Gan Xu – Artificial Intelligence – Best Researcher Award

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Gan Xu – Artificial Intelligence – Best Researcher Award

Mr. Gan Xu distinguished academic and researcher in the field Artificial Intelligence.

🌐 Professional Profile

Educations📚📚📚

He is currently pursuing a Ph.D. in Finance at the Capital University of Economics and Business in Beijing, China, since September 2021. Prior to this, he completed his Master’s in Finance from Beijing Union University, Beijing, China, graduating in June 2021. His academic journey began with a Bachelor’s degree in Biotechnology, which he obtained from Guilin Medical University, Guilin, Guangxi, China, in June 2010.

Research Experience

He participated in the Project of the National Social Science Foundation of China, focusing on the “Research on Level Measurement, Spatial and Temporal Divergence, and Improvement Path of Rural Financial Services for Rural Revitalization” (19BJY158), where he was mainly responsible for the research design of some sub-topics and participated in enterprise research. Additionally, he contributed to the Key Topic of the China Mobile Communication Federation on the “Research on the Application of Blockchain Technology in Finance” (CMCA2018ZD01), taking charge of the research design of certain sub-topics and writing research reports. Furthermore, he was involved in the research project on “Financial Support for Deepening Financial Services for Private and Micro and Small Enterprises” as part of the Comprehensive Reform Pilot City Project in Jincheng City, Shanxi Province, where he was responsible for independently participating in application writing.

Social Experience

He has co-authored several significant publications, including “Financial Density of Village Banks and Income Growth of Rural Residents” with Yang, G.Z., Xu, G., Zhang, Y., and others, published in Economic Issues in 2021. Additionally, he contributed to “Knowledge Mapping Analysis of Seven Decades of Rural Finance Research in China” with Zhang, F., Xu, G., Zhang, X.Y., and Cheng, X., which appeared in Rural Finance Research in 2020. He also co-authored “A Review of Blockchain Applications in the Financial Sector” with Zhang, F. and Cheng, X., published in Technology for Development in 2019.

Honors

  • Received Beijing Outstanding Graduates in 2020
  • Outstanding graduate of Beijing Union University in 2020
  • First Prize of Excellent Paper in the First Annual Meeting of the Financial Technology Professional Committee of the China Society for Technology Economics, 2019
  • Second Prize of Excellent Paper in the 13th China Rural Finance Development Forum, 2019
  • Second Prize of Excellent Paper of the 9th Annual Conference of China Regional Finance and Xiongnu Financial Technology Forum, 2019

📝🔬Publications📝🔬

Nagesh Dewangan – Interpretation Analysis of Deep Learning Models-Best Researcher Award

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Nagesh Dewangan – Interpretation Analysis of Deep Learning Models-Best Researcher Award

Mr. Nagesh Dewangan distinguished academic and researcher in the field Interpretation Analysis of Deep Learning Models. As a dedicated researcher in the field of machinery condition monitoring, his work has focused on advancing knowledge in activity monitoring and fault diagnosis for heavy machinery using deep learning models. His research has led to several key advancements, particularly in the areas of machinery activity recognition and motor fault diagnosis. He has worked on projects focusing on the cycle time of dumper activities and real-time fault diagnosis of motors using acceleration signals. The studies were conducted in both laboratory and real environments, providing comprehensive data for robust analyses. His work has resulted in the development of innovative methodologies and technologies. He has contributed to the creation of new algorithms for activity recognition using convolutional neural networks (CNNs) and developed approaches to enhance the generalizability of models across different environments. Collaborations with institutions like CSIR-Central Institute of Mining and Fuel Research Dhanbad, India, and industry partners like Coal India Limited, India, have enriched his research.

 

🌐 Professional Profile

Educations📚📚📚

He is currently a Ph.D. research scholar in the Acoustics and Condition Monitoring Laboratory, Mechanical Engineering Department, Indian Institute of Technology Kharagpur, India. He received his B.E. degree in Mechanical Engineering from the Bhilai Institute of Technology Durg, India, in 2016, and his M.Tech. degree in Maintenance Engineering & Tribology from the Indian Institute of Technology Dhanbad, India, in 2019. His research interests are in the areas of Mining Machinery, Condition Monitoring, Signal Processing, Fault Diagnosis, Real-time Application, Internet of Things, Machine Learning, and Deep Learning for industry-oriented Product Design and Development. Throughout his academic career, he has been involved in numerous research projects focused on improving machinery efficiency and safety, particularly in the mining industry. His recent work includes analyzing the cycle time of dump truck activities, fuel consumption, and implementing Convolutional Neural Networks for activity recognition.

Experience

He has published a paper in the reputed journal Automation in Construction, where he critically evaluates existing methods and proposes innovative solutions. Additionally, he has co-authored two papers in reputed journals, such as Engineering Transactions and the International Journal of Chemical Engineering. He has also presented his work at various prestigious conferences, such as the International Conference on Mechanical Power Transmission 2019 (IIT Madras), 17th International Conference on Vibration Engineering and Technology of Machinery 2022 (Institute of Engineering, Nepal), National Conference on Condition Monitoring 2023 (NSTL, Visakhapatnam), and World Congress on Engineering Asset Management (RMIT University, Vietnam), sharing his findings and insights with the academic and professional community. For his research work, he predominantly uses MATLAB, Python, LabVIEW, and NI Multisim.

 

📝🔬Publications📝🔬

Hedieh Sajedi – Machine learning – Best Researcher Award

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Hedieh Sajedi – Machine learning – Best Researcher Award

Dr. Hedieh Sajedi  distinguished academic and researcher in the field Machine learning.  Her research interests encompass a wide range of advanced topics, including deep learning and machine learning, where she delves into the development and refinement of algorithms that enable computers to learn from and make decisions based on data. She is also deeply involved in multimedia processing, exploring techniques to enhance and manipulate various forms of media, such as images, videos, and audio. Additionally, her work in data mining and information retrieval focuses on extracting meaningful patterns and insights from large datasets, improving the efficiency and accuracy of information retrieval systems. Furthermore, she investigates bio-inspired algorithms, drawing inspiration from natural processes to create innovative computational methods that solve complex problems.

🌐 Professional Profile

Educations📚📚📚

She completed her Ph.D. in Artificial Intelligence and Robotics at Sharif University of Technology in May 2010, following her M.Sc. in the same field from the same institution, which she earned in August 2005. Prior to her postgraduate studies, she obtained her B.Sc. in Computer Software Engineering from Amir Kabir University of Technology in September 2002.

Work Experience:

She has delivered several invited talks on various topics, including “Computer vision and machine learning for medical image analysis” at the Children’s International Research Center in Washington DC, USA, in July 2022, and “Age Prediction based on brain MRI images” at Pompeu Fabra University in Barcelona, Spain, in June 2022. Additionally, she discussed a “Blind Spot Warning System based on Vehicle Analysis in Stream Images” at the same university and “Brain Age Estimation based on Brain MRI Images” at Sehir University of Istanbul, Turkey, in March 2018. Earlier, in March 2014, she presented on the “Application of Steganography and Steganalysis Methods in Medical and Healthcare Systems” at the University of Pavia, Italy. Her executive activities include serving as the Scientific Chair of the International Conference on Pattern Recognition and Image Analysis (IPRIA) in 2023, head of the Computer Science Department from 2018 to 2022, and Scientific Chair of the 6th International Conference on Pattern Recognition and Image Analysis at the University of Tehran in 2022. She also held the position of Head of Computer Services and Information Technology in the College of Science from 2018 to 2020 and served as Inspector of the Image Processing and Machine Vision Society in Tehran, Iran, in 2015 and 2017. Her funded projects include research on the “Detection and Classification of Circular Objects on the Basis of Convolutional Neural Network (CNN)” funded by the Iran National Science Foundation (INSF) from 2021 to the present, “Investigating Brain Health from Brain MRI Images Using Machine Learning Methods,” partially funded by the Institute for Research in Fundamental Sciences (IPM) from 2018 to 2019, “Brain Age Estimation with Mathematical Modeling” funded by INSF from 2017 to 2018, and the development of “A High-Security and High-Capacity Steganography System” funded by INSF from 2011 to 2014.

Honors & Awards

She was recognized as a member of the University of Tehran Top Researchers Club in 2022 and received the Erasmus Mobility Award from the European Union in the same year. Additionally, she was honored with the Honors Program Graduate Award from Sharif University of Technology for the period from 2006 to 2010. Since 2009, she has been an active member of the Scientific Society for Image Processing and Machine Vision.

She has been an instructor at the University of Tehran since 2013, teaching courses such as “Machine Learning,” “Artificial Intelligence,” “Data Mining,” and “Digital Image Processing” in the Department of Computer Science. She has also instructed “Advanced Topics in Artificial Intelligence” since 2020 and “Advanced Information Retrieval” from 2017 to 2020. Additionally, she taught “Advances in AI” from 2013 to 2020 and “Machine Learning in Physics” from 2018 to 2019. Her teaching portfolio includes courses for Ph.D. students at the Institute of Biochemistry and Biophysics, such as “Advanced Data Structure” in 2018-2019. At AmirKabir University of Technology, she instructed “Machine Learning” from 2010 to 2011 and “Artificial Intelligence” in 2010-2011. She also co-instructed “Machine Vision” at Pompeu Fabra University in Barcelona, Spain, in May 2022. Her experience in bio-inspired computing includes teaching “Evolutionary Computing” at the University of Tehran from 2013 to 2016.

Furthermore, she has taught “Distributed Systems” at Azad University, Qazvin, from 2011 to 2013, and courses such as “Computer Networks,” “Compiler Design and Principles,” and “Introduction to Programming” at the University of Tehran. She also taught “Operating Systems,” “Introduction to Programming,” and other foundational courses at Tarbiat Moallem University from 2006 to 2008. Her early teaching roles include instructing “Introduction to Programming” at Sharif University of Technology in 2006-2007 and several technical and scientific presentation courses at AmirKabir University of Technology from 2009 to 2011.

📝🔬Publications📝🔬

Asif Hamid- Deep learning – Best Researcher Award

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Asif Hamid- Deep learning – Best Researcher Award

Mr. Asif Hamid  distinguished academic and researcher in the field  Deep learning. He has accumulated over four years of experience in writing and publishing research articles for journals and conferences. This experience has provided him with a deep understanding of various writing styles, from scholarly articles to book chapters and industry-focused documentation. His role as a reviewer for many prestigious conferences has also sharpened his critical thinking and editorial abilities.

His expertise is not limited to writing; he is skilled in Python and MATLAB programming, which are crucial for his research projects. He possesses basic skills in HTML and is proficient with MS Office tools—Word, Excel, and PowerPoint—as well as LaTeX software, all vital for creating research papers and presentations. Additionally, his ability to utilize internet applications and implement deep learning techniques demonstrates his aptitude for integrating cutting-edge technology into his research activities.

🌐 Professional Profiles

Educations📚📚📚

He is currently pursuing a Ph.D. at the Islamic University of Science and Technology (IUST) in Awantipora, Jammu & Kashmir, India, a program he began in 2020. Prior to this, he earned his Master of Technology degree in Control and Instrumentation Systems from Jamia Milia Islamia (JMI) in India, where he distinguished himself by securing a CGPA of 9.3 out of 10, placing him in the top 1% of his class. His foundational education was completed at Baba Ghulam Shah Badshah University in Rajouri, Jammu & Kashmir, where he received his Bachelor of Technology degree in Electronics and Communication Engineering, achieving a percentile score of 75.6, which also placed him in the top 1% of his peers.

Conference Papers

• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, May). Discovering low-rank
representations of large-scale power-grid models using Koopman theory. In 2022 Trends in
Electrical, Electronics, Computer Engineering Conference (TEECCON). IEEE.. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, July). Power Grid parameter
estimation using Sparse Identification of Nonlinear Dynamics. In 2022 International
Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) (pp. 1-6).
IEEE. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, Neural network-based time stepping

Awards and Achievements

He has received numerous accolades and support for his academic pursuits. Since 2020, he has been a recipient of the MHRD (Ministry of Human Resource Development, Government of India) fellowship for his Ph.D. studies in the Department of Electrical Engineering at the Islamic University of Science and Technology in Awantipora, Jammu & Kashmir, India, supported by grant number IUST0119013135. In 2019, he successfully qualified the GATE (Graduate Aptitude Test in Engineering) for Electronics and Communication Engineering, scoring 31.67 out of 100. Furthermore, in 2017, he qualified for the M.Tech. program at Jamia Milia Islamia, Delhi, by passing the entrance examination, demonstrating his consistent excellence and competence in his field.

WORKSHOP / SEMINAR / TRAINING / STC attended

1. Presented Discovering low-rank representations of large scale power-grid models using Koopman
theory paper in Electrical, Electronics, Computer Engineering Conference IEEE held on 26-27
may 2022 at Reva University.
2. Presented Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics
paper in the INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROLLER AND
COMPUTING FOR SMART POWER, IEEE 2022 organized by the Department of Electrical
and Electronics Engineering, Sreenidhi Institute of Science And Technology, Hyderabad,
India during 21–23 July 2022.
3. Reviewer for IEEE international conference on applied intelligence and sustainable
computing 2023.
4. Attend in faculty development program entitled “Research Methodology + Publication Ethics”
organised by Department of computer science and engineering IUST, Awantipora form 7-11
Feb 2022.

📝🔬Publications📝🔬

  • Hierarchical deep learning-based adaptive time stepping scheme for multiscale simulations

    Engineering Applications of Artificial Intelligence
    2024-07 | Journal article
    DOI: 10.1016/j.engappai.2024.108430
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Neural network-based time stepping scheme for multiscale partial differential equations

    2023 7th International Conference on Computer Applications in Electrical Engineering-Recent Advances (CERA)
    2023-10-27 | Conference paper
    DOI: 10.1109/cera59325.2023.10455439
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Deep learning assisted surrogate modeling of large-scale power grids

    Sustainable Energy, Grids and Networks
    2023-06 | Journal article
    DOI: 10.1016/j.segan.2023.101031
    Part ofISSN: 2352-4677
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics

    2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)
    2022-07-21 | Conference paper
    DOI: 10.1109/iciccsp53532.2022.9862464
    CONTRIBUTORS: ASIF HAMID BHAT

Wei Zhang – Digital algorithms – Best Researcher Award

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Wei Zhang – Digital algorithms – Best Researcher Award

Dr. Wei Zhang distinguished academic and researcher in the field Digital algorithms. Zhang Wei and Liu Hui have collaborated on several scholarly articles addressing rural economic issues in China. In their 2020 publication in “Jiangsu Agricultural Sciences,” they examined the “Problems and Countermeasures in the Development of Rural Collective Economy,” using Fenyi County, Jiangxi Province as a case study. This article, found in volume 48, issue 21, pages 28-33, discusses specific challenges faced by rural economies and proposes various strategies for improvement.

🌐 Professional Profiles

Educations📚📚📚

From September 2016 to June 2019, he pursued his Bachelor of Marketing at Hefei University of Technology. He continued his studies at Hunan Agricultural University, where he earned a Master of Agricultural and Forestry Economics and Management, completing the program in June 2021. Building on his academic achievements, he began his PhD in Capability Economic Management at the same university in September 2021, with an expected completion date of June 2025.

Research Experience

Zhang Wei and Liu Hui have collaborated on several scholarly articles addressing rural economic issues in China. In their 2020 publication in “Jiangsu Agricultural Sciences,” they examined the “Problems and Countermeasures in the Development of Rural Collective Economy,” using Fenyi County, Jiangxi Province as a case study. This article, found in volume 48, issue 21, pages 28-33, discusses specific challenges faced by rural economies and proposes various strategies for improvement. Following this, in 2022, they published an article in “Price Theory and Practice,” where they analyzed the effectiveness of reforms in the rural collective property rights system from the perspective of farmer participation. This research, featured in the March 2022 issue on pages 169-172 and 205, was underpinned by a survey of 315 farmer households across Hunan and Jiangxi provinces, offering valuable insights into the impact of these reforms on rural communities.

Project experience

He hosted the 2023 Hunan Provincial Postgraduate Research Innovation Project Key Project, CX20230730, which focused on the Research on the Contract and Performance of Farmland Infrastructure Governance under Endowment Heterogeneity. He also played a significant role in contributing to several major research projects. He participated in writing a major project for the Hunan Provincial Social Science Fund, numbered 23ZWA14, which involved researching the Current Situation and Countermeasures of Rural Collective Economic Development in Hunan Province. Additionally, he contributed to the general project of the Hunan Provincial Social Science Fund, 21YBA079, which examined the governance mechanism and performance of high-standard farmland in the context of food and ecological security. His research contributions extended to the Hunan Provincial Natural Science Foundation’s general project, 2023JJ30312, focusing on the mechanism and performance of digital technology in empowering farmland water conservancy facilities. Moreover, he was involved in writing for a project under the Hunan Provincial Development and Reform Commission that researched coordinated food and ecological security in the middle and lower reaches of the Yangtze River plain, considering “resources-factors-policies.”

Personal honor

He achieved notable recognition in various academic competitions and forums. At the 2021 Modern Agricultural Development Forum and the First “World Agriculture” Workshop in the context of “Dual Cycles,” he won the second prize in the paper competition. His research excellence continued into the following year when he won the first prize for outstanding paper at the 2022 Hunan Rural Economics Association Annual Meeting. Additionally, he received the award for the second “Economic Management Quantitative Research Methods” Excellent Paper at the School of Economics, Hunan Agricultural University. He also actively participated in advanced training sessions, including the “Jiangsu Province Applied Economic Research Methodology” workshop organized by the Economics Graduate Education Steering Committee of Jiangsu Province and the School of Economics and Management of Nanjing Agricultural University, where he earned the title of qualified student. Furthermore, he attended the “2021 Summer Econometrics and Scientific Research Methods Lecture Series” at the School of Statistics and Mathematics of Zhongnan University of Economics and Law, also achieving the status of qualified student.

 

📝🔬Publications📝🔬

Jianxiao Wang – Data Science – Best Researcher Award

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 Dr. Jianxiao Wang  distinguished academic and researcher in the Data Science and Smart Grid. He is currently an Assistant Professor at the National Engineering Laboratory For Big Data Analysis and Applications, Peking University, and a Distinguished Researcher at the PKU-Changsha Institute for Computing and Digital Economy. He obtained Bachelor’s degrees in Engineering and Economics from Tsinghua University in 2014, and completed his Ph.D. in Electrical Engineering from Tsinghua University in 2019. From 2016 to 2017, he served as a visiting researcher at Stanford University and the University of California, Berkeley. From 2019 to 2020, he worked as a project leader at the Ministry of Science and Technology of the People’s Republic of China, contributing to the 14th Five-Year Plan for High Tech Development in the field of energy and transportation, and conducting research on the 2035 National Science and Technology Development Strategy in China.

His research interests revolve around data-driven decision making for energy storage and renewable power systems, focusing on evaluating the levelized cost and designing national low-carbon pathways for emerging technologies such as AIGC, roadside photovoltaics, electric and fuel cell vehicles, power-to-hydrogen, green ammonia chemical industry, and carbon capture and storage utilization. As the first or corresponding author, he has published 1 paper in Nature Sustainability, 2 papers in Nature Communications, 1 paper in Cell The Innovation, 1 paper in Cell Patterns, and 2 papers in Cell iScience. Additionally, he has authored 99 papers published in top journals and conferences, including two 0.1% ESI Hot Paper, two 1% ESI Highly Cited Paper, and four IEEE Conference Best Paper Awards. He has applied for 35 China Invention Patents and 2 US Patents. Furthermore, he has published one Springer monograph as the first author, one IEEE Press monograph as a contributing author, and coauthored three Chinese monographs. The research article in Nature Sustainability was selected as a cover paper candidate and received an official report from Johns Hopkins University. As of August 2023, the research article in Nature Communications has been accessed over 10,000 times and cited 147 times, selected as a 0.1% ESI Hot Paper and officially reported by People’s Daily.

🌐 Professional Profiles

Educations📚📚📚

He pursued his academic journey at Tsinghua University, where he completed his Bachelor’s degrees in Electrical Engineering from the Department of Electrical Engineering and Economics from the School of Economics and Management from August 2010 to July 2014. Subsequently, he continued his academic pursuit at Tsinghua University, specializing in Electrical Engineering, where he earned his Ph.D. from the Department of Electrical Engineering from August 2014 to January 2019. During his Ph.D., he achieved a GPA of 92.8, ranking 2nd out of 55 students. His outstanding performance led to his recognition as an Outstanding Doctoral Graduate and his dissertation being acknowledged as one of the top 2% at Tsinghua University. Additionally, he was awarded the Tsinghua University President Jiang Nanxiang Scholarship, a prestigious honor bestowed upon 10 Ph.D. students annually.

As part of his academic journey, he expanded his horizons through visiting researcher positions at renowned institutions. From April 2017 to December 2017, he conducted research as a visiting researcher at the University of California, Berkeley. Prior to this, from November 2016 to December 2017, he engaged in research activities as a visiting researcher at Stanford University. Furthermore, he broadened his research experience with a visiting researcher position at Texas A&M University from July 2013 to September 2013.

Research Experience

He has been serving as an Assistant Professor at the National Engineering Laboratory for Big Data Analysis and Applications at Peking University since June 2022. Concurrently, he holds the position of Distinguished Researcher at the PKU-Changsha Institute for Computing and Digital Economy. Prior to his current roles, from October 2019 to September 2020, he worked as a Project Manager at the Ministry of Science and Technology of the People’s Republic of China. Additionally, he gained valuable experience as a Lecturer at North China Electric Power University from June 2019 to May 2022.

He has received numerous accolades and awards for his outstanding contributions to science, technology, and innovation. In 2023, he was honored with the Second Prize of the Science and Technology Progress Award from the China Electrotechnical Society for his work on “Transmission and Distribution Network Coordinated Control Technology and Applications Under High Distributed Energy Penetration.” Additionally, he received the Second Prize of the Power Innovation Award from the China Electric Power Union for his achievements in “Technology and Application for Data Value-driven Hierarchical Scheduling of Renewable Power Systems.” He was also recognized with the Wu Wen-Jun Artificial Intelligence Outstanding Youth Award by the Chinese Association for Artificial Intelligence for his research on “Physics-informed Data Driven Theory for Smart Grid Operation.” Furthermore, he was selected for the Wiley Open Science Excellent Author Program.

In 2022, he was honored with the Young Scientist Award by the Ministry of Science and Technology of China. He has also been recognized under the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology for his work on “Smart City Energy System Operation Considering Adaptive Consistency Control of Water Electrolysis.” He received a Gold Medal at the Geneva International Exhibition of Inventions for his contribution to “Edge-intelligence Control Technology and System of Solar+Storage Powered Microgrid.” Additionally, his paper titled “Defending Against Adversarial Attacks by Energy Storage Facility” earned the IEEE PES General Meeting Best Paper Award.

He has been recognized for his exceptional service and expertise, receiving the IEEE Transactions on Sustainable Energy Excellent Reviewer Award multiple times. He was also listed in the Forbes China 30 Under 30 Elite List and acknowledged as one of the Outstanding Young Science and Technology Talents by the China Renewable Energy Society. In 2020, he was honored as one of the Beijing Outstanding Young Talents and recognized for his contributions to energy science and technology by the China Energy Research Association. Furthermore, his innovative work on “Renewable Energy-Dominated Virtual Power Plant” secured a place in the top 10 of the Elsevier Renewable Transformation Challenge. He has also been acknowledged with various awards for his inventions and innovations, including the Silver Award at the Beijing Invention and Innovation Competition and the Gold Award at the China Invention Exhibition. Additionally, he has been recognized as a Youth Of China’s High-End Technology Innovation Think Tank for his contributions to the technological development and environmental governance benefits of China’s photovoltaic and energy storage industry.

Monograph

He has authored several publications across various domains, showcasing his expertise and contributions to the field. As the first author, he collaborated with colleagues on the book “Sharing Economy in Energy Markets: Modeling, Analysis and Mechanism Design,” published by Springer in 2022. Additionally, he authored chapters 28-30 in the book “Microgrids: Theory and Practice,” published by IEEE Press in 2023.

Furthermore, he has contributed to monographs in different capacities. In the book “Introduction to the Electricity Spot Market: Trading Strategy and Profit Model for Information Driven Growth,” published by Mechanical Industry Press in 2021, he co-authored chapters 2, 4, and 6. Additionally, he was part of the team contributing to chapter 7 in “2060 China Carbon Neutrality,” published by Chemical Industry Press in 2022. He also co-authored chapters 1 and 2 in “Introduction to New-type Power Systems,” published by the China Association for Science and Technology Carbon Peak and Carbon Neutrality Series in 2022.

Representative Academic Service

He has been recognized for his exemplary contributions and leadership in various professional capacities. In 2023, he served as the Youth Editor for Cell The Innovation, a prestigious role reflecting his expertise in the field, with the journal boasting an Impact Factor of 32.1. He was also appointed as a National Graduate Education Evaluation and Monitoring Expert by the Ministry of Education, showcasing his commitment to education excellence.

In 2022, he was honored as a Distinguished Researcher under the Beijing “Thousands of People Entering Thousands of Enterprises” program, highlighting his significant contributions to research and innovation. He was also recognized as a National Excellent Educator in the National Simulation Innovation Application Competition and appointed as an Instructor by the IEEE Industry Applications Society (IAS) at Peking University. Additionally, he received accolades as an Excellent Editor from the IET Energy Conversion and Economics.

In 2021, he was appointed as an Executive Member of the IEEE Power and Energy Society (PES) China, underscoring his leadership and expertise in the field. He also served as a Youth Working Committee Member of the 9th Council of the Chinese Electrotechnical Society, demonstrating his active involvement in professional organizations.

In 2020, he was recognized as an expert in the 6th National Technology Prediction by the Ministry of Science and Technology of China, further acknowledging his expertise and contributions to technology development. Additionally, he joined the Editorial Board of IET Renewable Power Generation, contributing his insights to the publication.

From 2019 to 2022, he chaired panel sessions at the IEEE PES General Meeting, showcasing his leadership and expertise in the field. Through these diverse roles and responsibilities, he has demonstrated his commitment to advancing research, education, and innovation in his field.

Representative Research Project

He has undertaken numerous significant research projects as the primary investigator, showcasing his leadership and expertise in the field. From November 2022 to October 2025, he leads the National Key R&D Plan project titled “Resilience Enhancement Technology for Large Urban Power Grids Amidst Extreme Events,” with a funding of 4.5 million Chinese yuan. Similarly, from January 2023 to December 2026, he is leading a project funded by the National Natural Science Foundation of China titled “Renewable-dominated Power System Flexible Ramping Operation Considering Consistency Control of Water Electrolysis Multiphysics,” with a grant of 540 thousand Chinese yuan.

In previous years, he has led various other research projects funded by prestigious organizations such as the National Natural Science Foundation of China and the State Grid Corporation of China. These projects cover a wide range of topics including virtual power plant market operation, energy systems integration, self-sustained energy systems for highways, and collaborative regulation technology for large-scale energy storage clusters. Through his involvement in these projects, he has made significant contributions to advancing research and innovation in the energy sector.

📝🔬Publications📝🔬

1 Jianxiao Wang#, Liudong Chen#, Zhenfei Tan, Ershun Du, Nian Liu, Jing Ma, Mingyang Sun, Canbing Li, Jie Song,
Xi Lu*, Chin-Woo Tan*, Guannan He*. Inherent spatiotemporal uncertainty of renewable power in China. Nature
Communications, 2023, 14: 5379.
2 Yang Yu#, Jianxiao Wang#, Qixin Chen, Johannes Urpelainen, Qingguo Ding, Shuo Liu, Bing Zhang*.
Decarbonization efforts hindered by China’s slow progress on electricity market reforms. Nature Sustainability.
2023, 6, 1006-1015.
Special Comments from Johns Hopkins University:

China’s Sluggish Electricity Market Reforms Impede Decarbonization Efforts


Representative Publications
3 Jianxiao Wang#, Haiwang Zhong*, Zhifang Yang, Mu Wang, Daniel M Kammen*, Zhu Liu, Ziming Ma, Qing Xia
and Chongqing Kang. Exploring the trade-offs between electric heating policy and carbon mitigation in China,
Nature Communications, 2020, 11: 6054. (0.1% ESI Hot Paper) https://doi.org/10.1038/s41467-020-19854-y
Special Comments from People’s Daily and Tsinghua University News:
https://www.tsinghua.edu.cn/info/1175/21483.ht

4 Jianxiao Wang#, Feng Gao#, Yangze Zhou, Qinglai Guo, Chin-Woo Tan, Jie Song, Yi Wang*. Data sharing in energy
systems. Advances in Applied Energy, 2023, 10: 100132.
AEii International Applied Energy and EnergyVision Youth Scientists Forum Report:
https://mp.weixin.qq.com/s/9FyaH55gpaKFirXhlrboGg
5 Jianxiao Wang#, Haiwang Zhong*, Zhifang Yang, Xiaowen Lai, Qing Xia, Chongqing Kang. Incentive mechanism
for clearing energy and reserve markets in multi-area power systems. IEEE Transactions on Sustainable Energy, 2020,
11(4): 2470 – 2482.
6 Jianxiao Wang#, Junjie Qin, Haiwang Zhong*, Ram Rajagopal, Qing Xia, Chongqing Kang. Reliability value of
distributed solar+storage systems amidst rare weather events. IEEE Transactions on Smart Grid, 2019, 10(4): 4476 –
4486.
7 Jianxiao Wang#, Haiwang Zhong*, Xiaowen Lai, Qing Xia, Yang Wang, Chongqing Kang. Exploring key weather
factors from analytical modeling toward improved solar power forecasting. IEEE Transactions on Smart Grid, 2019,
10(2): 1417-1427.
8 Jianxiao Wang#, Haiwang Zhong, Qing Xia*, Chongqing Kang. Optimal planning strategy for distributed energy
resources considering structural transmission cost allocation. IEEE Transactions on Smart Grid, 2018, 9(5):
5236-5248.
9 Jianxiao Wang#, Haiwang Zhong, Chin-Woo Tan, Xiao Chen, Ram Rajagopal, Qing Xia*, Chongqing Kang.
Economic benefits of integrating solar-powered heat pumps in a CHP system. IEEE Transactions on Sustainable
Energy, 2018, 9(4): 1702-1712.
10 Jianxiao Wang#, Haiwang Zhong, Ziming Ma, Qing Xia*, Chongqing Kang. Review and prospect of integrated.

Jorge Laureano Moya Rodríguez – Neural Networks – Best Researcher Award

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Jorge Laureano Moya Rodríguez – Neural Networks

 Prof Dr.  Jorge Laureano Moya Rodríguez distinguished academic and researcher in the field Neural Network.  Jorge Laureano Moya Rodríguez is a Professor Emeritus at the Central University “Marta Abreu” de las Villas. Cuba. He received his Ph.D. in Mechanical Engineering at this university in 1994. He published over a three hundred papers in professional journals and he has authored several books in mechanical and electrical engineering. He has several international and national awards, including some from the Academy of Sciences of Cuba. He has lectured in different Universities of Spain, México, Nicaragua and Brazil. He is currently visiting professor at the Federal University of Bahia in Brazil. Dr. Moya’s research interests are Multiobjective Optimization, Logistics, Computer Aided Design, and Computer Aided Engineering.

Ele é também membro da ERASMUS MUNDUS ASSOCIATION (EMA) e da Associação Mexicana de Modelagem Numérica e Engenharia (AMMNI). Reconhecido como bolsista de produtividade em Pesquisa pelo CNPq (nível 2) e consultor ad hoc do CNPq, ele contribui como árbitro para diversas revistas científicas e instituições acadêmicas em países como Venezuela, Colômbia, Peru e Cuba. Com uma ampla lista de mais de 50 projetos de pesquisa concluídos e implementados em Cuba, ele é considerado Professor de Mérito pela Universidade Central Marta Abreu de Las Villas. Sua atuação como professor abrange cursos de pós-graduação e disciplinas de mestrado em várias universidades, incluindo a Universidade Federal do Espírito Santo (Brasil), Universidade Veracruzana (México), Universidade Técnica do Estado de Aragua (Venezuela) e Universidade Nacional de Engenharia (Nicarágua). Ele também coordenou o Mestrado em Engenharia Mecatrônica em várias universidades na Venezuela e trabalhou como professor convidado em diversas instituições no México, Peru e Espanha. Anteriormente, ele foi pesquisador do ITEGAM, professor visitante na Universidade Federal do Espírito Santo e na Universidade Federal da Bahia.

 

🌐 Professional Profiles

Educations: 📚🎓

Jorge Laureano Moya Rodríguez, known in bibliographic citations as J. L. M. Rodríguez, J. L. Moya, Jorge Moya, Jorge Laureano Moya Rodríguez, J. Moya, Jorge Rodríguez, Jorge L. Moya Rodríguez, or variations thereof, is affiliated with the University Federal da Bahia, where he works within the Program of Industrial Engineering Postgraduate Studies.

He completed a postdoctoral position in 2011 at the Universidad de Oviedo, UNIOVI, Spain, funded by the Agencia Española de Colaboración Internacional, AECI, Spain. The research was in the field of Engineering.

In 2008, he undertook a postdoctoral fellowship at the Universidad de Oviedo, UNIOVI, Spain, funded by ERASMUS MUNDUS, EM, Germany. The research focus was in Engineering.

In 2005, he conducted postdoctoral research at the Universidad Católica de Leuven, KLU, Belgium, supported by VLIR, VLIR, Belgium. The research was within the field of Engineering.

Publication

 

Peican Zhu -Natural language processing (NLP) – Best Researcher Award

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Peican Zhu -Natural language processing (NLP)

Dr.Peican zhu   distinguished academic and researcher in the field of Natural lanuage processing. Since May 2022, he has been serving as an Associate Professor at the School of Artificial Intelligence, Optics, and Electronics (iOPEN) within Northwestern Polytechnical University. Prior to this, from March 2016 to April 2022, he held the position of Associate Professor at the School of Computer Science, specifically contributing to the Center for Multidisciplinary Convergence Computing at the same university. Throughout his tenure, he has been actively engaged in academia, making significant contributions to the field of computer science and multidisciplinary convergence computing.

Education

He pursued his academic journey with a Ph.D. from the University of Alberta, Canada, spanning from September 2011 to August 2015 under the guidance of Dr. J. Han. Following this, he continued to expand his knowledge and expertise by obtaining a Master’s degree at Northwestern Polytechnical University, China, from September 2008 to April 2011, with Dr. X. Gao as his supervisor. His educational foundation was laid during his undergraduate studies at Northwestern Polytechnical University, China, where he earned his Bachelor’s degree from September 2007 to June 2008. Throughout his educational pursuits, he has demonstrated a commitment to academic excellence and a passion for advancing his understanding in the fields of computer science and related disciplines.

Professional Profiles:

Research Interest

Social computation and network science; Complex networks; Epidemic spreading and behavior vaccination; Reliability evaluation and criticality analysis Monte Carlo simulations and stochastic analysis; Evolutionary game theory; Data Science

Honors & Awards

He has garnered several prestigious honors and awards throughout his career, underscoring his dedication and contributions to various domains. In 2014, he received a Travel Award from the Canadian Institutes of Health Research (CIHR) to attend the Canadian Bioinformatics Workshops, followed by another CIHR Travel Award in 2013 for the 11th Asia Pacific Bioinformatics Conference (APBC). Notably, from May 2014 to May 2015, he was honored with the Alberta Innovates Graduate Student Scholarship, including the AITF (Alberta Innovates Technology Futures) Top-Up Award, recognizing his outstanding achievements during his graduate studies in Alberta, Canada.

Furthermore, his excellence in the field has been acknowledged with the Qian Weichang Prize in Chinese Information Processing Science and Technology, a prestigious award he received in November 2018. Adding to his list of accolades, in March 2021, he was bestowed with the Natural Science Award of Shaanxi Province, earning the coveted First Prize No. 3. These honors underscore his significant contributions and achievements in the realms of bioinformatics, technology, and information processing.

Academic Activities

He actively engages in various academic activities, particularly as a referee for numerous peer-reviewed journals, showcasing his commitment to contributing to the scholarly community. Notably, he has served as a referee for esteemed journals such as Reliability Engineering and System Safety, Microelectronic Reliability, Chaos Solitons & Fractals, Chaos, Annals of Operations Research, Scientific Reports, BMC System Biology, Biosystems, IEEE Biomedical Circuits and Systems, IEEE Transactions on Circuits and Systems II: Express Briefs, BioMed Research International, IEEE Access, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Reliability, IEEE Transactions on Industrial Electronics, Mathematical Problems in Engineering, DATE, DFT, ECCV, KSEM, and more.

In addition to his role as a reviewer, he is an active member of prominent professional organizations, including the Institute of Electrical and Electronics Engineers (IEEE) and the Reliability Branch of the China Operational Research Society. His affiliations extend to memberships in the China Computer Federation (CCF), Chinese Society of Optimization, Overall Planning and Economic Mathematics, Chinese Association for Artificial Intelligence, Association for the Advancement of Artificial Intelligence, and the Chinese Association of Automation.

Moreover, he contributes to the academic community as an associate editor for journals such as Humanities & Social Sciences Communications and Heliyon. His editorial responsibilities also include serving as a guest editor for Frontiers in Physics, Complexity (Hindawi), Mathematics (mdpi), and Applied Sciences (mdpi). These diverse roles highlight his extensive involvement and leadership within the academic and research realms.

Grants

He has been actively involved in securing research grants, showcasing his leadership and expertise in various domains. As the principal investigator, he leads the Key Research and Development Program of Shaanxi Province (Grant No. 2022KW-26) from January 2022 to December 2023, focusing on the research of intelligent decision theory and its applications. Furthermore, he spearheads the National Key Research and Development Project of China (Grant No. 2020AAA0107704) from November 2021 to October 2023, dedicated to enhancing the robustness and automatic attack and defense mechanisms of AI systems.

In the realm of network populations, he serves as the principal investigator for the National Science Foundation of China (Grant No. 62073263) from January 2021 to December 2024, exploring the mechanisms of information dissemination. His earlier contributions include leading projects such as the Stochastic Analysis of Two-layered Multiplex Networks funded by the National Science Foundation for Young Scientists of China (Grant No. 61601371) from January 2017 to December 2019.

His research extends to the aerospace domain, as seen in projects like the Reliability Evaluation of Wireless Sensor Networks in Aerospace Crafts through Stochastic Analysis (Aerospace Science and Technology Fund, January 2017 – December 2017). Additionally, he delves into reliability evaluation and optimization of complex systems through the Natural Science Basic Research Plan in Shaanxi Province of China (Grant No. 2018JQ6075) from January 2018 to December 2019.

Participating as the principal investigator and project participant in various national and provincial research initiatives, he addresses diverse topics, including epidemic spreading in dynamical complex networks, game decision under incomplete information, multi-source spatio-temporal large data perception, fusion, and analysis in public security, multi-source heterogeneous large data fusion and analysis based on network public security, and key technologies of new infrastructure’s automatic network attack-defense countermeasure. These grant projects underscore his multifaceted contributions to advancing knowledge and innovation in his field.

Publication

  1. A stochastic computational approach for accurate and efficient reliability evaluation
    J Han, H Chen, J Liang, P Zhu, Z Yang, F Lombardi
    IEEE Transactions on Computers 63 (6), 1336-1350
  2. Investigation of epidemic spreading process on multiplex networks by incorporating fatal properties
    P Zhu, X Wang, S Li, Y Guo, Z Wang
    Applied Mathematics and Computation 359, 512-524- 2019
  3. Investigating the co-evolution of node reputation and edge-strategy in prisoner’s dilemma game
    P Zhu, X Wang, D Jia, Y Guo, S Li, C Chu
    Applied Mathematics and Computation 386, 125474 – 2020
  4. A stochastic approach for the analysis of dynamic fault trees with spare gates under probabilistic common cause failures
    P Zhu, J Han, L Liu, F Lombardi
    IEEE Transactions on Reliability 64 (3), 878-892 – 2015
  5. Properties and structural analyses of USA’s regional electricity market: a visibility graph network approach
    J Hu, C Xia, H Li, P Zhu, W Xiong
    Applied Mathematics and Computation 385, 125434 – 2020
  6. Lévy noise promotes cooperation in the prisoner’s dilemma game with reinforcement learning
    L Wang, D Jia, L Zhang, P Zhu, M Perc, L Shi, Z Wang
    Nonlinear Dynamics 108 (2), 1837-1845 – 2022
  7. Difference and cluster analysis on the carbon dioxide emissions in China during COVID-19 lockdown via a complex network model
    J Hu, J Chen, P Zhu, S Hao, M Wang, H Li, N Liu
    Frontiers in psychology 12, 795142 – 2022
  8. Investigating the effects of updating rules on cooperation by incorporating interactive diversity
    P Zhu, X Hou, Y Guo, J Xu, J Liu
    The European Physical Journal B 94, 1-8 – 2021
  9. Suppression of epidemic spreading process on multiplex networks via active immunization
    Z Li, P Zhu, D Zhao, Z Deng, Z Wang
    Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (7) – 2019
  10. Community detection in temporal networks via a spreading process
    P Zhu, X Dai, X Li, C Gao, M Jusup, Z Wang
    Europhysics Letters 126 (4), 48001 – 2019

 

Guangli Wu – Video Summarization – Best Researcher Award

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Guangli Wu – Video Summarization

prof Dr. Guangli Wu  distinguished academic and researcher in the field  Video summarization.  The existence of software vulnerabilities will cause serious network attacks and information leakage problems. Timely and accurate detection of vulnerabilities in software has become a research focus on the security field. Most existing work only considers instruction-level features, which to some extent overlooks certain syntax and semantic information in the assembly code segments, affecting the accuracy of the detection model. In this paper, we propose a binary code vulnerability detection model based on multi-level feature fusion. The model considers both word-level features and instruction-level features. In order to solve the problem that traditional text embedding methods cannot handle polysemy, this paper uses the Embeddings from Language Models (ELMo) model to obtain dynamic word vectors containing word semantics and other information. Considering the grammatical structure in the assembly code segment, the model randomly embeds the normalized assembly code segment to represent it. Then the model uses bidirectional Gated Recurrent Unit (GRU) to extract word-level sequence features and instruction-level sequence features respectively.

Eduvation

He pursued his academic journey with a solid foundation in computer science and technology, earning a Bachelor’s degree from Shandong Technology and Business University in 2003. Building upon this, he delved into the realm of Computer Application Technology, completing his Master’s degree at Northwest Minzu University in 2007. Driven by a passion for cultural diversity and linguistic exploration, he further expanded his expertise by attaining a doctoral degree in Chinese Minority Ethnic Languages and Literature from Northwest Minzu University in 2011. This educational trajectory reflects his commitment to a multidisciplinary approach, seamlessly blending computer technology with a profound understanding of language and culture.
Professional Profiles:

RESEARCH INTEREST

⚫ Video Summarization
⚫ Temporal Language Localization in videos
⚫ Botnet Detection
⚫ Binary Code Vulnerability Detection
⚫ Video Abnormal Event Detection
FUND PROJECTS
1. Natural Science Foundation of Gansu Province (17JR5RA161, 21JR7RA570)
2. Gansu University of Political Science and Law Major Scientific Research and Innovation Projects
(GZF2020XZDA03)
3. Young Doctoral Fund Project of Higher Education Institutions in Gansu Province (2022QB-123)
4. Gansu Province Higher Education Innovation Fund Project (2017A-068)
5. University-level Innovative Research Team of Gansu University of Political Science and Law
6. Longyuan Youth Innovation and Entrepreneurship Talent Project (2022QB-123)

MAIN SCIENTIFIC PUBLICATIONS

1. Guangli Wu,ShengTao Wang,Shipeng Xu. “Feature fusion over hyperbolic graph convolution networks for
video summarization.” IET Computer Vision,2023.
2. Guangli Wu,Tongjie Xu. “Video Moment Localization Network Based on Text Multi-semantic Clues
Guidance.” Advances in Electrical and Computer Engineering,2023,23(3):85-92.
3. Guangli Wu,Huili Tang. “Binary Code Vulnerability Detection Based on Multi-Level Feature Fusion.” IEEE
Access,2023,11: 63904-63915.
4. Guangli Wu,Shanshan Song,Leiting Li. “Video Summarization Generation Model Based on Transformer
and Deep Reinforcement Learning.” in 2023 8th International Conference on Computer and
Communication Systems (ICCCS). IEEE, 2023: 916-921.
5. Guangli Wu,Shengtao Wang,Liping Liu. “Fast Video Summary Generation Based On Low Rank Tensor
Decomposition.” IEEE Access,2021,9:127917-127926.
6. Guangli Wu,Zhenzhou Guo,Mianzhao Wang,Leiting Li and Chengxiang Wang. “Video Abnormal Event
Detection Based on CNN and Multiple Instance Learning.” in twelfth international conference on signal
processing systems. SPIE,2021:134-139.
7. Guangli Wu,Zhenzhou Guo,Leiting Li and Chengxiang Wang. “Video Abnormal Event Detection Based on
CNN and LSTM.” in 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP).
IEEE,2020: 334-338.
8. Guangli WU,Leiting LI,Zhenzhou GUO,Chengxiang WANG and Yanpeng, YAO. “Video summarization
Based on ListNet Scoring Mechanism.” in 2020 5th International Conference on Computer and
Communication Systems (ICCCS). IEEE,2020: 281-285.
9. Guangli WU,Liping LIU,Chen Zhang and Dengtai TAN. “Video Abnormal Event Detection Based on ELM.”
in 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).IEEE,2019: 367-371

 

Mohamed Shoaib | Applications of Deep Learning

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Mohamed Shoaib |Applications of Deep Learning

Academician/Research Scholar

NTU (Nanyang Technological University, Singapore) DOCTOR OF PHILOSOPHY at the School of Computer Science and Engineering (SCSE) (FULL-TIME) JAN 2023. Working as a full-time Researcher in the fields of Machine Learning, Data Science, and Artificial Intelligence. Working on applications like how to apply AI in Biomedical, Agriculture, and
communication.

 

Professional Profiles:

Education:

  • Information Technology Institute (ITI)
    Diploma in Artificial Intelligence powered by EPITA School of Engineering and Computer Science. APR 2021 – JAN 2022
  • Faculty of Engineering, Menoufia University.
    Master’s degree in Engineering Science. Subject: Utilization of Artificial Intelligence Techniques in Healthcare Applications. (Pre-Master GPA: 3.46/4) Oct 2019 – MARCH 2022

CERTIFICATIONS

  • Udacity Certified -AWS Machine Learning Foundations Nanodegree Program (2021)
  • Data Camp Certified- Data scientist, Data analyst, and Python programming Career Tracks. (2021.
  • IBM Certified – ML, Data Science, NLP, and AI courses. (2020).
  • Udemy Certified – ML, Data Science, NLP, and DL courses. (2019).

publications