Yunge Zou | Computer Science | Best Scholar Award

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Dr. Yunge Zou | Computer Science | Best Scholar Award

Dr. Yunge Zou, Chongqing University, China

Dr. Yunge Zou is a Ph.D. scholar at Chongqing University, specializing in hybrid powertrain design and battery degradation in the Department of Automotive Engineering. He is a talent under the Chongqing Excellence Program and a Shapingba Elite Talent (2023–2025). Dr. Zou has led key projects, including the National Key R&D Program, focusing on high-efficiency powertrain technologies. His contributions include innovative methods like Hyper-Rapid Dynamic Programming, which optimizes multi-mode hybrid powertrains. With multiple patents and high-impact publications, he collaborates with leading automotive firms like Chang’an New Energy, advancing sustainable transportation. 🚗🔋📚

 

Publication Profile

Orcid

Google Scholar

Academic and Professional Background 🔋

Dr. Yunge Zou earned his B.E. degree in Automotive Engineering from Chongqing University, China, in 2018. Currently, he is pursuing his Ph.D. in hybrid powertrain design and optimization at the Vehicle Power System Lab, Department of Automotive Engineering, Chongqing University. Recognized for his exceptional talent, Dr. Zou is part of the prestigious Chongqing Excellence Program and was honored as a Shapingba Elite Talent for 2023–2025. His research focuses on hybrid powertrain topology design, battery degradation, energy management systems (EMS), and enhancing battery life, contributing to sustainable transportation innovation. 📚🔧🌱

 

Research and Innovations 🚗

Dr. Yunge Zou is leading several groundbreaking research projects in the field of hybrid powertrain design and optimization. His work includes the National Key Research and Development Program of China on high-efficiency range extender assembly and electric vehicle integration (2022-2024), with a funding of 2.5 million yuan. He is also working on optimizing hybrid electric vehicle design through the National Science Fund for Excellent Young Scholars (2023-2025). Additionally, he contributes to various projects focusing on hybrid vehicle dynamics, energy efficiency, and low-emission technologies, backed by substantial funding from multiple prestigious organizations. 🛠️⚡

 

🛠️ Research Focus

Dr. Yunge Zou’s research primarily focuses on hybrid powertrain design and optimization for electric and range-extended vehicles. His work includes the development of control strategies and topology design for hybrid systems, aiming to improve fuel economy, efficiency, and reduce emissions. Dr. Zou has made significant advancements in aging-aware optimization and mode-switching mechanisms for multi-mode hybrid vehicles. His contributions also extend to battery degradation, energy management, and the computational efficiency of fuel economy assessment using innovative algorithms like Hyper Rapid Dynamic Programming (HR-DP). His work is instrumental in the evolution of transportation electrification. 🚗⚡

 

Publication Top Notes

  • “Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory” – Energy 242, 122944 (Cited by 14, 2022) 🔋
  • “Aging-aware co-optimization of topology, parameter and control for multi-mode input-and output-split hybrid electric powertrains” – Journal of Power Sources 624, 235564 (Cited by 1, 2024) ⚙️
  • “Design of optimal control strategy for range extended electric vehicles considering additional noise, vibration and harshness constraints” – Energy 310, 133287 (Cited by 1, 2024) 🚗
  • “Computationally efficient assessment of fuel economy of multi-modes and multi-gears hybrid electric vehicles: A Hyper Rapid Dynamic Programming Approach” – Energy, 133811 (Cited by 0, 2024) 🔧

Sureshkumar Chelladurai | Information Technology | Best Researcher Award

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Dr. Sureshkumar Chelladurai | Information Technology | Best Researcher Award

Dr. Sureshkumar Chelladurai, Vel Tech Rangarajan Dr Sangunthala R and D Institute of Science and Technology, India

Dr. Sureshkumar Chelladurai is a seasoned academic with over 12 years of experience in IT education. He currently serves as an Assistant Professor at Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology. Previously, he taught at Anna University, BIT campus, and Maha Barathi Engineering College. Dr. Chelladurai holds a Ph.D. in ICE from Anna University, an M.E. in CSE from Annamalai University, and a B.Tech in IT from SVCET, Tenkasi. His expertise spans programming languages, networks, cloud computing, operating systems, compiler design, and machine learning. 🚀📚

Publication Profile

Orcid

Experience 🧑‍🏫

Dr. Sureshkumar Chelladurai is a seasoned academic with a wealth of experience in teaching and research. He began his career as an Assistant Professor of IT at Maha Barathi Engineering College in Kallakurichi, Tamil Nadu, serving from June 2011 to July 2014, totaling 37 months. He then moved to Anna University, BIT Campus, Tiruchirappalli, Tamil Nadu, where he worked as a Teaching Fellow in IT from January 2015 to December 2023, accumulating 107 months of experience. Currently, Dr. Chelladurai holds the position of Assistant Professor of IT at Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, starting in December 2024. With over 12.3 years of experience, Dr. Chelladurai has established himself as a dedicated and knowledgeable educator.

Education 🎓

Dr. Chelladurai’s academic journey is marked by significant achievements. He completed his Ph.D. in Instrumentation and Control Engineering from Anna University, Chennai, in 2023. Prior to this, he earned his M.E. in Computer Science and Engineering from Annamalai University, Chidambaram, in 2011, with a commendable OGPA of 7.9. He also holds a B.Tech in Information Technology from SVCET, Puliyangudi, Tenkasi, Tamil Nadu, graduating in 2008 with a percentage of 69. His early education includes a Higher Secondary Certificate (HSC) from H.N.U.C. Hr. Sec. School, Puliyangudi, with a percentage of 76 in 2003, and a Secondary School Leaving Certificate (SSLC) from the same institution, where he scored 86% in 2000.

Research Focus

Dr. Sureshkumar Chelladurai’s research primarily revolves around enhancing the efficiency and security of wireless sensor networks (WSNs). His work spans various crucial aspects, including reducing traffic overhead, developing adaptive frameworks for spatial data, and implementing secure trust-based group key generation algorithms. Additionally, he focuses on improving energy efficiency and intrusion detection within WSNs using advanced techniques like fuzzy-based authentication and clustering. Dr. Chelladurai’s contributions significantly impact areas such as networks, cloud computing, machine learning, and cybersecurity, aiming to create more robust and efficient network systems. 🌐🔐📡

 

Publication Top Notes

  • Adaptive Graphical Routing Methodology for Reducing Traffic Overhead in Wireless Sensor Networks 🛤️📡
    • Publication: Signal, Image and Video Processing
    • Year: 2023
    • DOI: 10.1007/s11760-023-02834-2
    • Contributors: C. Sureshkumar, S. Sabena, L. Sai Ramesh
    • Cited by: –
  • Design of an Adaptive Framework with Compressive Sensing for Spatial Data in Wireless Sensor Networks 🖼️🌐
    • Publication: Inventive Computation and Information Technologies
    • Year: 2021Secure Trust-Based Group Key Generation Algorithm for Heterogeneous Mobile Wireless Sensor Networks 🔑📱
    • Contributors: S. Sabena, C. Sureshkumar, L. Sai Ramesh, A. Ayyasamy
  • Fuzzy-Based Secure Authentication and Clustering Algorithm for Improving the Energy Efficiency in Wireless Sensor Networks 🔐🌿
    • Publication: Wireless Personal Communications
    • Year: 2020
    • DOI: 10.1007/s11277-020-07113-8
    • Contributors: C. Sureshkumar, S. Sabena
  • Time of Development and Fitness Analysis of Modified COCOMOII Model for Software Projects 🕒💻
    • Publication: International Journal of Recent Technology and Engineering
    • Year: 2019
    • Contributors: Sivakumar, D., Sureshkumar, C.
  • Diagnosis Prognosis and Prevention of Breast Cancer Based on Present Scenario of Human Life 🎗️👩‍⚕️
    • Publication: Proceedings – 2018 International Conference on Communication, Information and Computing Technology, ICCICT 2018
    • Year: 2018
    • Contributors: Isaac, L.D., Sureshkumar, C.
  • An Efficient Intrusion Detection System for Cyber Attack using Multi-Tier Application 🔍💼
    • Publication: INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT)
    • Year: 2018
    • Contributors: Dr. Sureshkumar C
  • Effort Estimation of Software Projects with Optimized Coefficients using Soft Computing Technique 🧮📊
    • Publication: 2017 Conference on Emerging Devices and Smart Systems, ICEDSS 2017
    • Year: 2017
    • Contributors: Sivakumar, D., Sureshkumar, C.
  • An Optimized Image Denoising in Impulse Noise Images using Firefly-Based Parallel Type 2 Fuzzy Filtering Approaches 📸✨
    • Publication: Journal of Computational and Theoretical Nanoscience
    • Year: 2016
    • Contributors: Revathi, D., Sureshkumar, C.
  • Solution to Uncertainty Using Random Forests for Predicting Mobile User Behavior 📱🔮
    • Publication: Journal of Computational and Theoretical Nanoscience
    • Year: 2016
    • Contributors: K Kandasamy, C Sureshkumar

Eyob Abera Deboch | Communication Engineering | Best Researcher Award

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Mr. Eyob Abera Deboch | Communication Engineering | Best Researcher Award

Mr. Eyob Abera Deboch, Shenzhen institute of advance technology, Ethiopia

🌟 Eyob Abera Deboch is an Ethiopian computer vision specialist with a master’s degree from the University of Electronic Science and Technology of China. With over three years of experience, he excels in deep learning, particularly in image fusion, classification, and detection. Eyob has showcased his expertise through impactful research, winning awards such as first prize in the Scientific Innovation Competition Contest. He’s published in esteemed journals and demonstrated leadership in academia and extracurricular activities. Eyob is fluent in Python, MATLAB, and C/C++, with a passion for leveraging AI for real-world applications. 🖥️🔍

 

Publication Profile

Scopus

Education

🎓 Eyob Abera Deboch pursued his academic journey at the University of Electronic Science and Technology of China, where he attained both his Bachelor’s and Master’s degrees. Graduating with honors, Eyob’s Master’s thesis delved into “Research on Image fusion with the deep learning framework,” showcasing his expertise in computer vision. Prior to this, his Bachelor’s thesis focused on “Image Fusion Algorithms based on Machine learning,” laying the foundation for his subsequent research endeavors. With a strong academic background in Electronic Information Engineering and Information and Communication Engineering, Eyob has demonstrated a commitment to advancing the field of AI through innovative research and academic excellence. 📚✨

 

Experience

🌟 Eyob Abera Deboch has a diverse range of experiences, showcasing his expertise in computer vision and deep learning. During his master’s program, he designed and implemented a cutting-edge deep learning model for infrared and visible image fusion, under the guidance of Associate Prof. Qi Jin. As a dedicated school assistant, Eyob provided invaluable support to students and faculty at the School of Information and Communication Engineering. His bachelor’s thesis, advised by Associate Prof. Wu Ruiqing, focused on developing an Ensemble Network for Infrared and Visible image fusion. Additionally, Eyob excelled in freelance projects, including ball height detection and dataset preparation, and earned recognition for his Raspberry Pi face detection project, winning the first prize in a scientific innovation competition. 🖥️🏆

 

Awards

🏅 Eyob Abera Deboch has garnered numerous accolades and scholarships, underscoring his exceptional academic and extracurricular achievements. Notably, he secured the prestigious Chinese Government Scholarship, enabling him to pursue his master’s degree. Throughout his academic journey, Eyob earned the Academic Achievement Award multiple times, demonstrating consistent excellence. He clinched the top spot in the Scientific Innovation Competition Contest and received recognition for his contributions to various workshops and competitions. Eyob’s linguistic prowess extends to English and Amharic, with proficient communication in Chinese. His dedication to both scholarly pursuits and sports exemplifies a well-rounded individual committed to success. 🎓🌟

 

Research Focus

🔍 Eyob Abera Deboch’s research focuses primarily on computer vision and deep learning applications, with a specialization in image fusion and enhancement. Through projects like “A deep learning and image enhancement based pipeline for infrared and visible image fusion,” Eyob demonstrates a keen interest in leveraging advanced algorithms to improve image quality and analysis. His work extends to areas such as automatic image contrast enhancement, utilizing reinforcement learning techniques. Eyob’s dedication to enhancing image processing techniques showcases his commitment to advancing technology’s capabilities in visual data analysis. With a strong foundation in these domains, he continues to contribute innovative solutions to the field, driving progress in computer vision. 🖥️🌟

 

Publication Top Notes

Multi-scale feature fusion for prediction of IDH1 mutations in glioma histopathological images

Jiasheng Ni | Intelligent perception technology | Best Researcher Award

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Prof. Jiasheng Ni | Intelligent perception technology | Best Researcher Award

Prof. Jiasheng Ni, the Faculty of Optoelectronics, Qilu University of Technology, China

Prof. Jiasheng Ni, a renowned expert in optoelectronics, holds a Ph.D. and serves as Executive Deputy Director at Qilu University of Technology. With a prolific career spanning prestigious roles globally, including Senior Visiting Scholar in Australia, Ni’s research focuses on intelligent detection, laser, and fiber optic sensing technologies. With over a dozen projects led and numerous publications, Ni’s contributions in optics earned him awards like Shandong Provincial Science and Technology Progress Award. His expertise encompasses areas like intelligent optoelectronic detection, high-performance lasers, and secure IoT. Ni’s journey reflects dedication and excellence in advancing optical sciences. 🌟🔬👨‍💼

 

Publication Profile

scopus

Education

Ni’s academic journey includes enriching experiences at prestigious institutions worldwide, including the University of New South Wales and Tianjin University, culminating in a Ph.D. in Optical Engineering. His academic pursuits are complemented by hands-on industry experience, reflecting a holistic approach to knowledge dissemination and application. Ni’s educational background underscores his dedication to bridging the gap between academia and industry, shaping the next generation of optoelectronic innovators. 🌐🔍

 

Research Focus

Prof. Jiasheng Ni’s research focus encompasses a wide array of cutting-edge topics in the field of optoelectronics. He specializes in intelligent optoelectronic detection technology, high-performance lasers, and fiber-optic sensing innovations, including secure IoT applications. Ni’s expertise extends to areas such as fiber-optic well logging, seismic detectors, marine sensing, and perimeter security technology. With a keen interest in advancing optical sciences, his contributions have led to significant breakthroughs in distributed fiber optic acoustic sensing systems and high-resolution temperature sensors. Ni’s dedication to pioneering research is reflected in his extensive publication record and leadership roles in professional societies. 🌐🔬🚀

 

Publication Top Notes

  1. “Distributed fiber optic acoustic sensing system intrusion full event recognition based on 1-D MFEWnet” by Dong, L., Zhao, W., Huang, S., Jia, Z., Ni, J. (2024) 🌐
    • Cited by: 0
  2. “High Spatial-Resolved φ-OTDR System Based on Differential Pulse Width Sequence Technique” by Wang, M., Qu, J., Qu, S., Shang, Y., Ni, J. (2024) 🌐
    • Cited by: 0
  3. “Study on the mechanism of fiber-optic hot-wire sensing based on DFB-FL thermally induced chirp effect” by Zhuang, Y., Zhang, X., Hong, Y., Ni, J., Song, Z. (2024) 🌐
    • Cited by: 0
  4. “Research progress of crystalline Raman yellow lasers” by Jiang, P., Ding, X., Guo, J., Ni, J., Yao, J. (2024) 🌐
    • Cited by: 1
  5. “An intelligent crash recognition method based on 1DResNet-SVM with distributed vibration sensors” by Yi, J., Shang, Y., Wang, C., Zhao, Y., Ni, J. (2023) 🌐
    • Cited by: 3
  6. “Intrusive and non-intrusive microflow measurement based on distributed optical fiber acoustic sensing” by Du, Y., Shang, Y., Wang, C., Zhao, Y., Ni, J. (2023) 🌐
    • Cited by: 1

Zhe Zhang | Computer Science | Best Researcher Award

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Assist Prof Dr. Zhe Zhang: Computer Science

🌐 Dr. Zhe Zhang, an Assistant Professor in the Department of Geography at Texas A&M University, is a distinguished scholar with a robust academic background. In 2016, he earned his Doctor of Science with distinction in Geoinformatics from Aalto University, Finland, minoring in applied mathematics. His journey includes a Master’s in Geomatics and a Bachelor’s in Environmental Engineering from top Finnish institutions. Since 2019, Dr. Zhang has been a dedicated Assistant Professor, contributing significantly to the College of Arts and Sciences. His interdisciplinary expertise extends to serving as Affiliate Faculty in Electrical and Computer Engineering and as a Faculty Fellow in the Texas A&M Hazard Reduction & Recovery Center. 🌍🔬

Profile:

Scopus

Orcid

Education:

🌍 Dr. Zhe Zhang, a distinguished academic, holds a Doctor of Science (with distinction) in Geoinformatics, with a minor in applied mathematics, awarded in 2016 by the Department of Built Environment at Aalto University, Espoo, Finland. 🏰 His academic journey began in 2009 with a Master of Science (Technology) in Geomatics from the Department of Surveying at Helsinki University of Technology. 🗺️ Prior to his advanced degrees, Dr. Zhang earned a Bachelor of Environmental Engineering in 2005 from Tampere University of Applied Sciences, Tampere, Finland, laying the foundation for his environmental expertise. 🎓 His diverse educational background reflects a commitment to interdisciplinary knowledge in geography, technology, and environmental engineering.

Experience:

🎓 Dr. Zhe Zhang is a versatile academic leader currently serving as an Assistant Professor (Tenure Track) in the Geography Department of the College of Arts and Sciences at Texas A&M University since September 2019. 🌐 His impactful roles extend to being an Affiliate Faculty in Electrical and Computer Engineering, a Faculty Fellow in the Texas A&M Hazard Reduction & Recovery Center, and a Faculty Fellow in the Institute of Data Science, all ongoing since September 2019. 🏛️ Dr. Zhang’s journey includes a Visiting Assistant Professor position in Geography at the College of Geosciences, Texas A&M University, and significant contributions as a Postdoctoral Research Associate at the University of Illinois Urbana-Champaign. 🌐 Outside academia, he chairs the American Association of Geographers’ Cyberinfrastructure Specialty Group and leads the CyberGIS and Decision Support Systems Research Initiative for the University Consortium for Geographic Information Science (UCGIS). As the CyberGIS Studio Coordinator at the National Center for Supercomputing Applications, his work has left a lasting impact. 🚀🌐

Research Interest:

🧠 Dr. Zhe Zhang is at the forefront of pioneering research, specializing in intelligent decision support systems, big data, CyberGIS, and spatiotemporal data modeling. His expertise lies in seamlessly blending the realms of data science and geographic information systems to harness the power of big data. 🌐 His innovative work delves into the intricacies of intelligent decision-making processes, utilizing cutting-edge technologies. Dr. Zhang’s focus on spatiotemporal data modeling demonstrates a commitment to unraveling the complexities of dynamic spatial information. 🗺️ With a flair for fuzzy logic applications, he contributes significantly to advancing knowledge in these critical domains, shaping the future of decision support systems with intelligence and precision. 🚀🔍

Publication Top Note:
  • MetaQA: Enhancing human-centered data search using Generative Pre-trained Transformer (GPT) language model and artificial intelligence
    • 👨‍💼 Li, D.; Zhang, Z.
    • 📅 2023
    • 📚 0 Citations
  • Embracing geospatial analytical technologies in tourism studies
    • 👨‍💼 Yang, Y.; Chen, X.; Gao, S.; … Zhang, Z.; Zhao, B.
    • 📅 2023
    • 📚 1 Citation 🌐
  • Impacts of climate change on future hurricane induced rainfall and flooding in a coastal watershed: A case study on Hurricane Harvey
    • 👨‍💼 Li, X.; Fu, D.; Nielsen-Gammon, J.; … Zhang, Z.; Gao, H.
    • 📅 2023
    • 📚 3 Citations 🌊
  • Analyzing spatial variations of heart disease and type-2 diabetes: A multi-scale geographically weighted regression approach
    • 👨‍💼 Cui, W.; Hu, N.; Zhang, S.; … Güneralp, B.; Zhang, Z.
    • 📅 2022
    • 📚 1 Citation 🗺️
  • COVID-19 impacts on mobility, environment, and health of active transportation users
    • 👨‍💼 Li, X.; Farrukh, M.; Lee, C.; … Zhang, Z.; Dadashova, B.
    • 📅 2022
    • 📚 13 Citations 🚶‍♀️🌍
  • Human-centered flood mapping and intelligent routing through augmenting flood gauge data with crowdsourced street photos
    • 👨‍💼 Alizadeh, B.; Li, D.; Hillin, J.; … Zhang, Z.; Behzadan, A.H.
    • 📅 2022
    • 📚 9 Citations 🗺️🌊
  • Do underserved and socially vulnerable communities observe more crashes? A spatial examination of social vulnerability and crash risks in Texas
    • 👨‍💼 Li, X.; Yu, S.; Huang, X.; … Cui, W.; Zhang, Z.
    • 📅 2022
    • 📚 4 Citations 🚗
  • Exploring the spatial disparity of home-dwelling time patterns in the USA during the COVID-19 pandemic via Bayesian inference
    • 👨‍💼 Huang, X.; Xu, Y.; Liu, R.; … Zhao, B.; Li, Z.
    • 📅 2022
    • 📚 7 Citations 🏡🌐
  • CyberGIS and Geospatial Data Science for Advancing Geomorphology
    • 👨‍💼 Wang, S.; Bishop, M.P.; Zhang, Z.; Young, B.W.; Xu, Z.
    • 📅 2022
    • 📚 0 Citations 🌐🗺️
  • Modeling human activity dynamics: an object-class oriented space–time composite model based on social media and urban infrastructure data
    • 👨‍💼 Zhang, Z.; Yin, D.; Virrantaus, K.; Ye, X.; Wang, S.
    • 📅 2021
    • 📚 8 Citations 🤖🏙️