Ji Changpeng | Engineering | Best Researcher Award

Published on 22/01/202522/01/2025 by Book of Award

Prof. Ji Changpeng | Engineering | Best Researcher Award

Liaoning Technical University | China

Author Profile

Early Academic Pursuits 🎓

Prof. Ji Changpeng began his academic journey with a Master’s degree in Computer Application Technology from Liaoning Technical University, which he completed in 2005. His strong foundation in computer applications laid the groundwork for his illustrious career in academia and research. With a keen interest in technological innovation and problem-solving, Prof. Ji's early academic endeavors marked the beginning of his contributions to the field of computer science.

Professional Endeavors 🏢

Currently a full professor and Master supervisor at Liaoning Technical University, Prof. Ji holds several prestigious roles. He is a recognized Codesys Senior Application Engineer and a Senior Artificial Intelligence Designer. As the Academic Leader of Information and Communication Engineering, he has played a pivotal role in shaping the department's vision. Additionally, his influence extends to academic leadership as a key member of the Outstanding Young Teacher initiative in Liaoning Province (2006). He also serves as an expert in discipline assessment and dissertation evaluations for the Ministry of Education, showcasing his authority in the field.

Contributions and Research Focus 🔬

Prof. Ji’s research contributions are vast and impactful. Having presided over more than 60 research projects, his work has significantly advanced the fields of artificial intelligence, information engineering, and communication systems. He has published over 160 academic papers and authored three academic works, contributing valuable insights and innovation to the global research community. His patents, numbering more than 40, highlight his practical approach to solving complex technological problems. Prof. Ji’s expertise as an editor and reviewer for esteemed journals such as Journal of Computers and IJConvC further solidifies his influence in academia.

Accolades and Recognition 🏆

Prof. Ji has received six prestigious science and technology advancement medals for his groundbreaking contributions. His role as an editorial board member and specialist reviewer for several reputed journals speaks volumes about his standing in the academic world. These accolades reflect his dedication to excellence and his commitment to pushing the boundaries of technology and innovation.

Impact and Influence 🌟

Through his extensive research, patents, and academic leadership, Prof. Ji has profoundly influenced the fields of artificial intelligence and communication engineering. His role in mentoring future researchers and supervising Master’s students ensures that his knowledge and vision continue to inspire the next generation. His work has not only shaped his university but has also had a far-reaching impact on the global research community.

Legacy and Future Contributions 🌍

Prof. Ji Changpeng’s contributions have left an indelible mark on the academic and technological landscape. His ability to blend research with practical application has set a benchmark for innovation. As he continues to explore new frontiers in artificial intelligence and communication engineering, his legacy will undoubtedly pave the way for groundbreaking advancements and a brighter future for technology and education.

Publications

📄 Design of Shared-Aperture Base Station Antenna with a Conformal Radiation Pattern
Journal: Electronics
Year: 2025
Authors: Ji Changpeng, Xin Ning, Wei Dai

📄 A Lightweight Safety Helmet Detection Algorithm Based on Receptive Field Enhancement
Journal: Processes
Year:2024
Authors: Ji Changpeng, Zhibo Hou, Wei Dai

Xizhong Shen | Engineering | Best Researcher Award

Published on 24/12/202424/12/2024 by Book of Award

Prof. Dr. Xizhong Shen | Engineering | Best Researcher Award

Shanghai Institute of Technology | China

Author Profile

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Early Academic Pursuits 🎓

Prof. Dr. Xizhong Shen's academic journey is marked by stellar achievements. He began his undergraduate studies at Shanghai University, earning a B.S. degree in 1990. He advanced his knowledge in medical sciences at Nanchuang University, where he received an M.D. in 1995. His pursuit of excellence culminated in a Ph.D. from the prestigious Shanghai Jiao Tong University in 2005, cementing his foundation in advanced research methodologies.

Professional Endeavors 🏫

Dr. Shen serves as a key academic figure at the Shanghai Institute of Technology, Shanghai, China. His professional career is dedicated to fostering innovation in electronics, computational sciences, and academia. Known for his dedication to teaching and mentoring, he inspires a new generation of researchers to contribute to evolving technological fields.

Contributions and Research Focus 🔍

Dr. Shen's research primarily focuses on cutting-edge topics, including deep learning, signal processing, and electronic CAD. With over 100 published research papers, he has significantly contributed to advancing these fields. His expertise is further reflected in his authorship of the authoritative book Digital Signal Processing, a seminal work that bridges theoretical insights with practical applications.

Accolades and Recognition 🏆

Dr. Shen's contributions have garnered widespread recognition in academic and industrial communities. His prolific research output and the quality of his work make him a respected thought leader in his fields of expertise.

Impact and Influence 🌟

Through his groundbreaking research and extensive publications, Dr. Shen has influenced both theoretical and applied sciences. His work in deep learning and signal processing is widely referenced, forming a basis for advancements in these areas. As an educator, his mentorship has shaped numerous successful careers in technology and academia.

Legacy and Future Contributions 🌍

As an innovator and thought leader, Dr. Shen’s legacy lies in his dedication to pushing technological boundaries. His future endeavors are expected to address emerging challenges in signal processing and artificial intelligence, ensuring his ongoing influence in these dynamic fields.

Publications

📄 Investigation of Bird Sound Transformer Modeling and Recognition

Author(s): Yi, D., Shen, X.
Journal: Electronics (Switzerland)
Year: 2024

📄 Feature-Enhanced Multi-Task Learning for Speech Emotion Recognition Using Decision Trees and LSTM

Author(s): Wang, C., Shen, X.
Journal: Electronics (Switzerland)
Year: 2024

📄 An Algorithm for Distracted Driving Recognition Based on Pose Features and an Improved KNN

Author(s): Gong, Y., Shen, X.
Journal: Electronics (Switzerland)
Year: 2024

📄 Air Leakage Detection and Rehabilitation Test Methods for Digital Thoracic Drainage Systems

Author(s): Wu, X., Shen, X.
Conference Paper: 2024 IEEE 2nd International Conference on Sensors, Electronics and Computer Engineering, ICSECE 2024
Year: 2024

📄 Temperature Control System of Hot and Cold Alternating Treatment System Based on Kalman Filter Combined with Fuzzy Logic

Author(s): Xiong, Z., Shen, X.
Journal: Applied Mathematics and Nonlinear Sciences
Year: 2024

Junwei Du | Computer Science | Best Researcher Award

Published on 17/12/202417/12/2024 by Book of Award

Prof. Junwei Du | Computer Science | Best Researcher Award

Qingdao University of Science and Technology | China

Author Profile

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Early Academic Pursuits 🎓

Prof. Junwei Du embarked on his academic journey with a strong foundation in computer science. He earned his Ph.D. in Computer Software and Theory from Tongji University in 2010. His thirst for international exposure led him to become a Visiting Scholar at Arizona State University, USA, in 2014. Further enriching his skills, Prof. Du attended the AI Training Workshop for Young Backbone hosted by the University of Queensland and the University of Technology, Sydney, Australia, in September 2018.

Professional Endeavors 💼

Prof. Junwei Du is currently Executive Vice Dean of the School of Data Science at Qingdao University of Science and Technology. His professional affiliations include being a Distinguished Member of CCF and holding memberships in prestigious committees like the China Computer Society's Software Engineering Specialised Committee and the China Automation Society's Network Information Service Committee. Additionally, he serves as a Director of the Shandong Artificial Intelligence Society, underscoring his leadership in the field.

Contributions and Research Focus 🔬

Prof. Du's research focuses on cutting-edge areas like intelligent software engineering, graph representation learning, and recommendation algorithms. He has led numerous high-impact projects, including a National Natural Science Foundation of China top-level project, two provincial funds, and a key R&D project in Shandong Province. His work has also extended to over 10 national vertical projects and nine enterprise-driven horizontal projects. Prof. Du has published more than 60 academic papers in renowned journals such as Information Sciences, Software Journal, and Expert Systems with Applications. His research has significantly contributed to software fault prediction, cross-domain recommendation systems, and privacy-preserving algorithms in IoT.

Accolades and Recognition 🏆

Prof. Junwei Du’s achievements have earned him notable accolades. As a key participant, he received the Third Prize of Shandong Provincial Scientific and Technological Progress and the Third Prize of Shandong Provincial Teaching Achievement. He has also guided his students to excel in prestigious competitions, leading them to win over 20 national awards in software design and testing.

Impact and Influence 🌍

Through his extensive contributions, Prof. Junwei Du has shaped the landscape of intelligent software systems and data science education. His leadership in research and teaching has inspired countless students to pursue innovation. Prof. Du’s work on ensemble learning, recommendation algorithms, and software fault prediction holds significant implications for industries ranging from IT to industrial IoT, enhancing technological efficiency and reliability.

Legacy and Future Contributions 🔮

Prof. Junwei Du continues to build a legacy of excellence, bridging academia and industry with transformative research and mentorship. His focus on emerging areas like graph representation learning and cross-domain recommendation systems will pave the way for smarter AI applications. By fostering collaboration and innovation, he is set to make lasting contributions to data science and software engineering, empowering the next generation of researchers and professionals.

Publications

📄 Improving Bug Triage with the Bug Personalized Tossing Relationship
Authors: Wei Wei, Haojie Li, Xinshuang Ren, Feng Jiang, Xu Yu, Xingyu Gao, Junwei Du
Journal: Information and Software Technology
Year: 2025

📄 A Privacy-Preserving Cross-Domain Recommendation Algorithm for Industrial IoT Devices
Authors: Yu X., Peng Q., Lv H., Du J., Gong D.
Journal: IEEE Transactions on Consumer Electronics
Year: 2024

📄 Research on Efficient Data Warehouse Construction Methods for Big Data Applications
Authors: Zhao C., Du J., Wang F., Li H.
Journal: Applied Mathematics and Nonlinear Sciences
Year: 2024

📄 A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features
Authors: Yu X., Lu Y., Jiang F., Du J., Gong D.
Journal: IEEE Transactions on Network and Service Management
Year: 2024

📄 A Multi-Behavior Recommendation Based on Disentangled Graph Convolutional Networks and Contrastive Learning
Authors: Yu J., Jiang F., Du J.W., Yu X.
Journal/Proceedings: Communications in Computer and Information Science
Year: 2024

Xinhai Wang | Computer Science | Best Researcher Award

Published on 05/10/202405/10/2024 by Book of Award

Mr. Xinhai Wang | Computer Science | Best Researcher Award

Northeastern University | China

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Early Academic Pursuits 🎓

Mr. Xinhai Wang's academic journey began with an undergraduate degree in Mathematics and Applied Mathematics from Northeastern University, where he achieved a GPA of 3.81/5. His academic excellence earned him several accolades, such as the "Outstanding Student Cadre" and "Three Good Students" awards, reflecting his dedication to both academics and extracurricular activities. Wang was actively involved in numerous projects during his undergraduate years, honing his skills in advanced algebra, data mining, and mathematical modeling, laying the groundwork for his future endeavors.

Professional Endeavors 🏆

In September 2022, Xinhai Wang assumed the role of monitor for Northeastern University's Master of Science Class 2201, demonstrating exemplary leadership and organizational skills. His work extended beyond the classroom, where he helped in the construction of class activities and assisted in Party branch operations. Wang was awarded the honorary title of Outstanding Graduate Student Cadre for his relentless efforts in promoting student engagement and fostering a collaborative environment. As a deputy director in the Project Development Department of the Social Practice Department, he organized impactful student initiatives such as charity sales, making significant contributions to the student community.

Contributions and Research Focus 🔬

Mr. Wang's contributions to academia and research are vast, with his work primarily centered on applying advanced algorithms in real-world scenarios. He has engaged in several high-level projects, including the application of genetic algorithms in mobile chess and using deep learning techniques like Deep Q Networks for stock market predictions. His research has tackled challenges in time series prediction, exploring fractional order random configuration networks (FSCN) to address the inherent non-stationarity in real-world data. These projects showcase his technical expertise in MATLAB and Python, alongside his growing knowledge of reinforcement learning and machine learning.

Accolades and Recognition 🏅

Xinhai Wang's academic brilliance has been recognized throughout his career, both during his undergraduate and graduate studies. His GPA of 3.40/4 ranked him 2nd in his class, further earning him prestigious honors such as the President Scholarship and First-Class Academic Scholarship. His leadership in class and organizational roles has led to multiple "Outstanding Class Cadre" awards. Wang's academic achievements extend beyond his GPA and awards, with his research work being submitted to conferences and awaiting SCI journal reviews, positioning him as a rising star in applied statistics and data science.

Impact and Influence 🌟

Through his roles in student governance and research, Wang has had a lasting impact on both his peers and the academic community. He has innovated branch activities, guided students in social practice initiatives, and created platforms for broader engagement in scientific and social matters. His research endeavors, such as the application of deep learning to stock prediction and time series analysis, contribute to the growing body of knowledge in the field of statistical modeling and artificial intelligence, influencing future technological advancements.

Legacy and Future Contributions 💡

Mr. Xinhai Wang's journey reflects a commitment to excellence in academic leadership, research, and innovation. As he continues to explore the boundaries of machine learning, algorithm design, and data modeling, his future contributions will likely have a profound effect on emerging fields like stock prediction and industrial data analysis. His ongoing projects in MATLAB and Python, combined with his growing expertise in reinforcement learning, position him for future success in both academic and professional arenas.

Publications

📄 Prediction of Ship-Unloading Time Using Neural Networks
Author: Zhen Gao, Danning Li, Danni Wang, Zengcai Yu, Witold Pedrycz, Xinhai Wang
Journal: Applied Sciences
Year: 2024-09

📄 Novel Admissibility Criteria and Multiple Simulations for Descriptor Fractional Order Systems with Minimal LMI Variables
Author: Xinhai Wang, Jin-Xi Zhang
Journal: Fractal and Fractional
Year: 2024-06

Heng Luo | Computer Science | Best Researcher Award

Published on 09/08/202409/08/2024 by Book of Award

Mr. Heng Luo | Computer Science | Best Researcher Award

The Hong Kong Polytechnic University | Hong Kong

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Early Academic Pursuits 🎓

Mr. Heng Luo's academic journey is a testament to his commitment to excellence in engineering and technology. He began his higher education at the University of Electronic Science and Technology of China, earning a Bachelor's Degree in Electronic Engineering in 2012. This foundational education was followed by a Master’s Degree in the same field from the same institution in 2013. Heng Luo further expanded his academic horizons by pursuing two more Master’s degrees, one in Industrial and Systems Engineering from The Hong Kong Polytechnic University, and another in the Warwick Manufacturing Group at The University of Warwick, both completed in 2016. Currently, he is a PhD candidate at The Hong Kong Polytechnic University, where he continues to advance his research in The Institute of Textiles and Clothing.

Professional Endeavors 💼

In addition to his academic pursuits, Mr. Heng Luo has been actively involved in professional organizations. Since 2021, he has been a member of the Institution of Engineering and Technology and IEEE. His affiliation with IEEE also includes participation in the Young Professionals group, reflecting his dedication to staying at the forefront of technological advancements and contributing to the global engineering community.

Contributions and Research Focus 📚

Mr. Heng Luo's research and professional work have led to significant contributions in various fields. His expertise spans wearable systems, polymer degradation, hydrogel technology, and control systems. Notable among his works are publications like the "Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities" and "Evaluating and Modeling the Degradation of PLA/PHB Fabrics in Marine Water." His research also includes innovative patents, such as those related to MIMO-OTH radar waveforms and machine learning-based article identification methods.

Accolades and Recognition 🏆

Throughout his career, Mr. Heng Luo has garnered recognition for his work, particularly in the realms of materials science and engineering. His contributions have been published in high-impact journals, and his patents demonstrate a strong application-oriented approach to research. He has also served as a peer reviewer for journals like Fibers and Polymers, showcasing his expertise and respected standing in the academic community.

Impact and Influence 🌍

Mr. Heng Luo's work has had a broad impact, particularly in the development of advanced materials and systems for practical applications. His research on wearable systems and polymer degradation has implications for both the healthcare industry and environmental sustainability. By integrating his engineering expertise with cutting-edge research, he has influenced the direction of technological development in these areas.

Legacy and Future Contributions 🌟

As Mr. Heng Luo continues his PhD research and professional activities, his future contributions are anticipated to further advance the fields of engineering and technology. His ongoing work promises to leave a lasting legacy, particularly in the areas of wearable technology and sustainable materials. As an emerging leader in his field, Mr. Heng Luo's future endeavors will likely continue to shape the landscape of modern engineering and contribute to global technological progress.

Publications 📚

📖 Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities

Authors: Heng Luo, Ying Xiong, Mingyue Zhu, Xijun Wei, Xiaoming Tao
Journal: Sensors
Year: 2024

📖 Evaluating and Modeling the Degradation of PLA/PHB Fabrics in Marine Water

Authors: Qi Bao, Ziheng Zhang, Heng Luo, Xiaoming Tao
Journal: Polymers
Year: 2022

📖 Ionic Hydrogel for Efficient and Scalable Moisture‐Electric Generation

Authors: Heng Luo
Journal: Advanced Materials
Year: 2022

📖 Article Identification Method and Device Based on Machine Learning

Authors: Heng Luo
Journal: Patent
Year: 2020

📖 Observer-Based Control of Discrete-Time Fuzzy Positive Systems with Time Delays

Authors: Heng Luo
Journal: IFAC Proceedings Volumes
Year: 2013

Kalyanapu Srinivas | Computer Science | Best Researcher Award

Published on 07/08/202407/08/2024 by Book of Award

Dr. Kalyanapu Srinivas | Computer Science | Best Researcher Award

Vaagdevi Engineering College | India

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Early Academic Pursuits 🎓

Dr. Kalyanapu Srinivas embarked on his academic journey with a Bachelor of Technology (B.Tech) in Computer Science Engineering from Vidya Bharathi Institute of Technology, graduating in 2006 with First Division honors. He continued to advance his studies with a Master of Technology (M.Tech) in Software Engineering from Ramappa Engineering College in 2010, where he achieved Distinction with a 78.2% score. Further solidifying his academic prowess, Dr. Srinivas completed his Ph.D. in Cryptography & Network Security at JNTU, Hyderabad in 2020.

Professional Endeavors 💼

Dr. Srinivas has accumulated over 16 years of experience in academia. His professional journey includes roles such as Assistant Professor at various institutions, including Vaagdevi Engineering College, Kakatiya Institute of Technology and Science, and SR Engineering College. His tenure in these roles highlights his commitment to advancing the field of computer science and engineering. Notably, he has been involved in teaching, research, and academic administration.

Contributions and Research Focus 🔬

Dr. Srinivas’s research primarily focuses on Cryptography and Network Security, with a keen interest in Data Mining, Cloud Computing, and Quantum Computing. His Ph.D. thesis, titled "Novel Techniques for Image-Based Key Generation using Chinese Remainder Theorem and Chaotic Logistic Maps," reflects his innovative approach to enhancing security protocols. Additionally, his ongoing research guidance includes supervising several Ph.D. students in areas such as Wireless Networks and Cloud Computing.

Accolades and Recognition 🏆

Dr. Srinivas has earned significant recognition throughout his career. His work in machine learning and cryptography has led to the publication of a patent on Alzheimer's prediction using machine learning. He has also been honored as a session chair at the International Conference on Research in Science, Engineering, Technology, and Management (ICRSETM2020) and served as a guest speaker at SAFER INTERNET DAY 2023. His expertise has been acknowledged through editorial and review roles for various conferences and journals.

Impact and Influence 🌍

Dr. Srinivas’s contributions extend beyond his research. His involvement in organizing and participating in short-term training programs (STTP) on IoT simulation and fog computing showcases his dedication to fostering knowledge and innovation in emerging technologies. His role as a primary evaluator for TOYCATHON 2021 further emphasizes his influence in shaping the future of technology education and development.

Legacy and Future Contributions 🚀

Looking ahead, Dr. Srinivas is poised to continue making impactful contributions to the fields of cryptography and network security. His research initiatives and academic leadership are expected to drive advancements in secure computing and innovative technologies. As he mentors the next generation of researchers and contributes to cutting-edge research, his legacy in the academic and professional realms will undoubtedly endure, inspiring future advancements in technology and education.

Publications 📚

Article: Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
Authors: Stateczny, A., Narahari, S.C., Vurubindi, P., Guptha, N.S., Srinivas, K.
Journal: Remote Sensing
Year: 2023

Article: User-segregation based channel estimation in the MIMO system
Authors: Patra, R.K., Kumar, M.H., Srinivas, K., Sekhar, P.C., Subhashini, S.J.
Journal: Physical Communication
Year: 2023

Book Chapter: An Enhancement in Crypto Key Generation Using Image Features with CRT
Authors: Srinivas, K., Kumar, N.S., Sanathkumar, T., Rama Devi, K.
Book: Cognitive Science and Technology
Year: 2023

Article: Plant disease classification using deep bilinear CNN
Authors: Rao, D.S., Ramesh Babu, C., Kiran, V.S., Mohan, G.S., Bharadwaj, B.L.
Journal: Intelligent Automation and Soft Computing
Year: 2022

Article: Symmetric key generation algorithm using image-based chaos logistic maps
Authors: Srinivas, K., Janaki, V.
Journal: International Journal of Advanced Intelligence Paradigms 🧠
Year: 2021

Soopil Kim | Computer Science | Best Researcher Award

Published on 02/08/202402/08/2024 by Book of Award

Dr. Soopil Kim | Computer Science | Best Researcher Award

Daegu Gyeongbuk Institute of Science and Technology | South Korea

Author Profile

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Early Academic Pursuits 🎓

Dr. Soopil Kim's academic journey began with a Bachelor of Engineering in Robotics and Mechatronics Engineering from Daegu Gyeongbuk Institute of Science & Technology (DGIST), where he graduated Cum Laude. He continued his studies at DGIST, pursuing a Master’s and Ph.D. in the same field, focusing on medical image segmentation. His research during these years emphasized label-efficient segmentation models and limited pixel-level annotation, laying a strong foundation for his future work in deep learning and computer vision.

Professional Endeavors 💼

Dr. Kim's career has seen significant milestones, including a role as a Visiting Student at Stanford University's CNSLAB under the supervision of Prof. Kilian M. Pohl and Ehsan Adeli. Currently, he is a Post-Doctoral Research Fellow at the Medical Image & Signal Processing Lab (MISPL) at DGIST, where he works under Prof. Sang Hyun Park. His professional trajectory reflects a commitment to advancing the field of computer vision through innovative research and collaboration.

Contributions and Research Focus 🔬

Dr. Kim’s research is at the forefront of deep learning and computer vision. His work addresses the challenges of image segmentation with partially labeled datasets by developing federated learning strategies and few-shot segmentation techniques. His notable contributions include the creation of a medical image segmentation model that integrates meta-learning and bi-directional recurrent neural networks, a semi-supervised segmentation model based on uncertainty estimation, and a transductive segmentation model for industrial imaging. These advancements aim to improve the efficiency and accuracy of image segmentation processes.

Accolades and Recognition 🏆

Dr. Kim has received several awards that highlight his exceptional contributions to the field. Notably, he was ranked 3rd among 40 teams in the SNUH Sleep AI Challenge in 2021 and was honored with the Outstanding Student Award from the Department of Robotics and Mechatronics Engineering at DGIST in 2022. In 2024, he was recognized at the KCCV Oral/Poster Presentation Doctoral Colloquium for his work on label-efficient segmentation models.

Impact and Influence 🌍

Dr. Kim's research has made a significant impact on the field of computer vision, particularly in the area of image segmentation. His innovative approaches to handling partially labeled datasets and federated learning have the potential to advance both academic research and practical applications in medical imaging and beyond. His work on few-shot learning and uncertainty-aware models addresses critical challenges in the field, contributing to more robust and adaptable segmentation solutions.

Legacy and Future Contributions 🚀

As Dr. Kim continues his research, his focus on improving segmentation models and developing new methodologies promises to shape the future of computer vision. His commitment to exploring federated learning and few-shot learning techniques will likely drive further innovations in the field, offering solutions to complex challenges and enhancing the accuracy of image analysis across various applications.

Publications 📘

📄Few-shot anomaly detection using positive unlabeled learning with cycle consistency and co-occurrence features
Authors: Sion An, Soopil Kim, Philip Chikontwe, Jiwook Jung, Hyejeong Jeon, Jaehong Kim, Sang Hyun Park
Journal: Expert Systems with Applications
Year: 2024

📄Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets
Authors: Soopil Kim, Haejun Park, Myeongju Kang, Kilian M. Pohl, Sang Hyun Park
Journal: Medical Image Analysis
Year: 2024

📄FedNN: Federated learning on concept drift data using weight and adaptive group normalizations
Authors: Myeongju Kang, Soopil Kim, Kwang-Hyun Jin, Kilian M. Pohl, Sang Hyun Park
Journal: Pattern Recognition
Year: 2024

📄Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection
Authors: Soopil Kim, Sion An, Philip Chikontwe, Kilian M. Pohl, Sang Hyun Park
Conference: Proceedings of the AAAI Conference on Artificial Intelligence
Year: 2024

📄Uncertainty-aware semi-supervised few shot segmentation
Authors: Soopil Kim, Philip Chikontwe, Sion An, Sang Hyun Park
Journal: Pattern Recognition
Year: 2023

Rudresh Dwivedi | Computer Science | Best Researcher Award

Published on 29/06/202429/06/2024 by Book of Award

Assist Prof Dr. Rudresh Dwivedi | Computer Science | Best Researcher Award

Netaji Subhas University of Technology | India

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Early Academic Pursuits

Dr. Rudresh Dwivedi's academic journey began with a Bachelor of Technology in Computer Science & Engineering from ICFAI University, Dehradun, India. He graduated in 2010 with a CGPA of 6.63/10. He then pursued a Master of Technology in Electrical Engineering from the National Institute of Technology (NIT), Raipur, India, graduating in 2013 with a CGPA of 8.63/10. His thesis, supervised by Dr. Narendra D. Londhe, focused on the classification of EEG-based multiclass motor imagery movements. Dr. Dwivedi furthered his academic career with a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology (IIT), Indore, India, completing his doctoral studies in 2019 under the supervision of Dr. Somnath Dey. His Ph.D. thesis titled "Unimodal and Multimodal Biometric Verification Using Cancelable Iris and Fingerprint Templates" earned him a CGPA of 9.25/10.

Professional Endeavors

Dr. Dwivedi's professional career is marked by a blend of academic and industry experiences. His career commenced as a Software Engineer at Mars Web Solution, Bangalore, India, from August 2010 to March 2011. Transitioning to academia, he served as an Assistant Professor at NMIMS University, Maharashtra, India, in 2013. Following this, he was a Research Assistant at IIT Indore for a SERB-DST project focused on efficient cancelable template generation methods for fingerprint and iris biometrics. He then joined Pandit Deendayal Petroleum University (PDPU), Gandhinagar, Gujarat, India, as an Assistant Professor from July 2019 to August 2021. Currently, Dr. Dwivedi is an Assistant Professor in the Computer Science & Engineering Department at Netaji Subhas University of Technology, Dwarka, Delhi, India.

Contributions and Research Focus

Dr. Dwivedi has made significant contributions to the fields of biometrics, machine learning, and computer vision. His research has primarily focused on developing novel approaches for cancelable iris and fingerprint template generation, rotation-invariant iris code generation, and privacy-preserving biometric systems. He has also explored score-level and hybrid fusion schemes for protected multimodal biometric verification and secure communication systems using fingerprint-based cryptographic techniques. Additionally, his work on BCI (Brain-Computer Interface) systems has advanced the classification of EEG signals and the development of motor imagery-based systems.

Accolades and Recognition

Throughout his career, Dr. Dwivedi has received numerous awards and recognitions. These include the Third Prize at the Fifth IDRBT Doctoral Colloquium in 2015, the MHRD TA Fellowship for his Ph.D. studies, a Summer Research Fellowship at IIT Delhi in 2012, and a high percentile in the GATE 2011 exam, which secured him an MHRD TA Fellowship for his M.Tech. studies. He has also been awarded the State Meritorious Student Award and the National Talent Search Examination Scholarship during his early academic years.

Impact and Influence

Dr. Dwivedi's research has had a substantial impact on the field of biometric security, particularly in developing methods for protecting biometric templates. His work on cancelable biometrics and secure communication systems has contributed to enhancing privacy and security in biometric applications. His publications in esteemed journals and conferences have garnered attention and citations, reflecting his influence in the academic community.

Legacy and Future Contributions

Dr. Dwivedi's legacy is marked by his innovative contributions to biometric security and machine learning. His ongoing research continues to push the boundaries of these fields, promising further advancements in secure biometric systems and AI-based solutions. As a dedicated educator and researcher, Dr. Dwivedi's future contributions are anticipated to significantly impact both academia and industry, fostering the development of more secure and efficient biometric technologies.

Notable Publications

Explainable AI (XAI): Core Ideas, Techniques and Solutions 2022 (161)

A Leaf Disease Detection Mechanism Based on L1-Norm Minimization Extreme Learning Machine 2021 (10)

A fingerprint based crypto-biometric system for secure communication 2019 (20)

Jingjing Cao | Computer Science | Best Researcher Award

Published on 16/03/202416/03/2024 by Book of Award

Dr. Jingjing Cao | Computer Science | Best Researcher Award

School of Transportation and Logistics Engineering | China

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Early Academic Pursuits

Dr. Jingjing Cao's academic journey commenced with a Bachelor of Engineering in Information and Computing Science from Dalian Maritime University. Subsequently, she pursued a Master of Science in Applied Mathematics before earning her Ph.D. from the Department of Computer Science at City University of Hong Kong.

Professional Endeavors

Dr. Cao's professional journey has been marked by significant contributions. She served as a Research Associate at Dalian Maritime University and later assumed roles as Assistant Professor and now Tenure Track Associate Professor at Wuhan University of Technology.

Contributions and Research Focus

With a focus on Machine Learning and its applications in transportation and logistics, Dr. Cao has made remarkable contributions. Her research spans various domains, including ensemble learning, deep learning, and optimization algorithms, as evidenced by her prolific publication record in reputable journals and conferences.

Accolades and Recognition

Dr. Cao's impactful research has garnered widespread recognition, exemplified by her receipt of the prestigious Best Researcher Award. Her publications in renowned journals and conferences underscore her standing as a leading figure in the field of Computer Science and Machine Learning.

Impact and Influence

Dr. Cao's work has left a lasting impact on the academic community and industry alike. Her research has not only advanced the theoretical understanding of Machine Learning but has also found practical applications in domains such as transportation, logistics, and industrial informatics.

Legacy and Future Contributions

As Dr. Cao continues her academic journey, her legacy is defined by a commitment to excellence in research and education. With ongoing projects and professional services, she remains dedicated to shaping the future of Computer Science and Machine Learning, leaving an indelible mark on the field.

Notable Publication

A two-stage model for forecasting consumers’ intention to purchase with e-coupons 2021 (15)

RtDS: real-time distributed strategy for multi-period task offloading in vehicular edge computing environment 2021 (14)

Zhiwei Yang | Computer Science | Best Researcher Award

Published on 23/01/202423/01/2024 by Book of Award

Dr. Zhiwei Yang | Computer Science | Best Researcher Award

Jinan University | China

Author Profile

Scopus

Early Academic Pursuits

Zhiwei Yang embarked on his academic journey with a focus on Computer Science, earning a Master's degree in Computer Science from Fuzhou University. Subsequently, he delved into advanced studies, pursuing a Ph.D. in Computer Software and Theory at Jilin University. During his doctoral journey, he also broadened his academic horizons as a full-time exchange Ph.D. student at Hong Kong Baptist University, under the mentorship of Prof. Jing Ma.

Professional Endeavors

Currently holding the position of Assistant Professor at the Guangdong Institute of Smart Education, Jinan University, Guangzhou, China, Zhiwei Yang has demonstrated his commitment to academia. His professional path has been marked by a dedication to unraveling the intricacies of Information Extraction and Rumor Detection.

Contributions and Research Focus

Zhiwei Yang's research contributions extend beyond the confines of traditional academia. With over 10 publications in esteemed international conferences and journals such as AAAI, IJCAI, EMNLP, COLING, TNNLS, IPM, Neurocomputing, among others, he has significantly impacted the fields of Information Extraction and Rumor Detection. Furthermore, his innovative work has been acknowledged with the granting of three Chinese national invention patents.

Accolades and Recognition

Zhiwei Yang's scholarly pursuits have earned him recognition and respect in the academic community. Serving as a reviewer for prestigious conferences and journals including ACL, AAAI, KDD, IPM, Neural Networks, reflects the acknowledgment of his expertise in the field.

Impact and Influence

Zhiwei Yang's influence resonates not only through his publications and patents but also through his role as an educator, shaping the minds of aspiring scholars. His insights and contributions have contributed to advancements in the understanding and application of Information Extraction and Rumor Detection.

Legacy and Future Contributions

As an emerging figure in the realm of Computer Science, Zhiwei Yang's legacy is marked by a dedication to knowledge dissemination and innovative research. His future contributions are anticipated to further enrich the fields of Information Extraction and Rumor Detection, leaving an enduring impact on the academic landscape.

Notable Publications

A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection 2022

Context-Aware Attentive Multilevel Feature Fusion for Named Entity Recognition 2022 (22)