for his research excellence and is a published author in prestigious scientific journals.

Profile:

Education:

Dr. Hafiz Jamil holds a Doctor of Philosophy (Ph.D.) in Electronic Engineering, specializing in advanced energy management solutions, IoT, and intelligent systems. He also earned a Master of Science (M.Sc.) in Electrical Engineering, where he focused on integrating AI and blockchain technologies into energy systems. His academic journey began with a Bachelor of Science (B.Sc.) in Electronic Engineering. In addition to his formal degrees, Dr. Jamil has pursued specialized certifications in fields such as Advanced Machine Learning, Blockchain for Energy, Python for Data Science, MATLAB for Engineers, and IoT System Architecture.

Professional Experience:

Dr. Hafiz Jamil possesses extensive professional experience in the fields of Electronic Engineering, Data Science, and Renewable Energy Solutions. Currently serving as a Research and Development Engineer at KETEP’s Big Data Research Center in South Korea, he has spearheaded the integration of big data analytics and IoT systems, significantly enhancing operational efficiency by reducing latency and downtime. His key accomplishments include developing advanced energy management solutions that incorporate blockchain and AI technologies, resulting in a 25% improvement in operational reliability. Previously, Dr. Jamil worked as a Consultant in Project Portfolio Management at CSU Science and Technology Park in China, where he optimized human activity recognition systems and enhanced energy efficiency in electric vehicles. Earlier in his career, he served as a Data Engineer in Power Systems in Pakistan, where he led automation projects and mentored teams to improve project success rates. His work is characterized by a strong commitment to innovation, collaboration with industry leaders, and a focus on sustainability in energy management.

Research Interests:

Dr. Hafiz Jamil’s research interests lie at the intersection of Electronic Engineering, Data Science, and Renewable Energy Solutions. He is particularly focused on developing AI-driven intelligent systems and Internet of Things (IoT) applications that enhance energy management and sustainability. His work encompasses advanced data analytics and machine learning, aiming to optimize real-time data processing and improve system performance in energy systems. Dr. Jamil has a keen interest in integrating blockchain technology for enhanced transparency and security in energy transactions. His research also includes the exploration of digital twin technology for optimizing renewable energy use and reducing peak loads in energy systems. Additionally, he is dedicated to advancing federated learning and smart grid technologies to promote energy efficiency and resource management in modern energy infrastructures.

Skills:

Dr. Hafiz Jamil possesses a diverse skill set that encompasses various domains within Electronic Engineering and Data Science. He is highly proficient in developing and implementing machine learning models, data analytics, and AI-driven intelligent systems, with expertise in programming languages such as Python, MATLAB, and C++. Dr. Jamil has a strong command of advanced technologies, including blockchain integration for energy systems and IoT development for smart grids. His technical capabilities extend to real-time monitoring and predictive optimization, allowing him to enhance operational efficiency in energy management solutions. Additionally, he excels in project management and cross-functional collaboration, demonstrating leadership in guiding teams through complex technological challenges. Dr. Jamil’s skills in automation, data governance, and scalable model deployment further contribute to his ability to drive innovation and improve system performance across various projects in the field.

Conclusion:

Given Dr. Hafiz Jamil’s impressive track record in research, innovation, and practical application in fields such as AI, IoT, and renewable energy systems, he is highly suitable for the Best Researcher Award. His research contributions, technical leadership, and groundbreaking work in enhancing energy efficiency make him an outstanding candidate for this recognition.

Publication Top Noted:

An Optimized Ensemble Prediction Model Using AutoML Based on Soft Voting Classifier for Network Intrusion Detection

  • Journal: Journal of Network and Computer Applications
  • Cited By: 58
  • Year: 2023
  • Contributors: M.A. Khan, N. Iqbal, H. Jamil, D.H. Kim

PetroBlock: A Blockchain-Based Payment Mechanism for Fueling Smart Vehicles

  • Journal: Applied Sciences
  • Cited By: 52
  • Year: 2021
  • Contributors: F. Jamil, O. Cheikhrouhou, H. Jamil, A. Koubaa, A. Derhab, M.A. Ferrag

An Efficient Dynamic-Decision Based Task Scheduler for Task Offloading Optimization and Energy Management in Mobile Cloud Computing

  • Journal: Sensors
  • Cited By: 48
  • Year: 2021
  • Contributors: A. Ali, M.M. Iqbal, H. Jamil, F. Qayyum, S. Jabbar, O. Cheikhrouhou, M. Baz, et al.

Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid

  • Journal: Sensors
  • Cited By: 45
  • Year: 2021
  • Contributors: T. Nasir, S. Raza, M. Abrar, H.A. Muqeet, H. Jamil, F. Qayyum, et al.

EEG-Based Neonatal Sleep Stage Classification Using Ensemble Learning

  • Journal: Computers, Materials & Continua
  • Cited By: 37
  • Year: 2022
  • Contributors: S.F. Abbasi, H. Jamil, W. Chen

Amani Benamor | Physical Layer Security | Best Researcher Award

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Dr. Amani Benamor | Physical Layer Security | Best Researcher Award

Post-doctoral research fellow at University of Limoges, France

Dr. Amani Benamor is a Postdoctoral Researcher at the University of Limoges, specializing in next-generation wireless networks. She earned her PhD in Computer Systems Engineering from the University of Limoges, in collaboration with the University of Sfax, where her research focused on Multi-user Wireless Access Techniques for Machine-Type Communications. Her expertise includes advanced technologies like Non-Orthogonal Multiple Access (NOMA), Internet of Things (IoT), 5G/6G, and massive Machine-Type Communications (mMTC). Dr. Benamor has also contributed to the field of physical layer security and has published extensively in leading IEEE conferences and journals. Fluent in Arabic, French, and English, she is passionate about technological innovation, research, and development.

Profile:

Education:

Dr. Amani Benamor pursued her PhD in Computer Systems Engineering from the University of Limoges (France) in collaboration with the University of Sfax (Tunisia) between 2019 and 2023. Her field of study was Information and Communication Science and Technology. Her thesis focused on Multi-user Wireless Access Techniques for Machine-Type Communications, exploring advanced technologies such as Non-Orthogonal Multiple Access (NOMA), Internet of Things (IoT), massive Machine-Type Communications (mMTC), and future 5G/6G networks. The research was conducted within the XLIM Laboratory in Limoges, France, and the Electronics and Information Technology Laboratory in Sfax, Tunisia. Dr. Benamor utilized a variety of technical tools including game theory, machine learning, and Matlab for her research.

Professional Experience:

Dr. Amani Benamor is currently a Postdoctoral Researcher at the University of Limoges, where she focuses on Physical Layer Security for Next-Generation Wireless Networks. Her research explores advanced technologies such as Non-Orthogonal Multiple Access (NOMA), 5G, Internet of Things (IoT), and massive MIMO, utilizing tools like Matlab, Python, and network coding. Prior to this, Dr. Benamor completed a research engineer internship at the Laboratory of Information Processing Systems Teams in Cergy, France, where she conducted performance studies on 1-bit Quantized Linear Precoder for Massive MIMO Systems. She also gained hands-on experience as a Web Developer Assistant at the Advanced Technology Center in Gabes, Tunisia, developing a web application for human resource management, and as a Network Engineer Assistant at Tunisia Telecom Operator, where she analyzed urban telephone network structures. Dr. Benamor’s professional background reflects her expertise in wireless communications, system security, and network engineering, combined with a solid foundation in software development and applied research.

Research Interests:

Dr. Amani Benamor’s research interests lie at the intersection of information and communication technology, with a particular focus on wireless communication systems. Her current work explores Physical Layer Security for next-generation wireless networks, emphasizing the integration of Non-Orthogonal Multiple Access (NOMA) in 5G and 6G environments. Dr. Benamor is particularly interested in the application of game theory and machine learning to enhance resource allocation and optimize performance in massive Machine-Type Communications (mMTC) and the Internet of Things (IoT). Her innovative approach includes leveraging advanced mathematical techniques and modeling tools to address challenges in security and efficiency within wireless networks. Additionally, she is keen on exploring emerging technologies and their implications for improving connectivity and data privacy in increasingly complex communication landscapes.

Skills:

Dr. Amani Benamor possesses a diverse skill set that encompasses various domains within computer science and engineering. Proficient in operating systems such as Windows, Linux, and Android Studio, she excels in project analysis and design methodologies, including UML and Merise. Her technical expertise extends to web technologies, where she is adept in HTML5, CSS3, XML, PHP, JavaScript, and JSP. Dr. Benamor is also skilled in several programming languages, including Java, JavaEE, Python, C, and Matlab, allowing her to effectively tackle a wide range of programming and development tasks. Furthermore, she is experienced in utilizing tools for mathematics, game theory, GNS3, GitHub, Jenkins, Docker, and machine learning, enhancing her ability to conduct complex research and implement innovative solutions in her field. Her strong foundation in these areas equips her to contribute significantly to advancements in wireless communication and network security.

Conclusion:

Dr. Amani Benamor’s exceptional research on multi-user wireless access techniques and her contributions to advanced communication technologies, alongside her impressive academic credentials and diverse technical skills, make her a strong candidate for the Best Researcher Award. Her groundbreaking work in NOMA, IoT, and security for next-generation wireless networks reflects her commitment to innovation and excellence in the field of Information and Communication Science and Technology.

Publication Top Noted:

Multi-Armed Bandit Approach for Mean Field Game-Based Resource Allocation in NOMA Networks

Mean Field Game-Theoretic Framework for Distributed Power Control in Hybrid NOMA

NURENI AZEEZ | Cybersecurity | Excellence in Research Award

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Assoc Prof Dr. NURENI AZEEZ | Cybersecurity | Excellence in Research Award

Associate Professor at University of Lagos, Nigeria

Summary:

Assoc. Prof. Dr. Nureni Azeez is an accomplished academic and researcher currently serving as an Associate Professor in the Department of Computer Sciences at the University of Lagos, Nigeria. He obtained his Ph.D. in Computer Science from the University of the Western Cape, South Africa, focusing on scalability and interoperability in grid-based environments. Dr. Azeez also holds an M.Sc. in Computer Science from the University of Ibadan and a B.Tech. in Computer Science from the Federal University of Technology, Akure. With a strong background in security and privacy, trust management, and web services security, he has made significant contributions through numerous published articles in reputable journals. Dr. Azeez has held various academic roles and leadership positions, emphasizing the integration of technology in development and security.

Profile:

Education:

Assoc. Prof. Dr. Nureni Azeez holds a Ph.D. in Computer Science from the University of the Western Cape, South Africa, completed between May 2010 and March 2013. Prior to this, he obtained a Master of Science (Honours) in Computer Science from the University of Ibadan, Nigeria, in 2008, where he graduated with a Ph.D. grade. He also earned a Bachelor of Technology (Honours) in Computer Science from the Federal University of Technology, Akure, Nigeria, in 2004, achieving Second Class Honours, Upper Division. Dr. Azeez’s educational journey began with an Ordinary National Diploma in Computer Science in 1998 and a Senior Secondary Certificate Examination in 1996, where he achieved distinctions. His foundational education was completed at Ede Muslim Grammar School and Y.T.D School ‘B’ Ojoro, both in Osun State, Nigeria, where he attended from 1983 to 1996.

Professional Experience:

Assoc. Prof. Dr. Nureni Azeez has extensive professional experience in academia and research. He is currently an Associate Professor in the Department of Computer Sciences at the University of Lagos, Nigeria, a position he has held since October 2022. Prior to this, he served as a Senior Lecturer in the same department from October 2019 to October 2022. Dr. Azeez began his academic career as a Lecturer Grade II at the University of Lagos and subsequently progressed to Lecturer Grade I. He also gained valuable experience as a Postdoctoral Fellow at North-West University, South Africa, where he worked in the School of Information Technology. His earlier roles include research and teaching assistantships at the University of the Western Cape, as well as lecturer positions at various institutions in Nigeria. With a focus on computer science education and research, Dr. Azeez has played a significant role in shaping academic programs and mentoring students throughout his career.

Research Interests:

Assoc. Prof. Dr. Nureni Azeez has a diverse range of research interests primarily focused on the intersections of technology and security. His expertise encompasses Security and Privacy, particularly in the context of digital systems and data protection. He is also deeply involved in Trust Management, exploring how to establish and maintain trust in digital interactions. Additionally, Dr. Azeez is interested in Web Services Security, aiming to enhance the safety and reliability of online services. His research extends to ICT4D (Information and Communication Technology for Development), where he examines how technology can facilitate socio-economic growth. Furthermore, he is passionate about E-Health, investigating the role of information technology in improving health services and outcomes. Through his research, Dr. Azeez aims to contribute to the development of secure, efficient, and impactful technological solutions.

Skills:

Assoc. Prof. Dr. Nureni Azeez possesses a robust skill set that encompasses various areas of computer science and technology. His programming expertise includes proficiency in web development using PHP, HTML, XHTML, and MySQL, as well as coding in Assembly Language, Python, JAVA, FORTRAN, and BASIC across both Linux and Windows environments. He has demonstrated his capabilities in cybersecurity, particularly in web services security and machine learning applications in cyber defense. Dr. Azeez is skilled in systems analysis and design, having taught and implemented principles in academic settings. His experience also extends to database management, compiler construction, and the application of algorithms. Additionally, he has strong leadership and organizational skills, having held various academic and administrative roles within the university. His commitment to ongoing learning is evidenced by his participation in numerous training programs and workshops, further enhancing his expertise in emerging technologies and methodologies.

Concution:

In conclusion, Assoc. Prof. Dr. NURENI AZEEZ exemplifies the qualities associated with the Excellence in Research Award. His strong academic background, extensive work experience, active research contributions, leadership roles, and professional engagement collectively highlight his impact in the field of computer science. His commitment to research excellence, innovation, and education positions him as a deserving candidate for this prestigious recognition.

Publication Top Noted:

  • Security and Privacy Issues in E-Health Cloud-Based System: A Comprehensive Content Analysis
    • Authors: NA Azeez, C Van der Vyver
    • Year: 2019
    • Journal: Egyptian Informatics Journal 20 (2), 97-108
    • Citations: 163
  • Windows PE Malware Detection Using Ensemble Learning
    • Authors: NA Azeez, OE Odufuwa, S Misra, J Oluranti, R Damaševičius
    • Year: 2021
    • Journal: Informatics 8 (1), 10
    • Citations: 94
  • Using Wearable Sensors for Remote Healthcare Monitoring System
    • Authors: AP Abidoye, NA Azeez, AO Adesina, KK Agbele, HO Nyongesa
    • Year: 2011
    • Journal: Journal of Sensor Technology 2011
    • Citations: 86
  • Intrusion Detection and Prevention Systems: An Updated Review
    • Authors: NA Azeez, TM Bada, S Misra, A Adewumi, C Van der Vyver, R Ahuja
    • Year: 2020
    • Journal: Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019
    • Citations: 72
  • Cyber Security: Challenges and the Way Forward
    • Authors: NA Ayofe, B Irwin
    • Year: 2010
    • Journal: Comput. Sci. Telecommun. 29, 56-69
    • Citations: 62
  • Identifying Phishing Attacks in Communication Networks Using URL Consistency Features
    • Authors: NA Azeez, BB Salaudeen, S Misra, R Damaševičius, R Maskeliūnas
    • Year: 2020
    • Journal: International Journal of Electronic Security and Digital Forensics 12 (2)
    • Citations: 60
  • Adopting Automated Whitelist Approach for Detecting Phishing Attacks
    • Authors: NA Azeez, S Misra, IA Margaret, L Fernandez-Sanz
    • Year: 2021
    • Journal: Computers & Security 108, 102328
    • Citations: 54
  • Network Intrusion Detection with a Hashing Based Apriori Algorithm Using Hadoop MapReduce
    • Authors: NA Azeez, TJ Ayemobola, S Misra, R Maskeliūnas, R Damaševičius
    • Year: 2019
    • Journal: Computers 8 (4), 86
    • Citations: 49
  • Ancaee: A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks
    • Authors: AP Abidoye, NA Azeez, AO Adesina
    • Year: 2011
    • Journal: Scientific Research
    • Citations: 40

Ousmane Thiare | Cybersecurity | Best Researcher Award

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Prof Dr. Ousmane Thiare | Cybersecurity | Best Researcher Award

Full Professor at Université Gaston Berger, Senegal

Summary:

Prof. Dr. Ousmane Thiare is a prominent scholar in Computer Science, currently serving as a Full Professor at Gaston Berger University in Saint-Louis, Senegal. He holds a Ph.D. in Computer Science from CY Cergy Paris University, along with multiple degrees in Applied Mathematics from Gaston Berger University. His extensive experience includes leadership roles in various European research initiatives aimed at enhancing agricultural studies and advancing cybersecurity in Senegal, such as his positions on the boards of the Senegal Internet Exchange Point and the National Cybersecurity School. Prof. Thiare’s research interests encompass a wide range of areas, including the Internet of Things (IoT), artificial intelligence, and circular economy. Notably, he has led significant projects, including the development of a national digital livestock tracking system in Mali and Senegal, contributing to sustainable development and innovation in the region. His dedication to education and research continues to empower future generations of scholars in Africa.

Profile:

Education:

Prof. Dr. Ousmane Thiare holds an impressive academic background, with a Ph.D. in Computer Science from CY Cergy Paris University in France, alongside multiple post-graduate and graduate degrees in Applied Mathematics from Gaston Berger University in Senegal. This extensive educational foundation has equipped him with strong analytical and technical skills, essential for advancing research in his field.

Professional Experience:

Prof. Dr. Ousmane Thiare boasts an impressive professional experience in academia and research. He currently serves as a Full Professor of Computer Science at Gaston Berger University in Saint-Louis, Senegal, where he has been instrumental in implementing research projects, supervising PhD theses, and teaching various modules. He has held several leadership roles, including the Scientific and Technical Director of major European research projects, such as the “URBANE” project focused on agroecological transformation and the Erasmus-funded initiative aimed at boosting agricultural studies in Sub-Saharan Africa. Additionally, he coordinates activities related to cybersecurity through the Cyberattack Detection, Warning, and Response Activities program. His involvement extends to the boards of several organizations, including the Senegal Internet Exchange Point and the National Cybersecurity School, where he contributes to the development of regional cybersecurity strategies. Through his leadership of the Mastercard Foundation Scholar Program, he has facilitated training for fellows in digital technologies, agriculture, health, and engineering, furthering the academic and professional landscape in Senegal and beyond.

Research Interests:

Prof. Dr. Ousmane Thiare’s research interests encompass a broad spectrum of cutting-edge topics in computer science and applied mathematics. He is particularly focused on the Internet of Things (IoT), where he explores innovative applications and technologies that enhance connectivity and data exchange. His expertise also extends to artificial intelligence, where he investigates algorithms and systems that can improve decision-making processes. Prof. Thiare is actively engaged in research on Wireless Sensor Networks (WSN) and Mobile Ad Hoc Networks (MANET), aiming to optimize communication and data management in dynamic environments. Additionally, his work in parallel and distributed systems addresses challenges related to efficiency and resource allocation. He has a keen interest in Peer-to-Peer (P2P) systems and routing and data replication techniques, which are critical for ensuring reliable data transfer. Furthermore, Prof. Thiare is involved in Grid and Cloud computing research, as well as the principles of the circular economy, reflecting his commitment to sustainable and impactful technological solutions.

Skills:

Prof. Dr. Ousmane Thiare possesses a diverse array of skills that underpin his expertise in computer science and applied mathematics. He is highly proficient in advanced computational techniques, with a strong command of programming languages and frameworks essential for developing and implementing innovative solutions in his research areas. His analytical skills enable him to approach complex problems methodically, utilizing data-driven insights to inform his work. Prof. Thiare is adept at project management, having successfully coordinated multiple research initiatives and collaborations, which highlights his ability to lead interdisciplinary teams. His experience in training and mentoring students and professionals demonstrates his commitment to knowledge transfer and capacity building in the academic community. Furthermore, his understanding of current trends in digital technology, cybersecurity, and sustainable practices equips him to contribute meaningfully to both local and global discussions on the future of technology and its societal implications.

Concution:

Prof. Dr. Ousmane Thiare’s extensive education, leadership roles, and active engagement in innovative research initiatives make him a highly suitable candidate for the Research for Best Researcher Award. His contributions not only advance academic knowledge but also foster significant social and technological advancements in Senegal and beyond, aligning perfectly with the award’s objectives.

Publication Top Noted:

  • Title: Enabling privacy and security in Cloud of Things: Architecture, applications, security & privacy challenges
    Authors: AA Abba Ari, OK Ngangmo, C Titouna, O Thiare, A Mohamadou, …
    Journal: Applied Computing and Informatics
    Volume: 20
    Issue: 1/2
    Pages: 119-141
    Cited By: 100
    Year: 2024
  • Title: Flood forecasting based on an artificial neural network scheme
    Authors: FY Dtissibe, AAA Ari, C Titouna, O Thiare, AM Gueroui
    Journal: Natural Hazards
    Volume: 104
    Pages: 1211-1237
    Cited By: 71
    Year: 2020
  • Title: Resource allocation scheme for 5G C-RAN: a Swarm Intelligence based approach
    Authors: AAA Ari, A Gueroui, C Titouna, O Thiare, Z Aliouat
    Journal: Computer Networks
    Volume: 165
    Article ID: 106957
    Cited By: 71
    Year: 2019
  • Title: HGC: HyperGraph based Clustering scheme for power aware wireless sensor networks
    Authors: JEZ Gbadouissa, AAA Ari, C Titouna, AM Gueroui, O Thiare
    Journal: Future Generation Computer Systems
    Volume: 105
    Pages: 175-183
    Cited By: 47
    Year: 2020
  • Title: Low-cost antenna technology for LPWAN IoT in rural applications
    Authors: C Pham, F Ferrero, M Diop, L Lizzi, O Dieng, O Thiaré
    Conference: 2017 7th IEEE International Workshop on Advances in Sensors and Interfaces
    Cited By: 35
    Year: 2017
  • Title: A study on IoT solutions for preventing cattle rustling in African context
    Authors: O Dieng, B Diop, O Thiare, C Pham
    Conference: ICC
    Volume: 17
    Pages: 1-13
    Cited By: 34
    Year: 2017
  • Title: Nature-based one health approaches to urban agriculture can deliver food and nutrition security
    Authors: B Ebenso, A Otu, A Giusti, P Cousin, V Adetimirin, H Razafindralambo, …
    Journal: Frontiers in Nutrition
    Volume: 9
    Article ID: 773746
    Cited By: 23
    Year: 2022
  • Title: Outdoor localization and distance estimation based on dynamic RSSI measurements in LoRa networks: Application to cattle rustling prevention
    Authors: O Dieng, P Congduc, O Thiare
    Conference: 2019 International Conference on Wireless and Mobile Computing, Networking
    Cited By: 21
    Year: 2019

Jian Li Hao | Cybersecurity | Women Researcher Award

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Dr. Jian Li Hao | Cybersecurity | Women Researcher Award

Senior Associate Professor at Xi’an Jiaotong-Liverpool University, China

Summary:

Dr. Jian Li Hao is a Senior Associate Professor in the Department of Civil Engineering at Xi’an Jiaotong-Liverpool University in Suzhou, China. He holds a Ph.D. in Civil Engineering from Concordia University, Canada, and has over a decade of academic and research experience. Dr. Hao specializes in sustainable construction, waste management, and environmental impact assessment. He has published over 50 journal papers and supervised multiple Ph.D. and master’s students. With research grants exceeding 4.5 million RMB and several prestigious awards, including the Suzhou Nature Science Excellent Paper Award, Dr. Hao is recognized for his contributions to advancing sustainability in the construction industry.

Profile:

Education:

Dr. Jian Li Hao holds a robust academic foundation in civil engineering and construction management. He earned his Ph.D. in Civil Engineering from Concordia University, Montreal, Canada, where his research focused on sustainable building practices and environmental impact assessments. Prior to his doctoral studies, Dr. Hao completed his Master’s degree in Construction Management at Southeast University, China, which laid the groundwork for his expertise in construction methodologies and project management. His academic journey began with a Bachelor’s degree in Civil Engineering, also from Southeast University, where he developed a solid technical foundation in engineering principles. Dr. Hao’s diverse educational background has significantly contributed to his research in sustainable construction and waste management, positioning him as a leading scholar in the field.

Professional Experience:

Dr. Jian Li Hao has extensive professional experience in civil engineering and academia. Since July 2020, he has served as a Senior Associate Professor in the Department of Civil Engineering at Xi’an Jiaotong-Liverpool University in Suzhou, China. Prior to this role, he was an Associate Professor at the same university from September 2016 to July 2020. Before moving to China, Dr. Hao worked as an Assistant Professor in the Department of Building, Civil and Environmental Engineering at Concordia University in Montreal, Canada, from June 2014 to June 2016. In addition to his teaching and research duties, Dr. Hao has been actively involved in the development and management of the MSc Construction Management program since 2020. He has also contributed significantly to various international conference scientific committees, including the International Conference on Sustainable Solid Waste Management and the International Symposium on Solid Waste Technology and Management. His expertise extends to the supervision of graduate students, with a total of 13 Ph.D. students currently under his supervision.

Research Interests:

Dr. Jian Li Hao’s research interests lie at the intersection of civil engineering, environmental sustainability, and construction management. He focuses on sustainable waste management, with particular emphasis on minimizing construction and demolition waste. His work explores innovative solutions for decarbonizing the construction industry, with special attention to life cycle assessment of sustainable materials, including recycled aggregate and supplementary cementitious materials. Dr. Hao also investigates the environmental impact of urbanization and energy consumption, utilizing advanced modeling techniques like the STIRPAT model to assess household carbon dioxide emissions. His research further extends to policy development for sustainable construction practices, scenario simulations for waste management, and the integration of environmental sustainability into construction projects.

Skills:

Dr. Jian Li Hao possesses a diverse set of skills that span across civil engineering, environmental sustainability, and academic leadership. His expertise includes advanced modeling techniques for environmental impact assessment, with a strong focus on life cycle assessment (LCA) and the STIRPAT model for analyzing carbon emissions and energy consumption. He has extensive experience in sustainable waste management, particularly in the minimization of construction and demolition waste, and is adept at decarbonizing building processes through innovative material use. In addition to his technical skills, Dr. Hao is proficient in program development and management, having successfully led the MSc Construction Management program. His academic leadership includes PhD supervision, research grant acquisition, and module development and delivery. He also demonstrates strong capabilities in international collaboration, serving as an external examiner and contributing to scientific committees for conferences in his field. Dr. Hao’s skills are further complemented by his role as a keynote speaker and session chair at international forums on sustainability and waste management.

Publication Top Noted:

  • Title: A checklist for assessing sustainability performance of construction projects
    Authors: LY Shen, JL Hao, VWY Tam, H Yao
    Journal: Journal of Civil Engineering and Management
    Year: 2007
    Volume: 13(4), pp. 273-281
    Citations: 386
  • Title: An empirical investigation of construction and demolition waste generation rates in Shenzhen city, South China
    Authors: W Lu, H Yuan, J Li, JL Hao, X Mi, Z Ding
    Journal: Waste Management
    Year: 2011
    Volume: 31(4), pp. 680-687
    Citations: 337
  • Title: A model for cost–benefit analysis of construction and demolition waste management throughout the waste chain
    Authors: HP Yuan, LY Shen, JL Hao, WS Lu
    Journal: Resources, Conservation and Recycling
    Year: 2011
    Volume: 55(6), pp. 604-612
    Citations: 273
  • Title: Procurement innovation for a circular economy of construction and demolition waste: lessons learnt from Suzhou, China
    Authors: Z Bao, W Lu, B Chi, H Yuan, JL Hao
    Journal: Waste Management
    Year: 2019
    Volume: 99, pp. 12-21
    Citations: 223
  • Title: Carbon emission reduction in prefabrication construction during materialization stage: A BIM-based life-cycle assessment approach
    Authors: JL Hao, B Cheng, W Lu, J Xu, J Wang, W Bu, Z Guo
    Journal: Science of the Total Environment
    Year: 2020
    Citations: 219
  • Title: A simulation model using system dynamic method for construction and demolition waste management in Hong Kong
    Authors: JL Hao, MJ Hills, T Huang
    Journal: Construction Innovation
    Year: 2007
    Citations: 167
  • Title: The evolution of construction waste sorting on-site
    Authors: H Yuan, W Lu, JL Hao
    Journal: Renewable and Sustainable Energy Reviews
    Year: 2013
    Volume: 20, pp. 483-490
    Citations: 162

Kyoung Jae Lim | Cybersecurity | Best Researcher Award

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Prof. Kyoung Jae Lim | Cybersecurity | Best Researcher Award

Professor at Kangwon National University, South Korea

Summary:

Prof. Kyoung Jae Lim is a prominent figure in the field of Agricultural and Biological Engineering, currently serving as a Professor in the Department of Regional Infrastructure Engineering at Kangwon National University in the Republic of Korea. With a Bachelor of Science degree in Agricultural Engineering from Kangwon National University and both a Master of Science and a Ph.D. from Purdue University, he has established a solid academic foundation. Prof. Lim’s research focuses on watershed management, land use change, and environmental impact assessment, and he has published extensively in respected journals. His work emphasizes innovative solutions to environmental challenges, making him a respected academic leader and contributor to sustainable engineering practices.

Profile:

Education:

Prof. Kyoung Jae Lim has an impressive educational background that forms the foundation of his expertise in Agricultural and Biological Engineering. He earned his Bachelor of Science degree in Agricultural Engineering from Kangwon National University in Chuncheon, Republic of Korea, from 1991 to 1994. He then pursued his graduate studies at Purdue University in West Lafayette, Indiana, USA, where he obtained a Master of Science degree in Agricultural and Biological Engineering in 1998, followed by a Ph.D. in the same field in 2001. This strong academic background has equipped Prof. Lim with the knowledge and skills necessary to excel in research and teaching within his area of specialization.

Professional Experience:

Prof. Kyoung Jae Lim has an extensive professional background in academia, spanning over two decades at Kangwon National University in the Republic of Korea. He began his career as a Part-Time Lecturer in Agricultural Engineering in 2004, quickly advancing to the role of Assistant Professor in 2006. By 2009, he was appointed Associate Professor, and in 2015, he achieved the position of Professor in the Department of Regional Infrastructure Engineering. Prior to his tenure at Kangwon National University, Prof. Lim gained valuable experience as a Post-Doctoral Research Associate in Agricultural and Biological Engineering at Purdue University in the United States from 2001 to 2004. Throughout his career, he has been committed to both teaching and research, contributing significantly to the fields of watershed management and environmental sustainability.

Research Interests:

Prof. Kyoung Jae Lim’s research interests lie primarily in the fields of watershed management, land use change, and environmental impact assessment. He focuses on understanding the complex interactions between land use and hydrological processes, aiming to develop effective strategies for managing water resources and mitigating environmental degradation. His work often involves the application of Geographic Information Systems (GIS) and remote sensing technologies to analyze and model environmental changes at various scales. Prof. Lim is particularly interested in assessing soil erosion risks and sediment transport dynamics, which are critical for sustainable land management and conservation practices. Through his research, he seeks to contribute to the development of innovative solutions that address pressing environmental challenges, fostering a more sustainable future.

Skills:

Prof. Kyoung Jae Lim possesses a diverse skill set that underpins his expertise in Agricultural and Biological Engineering. He is proficient in the application of Geographic Information Systems (GIS) and remote sensing technologies, which he utilizes to analyze spatial data and assess environmental impacts. His strong analytical skills enable him to model hydrological processes and conduct comprehensive assessments of land use changes and soil erosion risks. Additionally, Prof. Lim has a solid foundation in research methodologies, allowing him to design and execute studies that contribute valuable insights to his field. His ability to collaborate effectively with interdisciplinary teams and communicate complex concepts clearly further enhances his impact as an educator and researcher. Prof. Lim’s commitment to innovation and sustainability positions him as a leading figure in addressing contemporary environmental challenges.

Conclution:

Prof. Kyoung Jae Lim’s comprehensive academic background, extensive research contributions, and dedication to the field of Agricultural and Biological Engineering make him an outstanding candidate for the Research for Best Researcher Award. His innovative approaches and significant findings have greatly advanced knowledge in environmental management, water resources, and soil conservation, showcasing his commitment to addressing pressing global challenges.

Publication Top Noted:

  • Forecasting land use change and its environmental impact at a watershed scale
    • Cited By: 620
    • Year: 2005
    • Journal: Journal of Environmental Management, 76(1), 35-45
  • AUTOMATED WEB GIS BASED HYDROGRAPH ANALYSIS TOOL, WHAT1
    • Cited By: 587
    • Year: 2005
    • Journal: JAWRA Journal of the American Water Resources Association, 41(6), 1407-1416
  • Global rainfall erosivity assessment based on high-temporal resolution rainfall records
    • Cited By: 532
    • Year: 2017
    • Journal: Scientific Reports, 7(1), 1-12
  • GIS-based sediment assessment tool
    • Cited By: 318
    • Year: 2005
    • Journal: Catena, 64
  • EFFECTS OF INITIAL ABSTRACTION AND URBANIZATION ON ESTIMATED RUNOFF USING CN TECHNOLOGY
    • Cited By: 150
    • Year: 2006
    • Journal: JAWRA Journal of the American Water Resources Association, 42(3), 629-643
  • Soil erosion risk assessment of the Keiskamma catchment, South Africa using GIS and remote sensing
    • Cited By: 137
    • Year: 2012
    • Journal: Environmental Earth Sciences, 65, 2087-2102
  • Runoff impacts of land-use change in Indian River Lagoon watershed
    • Cited By: 121
    • Year: 2002
    • Journal: Journal of Hydrologic Engineering, 7(3), 245-251
  • Assessment of soil erosion and sediment yield in Liao watershed, Jiangxi Province, China, using USLE, GIS, and RS
    • Cited By: 119
    • Year: 2010
    • Journal: Journal of Earth Science, 21(6), 941-953
  • Effects of calibration on L-THIA GIS runoff and pollutant estimation
    • Cited By: 97
    • Year: 2006
    • Journal: Journal of Environmental Management, 78(1), 35-43
  • Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application
    • Cited By: 90
    • Year: 2010
    • Journal: Computers & Geosciences, 36(7), 936-944
  • Temporal variations in baseflow for the Little River experimental watershed in South Georgia, USA
    • Cited By: 74
    • Year: 2017
    • Journal: Journal of Hydrology: Regional Studies, 10, 110-121
  • An assessment of the utilization of waste resources for the immobilization of Pb and Cu in the soil from a Korean military shooting range
    • Cited By: 73
    • Year: 2012
    • Journal: Environmental Earth Sciences, 67, 1023-1031