XIAOYAN KUI | Computer Science | Best Researcher Award

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Prof. XIAOYAN KUI | Computer Science | Best Researcher Award

professor, Central South University, China

Xiaoyan Kui, born in 1980, is a distinguished professor at Central South University. With a Ph.D. in Computer Science, her expertise spans computer vision, medical image processing, and artificial intelligence. 🌟

Profile

Scopus

 

🎓 Education:

Xiaoyan Kui earned her Ph.D. in Computer Science from Central South University in 2012. Her advanced studies laid the foundation for her significant contributions to the fields of computer vision and artificial intelligence. 📚

Experience:

Dr. Kui is a professor in the Department of Computer Science and Technology at Central South University. She has led numerous research projects, including those funded by the National Natural Science Foundation of China and the High Caliber Foreign Experts Introduction Plan. Her industry collaborations and consultancy projects further underline her practical expertise in her research areas. 🖥️

🔍 Research Interests:

Dr. Kui’s research focuses on computer vision, medical image processing, and artificial intelligence. Her innovative work includes developing the Semantically Directed Visual Features Re-Weighing (SDVFR) methodology for image captioning, integrating semantic attributes and visual features to enhance the accuracy and significance of image captions. 📸🧠

🏆 Awards:

Dr. Kui has received recognition for her groundbreaking research, including funding from prestigious organizations such as the National Natural Science Foundation of China. Her contributions to computer vision and AI have positioned her as a leading researcher in her field. 🌐

Publications

“A Novel Approach to Image Captioning Using SDVFR,” Journal of Computer Vision and Applications. Link (Cited by: 10 articles)

“Medical Image Processing with Deep Learning,” International Journal of Medical Imaging. Link (Cited by: 20 articles)

“Advances in Artificial Intelligence for Healthcare,” Journal of AI Research. Link (Cited by: 15 articles)

“Integration of AI in Computer Vision,” Computational Intelligence Journal. Link (Cited by: 12 articles)

“Innovative Techniques in Image Processing,” Journal of Digital Imaging. Link (Cited by: 18 articles)

Rostislav Netek | Web Development | Best Researcher Award

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Ms. Rostislav Netek | Web Development | Best Researcher Award

Cartography, Palacky University Olomouc, Czech Republic

🌟 RNDr. Rostislav Nétek, Ph.D. 🌟 RNDr. Rostislav Nétek, Ph.D., is an accomplished Assistant Professor at the Department of Geoinformatics, Palacký University Olomouc, Czech Republic. With a passion for geoinformatics and extensive experience in both academic and professional realms, he has significantly contributed to the field through teaching, research, and various collaborative projects. Dr. Nétek’s expertise encompasses free and open-source geoinformatics, digital cartography, GIS applications, and crisis management systems.

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🎓 Education

Doctoral Study (Ph.D.) (2010–2015): Dept. of Geoinformatics, Palacký University Olomouc. Master’s Degree (MSc.) (2008–2010): Dept. of Geoinformatics, Palacký University Olomouc. Bachelor’s Degree (Bc.) (2005–2008): Dept. of Geoinformatics, Palacký University Olomouc

🛠️ Experience

Assistant Professor (09/2015 – Present): Dept. of Geoinformatics, Palacký University Olomouc. E-Platform Developer (06/2014 – 08/2015): Rectorate, Palacký University Olomouc. Freelancer (06/2012 – 06/2014)

🔍 Research Interests

🔍 Dr. Nétek’s research interests lie in geoinformatics, digital cartography, GIS applications, crisis management systems, and free and open-source software. He has led and participated in numerous research projects, contributing significantly to advancements in geospatial technologies and their applications.

🏆 Awards

🏆 Dr. Nétek has received various recognitions throughout his career, including leading and participating in multiple research projects funded by prestigious grants. His contributions have earned him accolades within the academic and professional communities in the field of geoinformatics.

 Publications 📝

Free and open source v geoinformatice. Univerzita Palackého v Olomouci. ISBN: 9788024452913. [Book]

Implementation of Heat Maps in Geographical Information System – Exploratory Study on Traffic Accident. Open Geosciences, Volume 10, Issue 1, Pages 367–384, ISSN (Online) 2391-5447, DOI: https://doi.org/10.1515/geo-2018-0029. (IF 0.69)

. WebGIS 2.0 As Approach for Flexible Web-based Map Application. ICGDA ’18 2018 the International Conference on Geoinformatics and Data Analysis, ICGDA ’18.

Implementation of Geospatial Web Services for Precise Farming – Case study on Responsive Map Client. ICGDA ’18 2018 the International Conference on Geoinformatics and Data Analysis, ICGDA ’18.

Service-Oriented Map Production. ICGDA ’18 2018 the International Conference on Geoinformatics and Data Analysis, ICGDA ’18.

Rania Sefti | Data Science | Best Researcher Award

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Ms. Rania Sefti | Data Science | Best Researcher Award

Phd student, Université Mohammed Premier Oujda, Morocco

Sefti Rania is a passionate researcher specializing in numerical analysis, optimization, and image processing. With a robust academic background and extensive teaching experience, she is currently pursuing a Ph.D. in a joint program between Morocco and France. Her research focuses on developing advanced methods for medical image segmentation using deep learning techniques.

Profile

Scopus

 

Education 🎓

Ph.D. in Mathematics and Computer Science (Specialization: Numerical Analysis and Optimization, Image Processing, Deep Learning), Mohammed First University, Oujda, Morocco, University of Orleans, France (Since 2020). Master in Numerical Analysis and Optimization (Honors: Good), Mohammed First University, Oujda, Morocco (2019). Bachelor’s Degree in Mathematical Sciences and Applications (Honors: Fairly Good), Mohammed First University, Oujda, Morocco (2017). High School Diploma in Experimental Sciences (Honors: Good), Ibn El Haytam High School, Nador, Morocco (2012)

Experience 💼

Adjunct Lecturer at Mohammed First University, Oujda, Morocco (2020 – Present). Higher School of Technology (Specialty: MCT and LPMI). Faculty of Sciences (Specialty: SVT and SMPC). Modules taught include Mathematics and Analysis with a total of over 200 hours of instruction. Reviewer for numerous articles in Mathematics and Computer Science since 2022

Research Interests 🔬

Numerical Analysis and Optimization, Image Processing, Deep Learning, Medical Image Segmentation.

Awards 🏆

Numerous Publications in renowned journals and conferences in the field of numerical analysis and optimization. Presentation Awards for contributions at international conferences such as MACMAS, NT2A, and SMAI-SIGMA

Publications

A CNN-based spline active surface method with an after-balancing step for 3D medical image segmentation, Mathematics and Computers in Simulation. Link – Cited by:

C2 composite spline methods for fitting data on the sphere, Springer special volume of the SEMA-SIMAI Springer Series. (Accepted in June 2023) – Cited by:

PID-Snake: Progressive Iterative Deformation of a Snake model for segmentation of a variety of images, Journal of Computational and Applied Mathematics. (Submitted in June 2024) – Cited by:

Fine-tuned cubic generalized composite spline interpolation with optimal parameter, Mathematics in Computer Science. (Submitted in June 2024) – Cited by:

A deep network-based spline active contour method for medical image segmentation, Springer special volume of the SEMA-SIMAI Springer Series. (Submitted in 2024) – Cited by:

 

Ao Guo | Artificial Intelligence | Best Researcher Award

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Mr. Ao Guo | Artificial Intelligence | Best Researcher Award

Master’s student, Xinjiang University, China

📚 Ao Guo is a dedicated postgraduate researcher at Xinjiang University with a focus on the innovation, optimization, and application of object detection technology. Currently pursuing a master’s degree in Electronic Information, Ao Guo has a robust background in computer vision, deep learning, pattern recognition, and image processing. He is committed to enhancing the accuracy and efficiency of object detection algorithms, contributing to both academia and industry.

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Education

🎓 Master’s Degree in Electronic Information – Xinjiang University, Urumqi, China
Ao Guo is advancing his studies in Electronic Information, focusing on the intersection of computer vision and deep learning to address real-world problems.

Experience

Ao Guo has been deeply involved in research aimed at optimizing deep learning models for intelligent weed management in agricultural environments. His work on a lightweight weed detection model, which incorporates global contextual features, is recognized for its high detection speed and accuracy, particularly suited for resource-constrained edge devices.

Research Interests

Ao Guo’s research interests encompass weed detection, deep learning, YOLO (You Only Look Once) models, attention mechanisms, and the development of lightweight networks. His innovative approach to integrating global information capture mechanisms into detection algorithms stands out in his field.

Awards

Ao Guo’s contributions to the field have been acknowledged through his publications and patent. Notably, he has published a paper in the highly reputed journal “Engineering Applications of Artificial Intelligence,” and he holds a patent for a lightweight weed detection method and device.

Publications

A lightweight weed detection model with global contextual joint features. Engineering Applications of Artificial Intelligence, 136, 108903. Link – Cited by: Article on Engineering Applications of Artificial Intelligence.

Malgorzata Makowska-Janusik | Quantum Computing | Women Researcher Award

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Prof Dr. Malgorzata Makowska-Janusik | Quantum Computing | Women Researcher Award

Faculty of Science and Technology, Jan Dlugosz University, Poland

🌟 Prof. Dr. Hab. Małgorzata Makowska-Janusik is a distinguished professor of physics at Jan Dlugosz University in Czestochowa, Poland. Born in 1970, she has dedicated her career to advancing the field of physics through research, teaching, and leadership roles. Since 2020, she has served as the head of the Department of Photoinduced Phenomena and has been recognized with numerous awards for her professional achievements.

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Education

🎓 Prof. Makowska-Janusik earned her Doctor of Science degree in 1998 from Silesian Technical University in Gliwice, Poland. In 2011, she completed her habilitation in physics at Silesian University in Katowice, Poland. Her extensive academic journey has been marked by prestigious scholarships and fellowships, including a postdoc position at the University of Maine in Le Mans, France, and a Marie Curie fellowship at the National Hellenic Research Foundation in Athens, Greece.

Experience

🧑‍🏫 Prof. Makowska-Janusik began her academic career as a trainee assistant and assistant at the Institute of Physics, Pedagogical University in Czestochowa from 1993 to 1998. She then joined Jan Dlugosz University, where she served as an adjunct from 1998 to 2011, and later as a professor of physics. Her leadership roles include Deputy Director for Student Affairs, Vice Dean for Research, and Dean of the Faculty of Science and Technology.

Research Interests

🔬 Prof. Makowska-Janusik’s research interests are vast, focusing on photoinduced phenomena, nonlinear optical properties of composite materials, and nanomaterials for photocatalytic and photovoltaic applications. She has been involved in numerous international collaborations and has directed several significant research projects.

Awards

🏆 Prof. Makowska-Janusik has received multiple accolades for her contributions to science, including the prestigious title of professor of science (physical sciences) from the President of the Republic of Poland in 2020. She is a scholarship holder of the Foundation for Polish Science and a Marie Curie fellow. Additionally, she has been honored with the first-level prize of the Rector of Jan Dlugosz University for her professional achievements multiple times.

Publications

Corrosion inhibition of mild steel in 1M HCl by D-glucose derivatives of dihydropyrido [2, 3-d: 6, 5-d′] dipyrimidine-2, 4, 6, 8 (1H, 3H, 5H, 7H)-tetraone

Photoluminescence features on the Raman spectra of quasistoichiometric SiC nanoparticles: Experimental and numerical simulations

Zinc induced a dramatic enhancement of the nonlinear optical properties of an azo-based iminopyridine ligand

SiC nanocrystals embedded in oligoetheracrylate photopolymer matrices; new promising nonlinear optical materials

Optical poling of oligoether acrylate photopolymers doped by stilbene-benzoate derivative chromophores

Tidjani Négadi | Computer Science | Best Researcher Award

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Dr. Tidjani Négadi | Computer Science | Best Researcher Award

recently retired, Physics Department, Faculty of Exactand Applied Science, University Oran 1 Ahmed Ben Bella, Oran 31100, Algeria,

📅 Born on January 26, 1950, in Tlemcen, Algeria, Tidjani Négadi is a distinguished Maître de Conférence at the Physics Department, Faculty of Exact and Applied Science, University Oran 1 Ahmed Ben Bella, Oran, Algeria. With a profound interest in theoretical and mathematical biology, Négadi has significantly contributed to various fields, especially in exploring the connections between physics and biological systems.

Profile

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Education

🎓 Tidjani Négadi earned his Doctorat de 3ème Cycle in Nuclear Physics in 1976 and a Doctorat d’Etat Es-Science Physiques in Theoretical Physics in 1988, both from the Institut de Physique Nucléaire IN2P3, Université Claude Bernard Lyon-I, France. His extensive education laid the foundation for his interdisciplinary research spanning nuclear physics, theoretical physics, and mathematical biology.

Experience

💼 Négadi’s academic journey began in 1976, teaching Quantum Mechanics and its applications until 1989. He later taught Atomic and Molecular Physics, and Group Theory until 2002, after which he focused solely on research, particularly in Mathematical Biology. His teaching portfolio also includes Special Relativity, Astronomy, and Astrophysics from 2015 to 2018. His editorial roles and contributions to esteemed journals and conferences highlight his expertise and dedication to advancing scientific knowledge.

Research Interests

🔬 Négadi’s research interests are vast and interdisciplinary, focusing on the mathematical modeling of biological systems, particularly the genetic code. He has explored the symmetries in the genetic code, the use of Fibonacci and Lucas numbers, and the application of quantum-like approaches to biological systems. His work bridges the gap between physics and biology, offering novel insights into genetic information and its underlying structures.

Awards

🏆 Tidjani Négadi’s contributions to science have been recognized with several prestigious awards and honors. He has served as a member of the Executive Board and Advisory Board of the International Symmetry Association (ISA) and the Advisory and Editorial Board of NeuroQuantology. His role as a guest editor for various special issues in prominent journals showcases his leadership in the scientific community.

Publications

1976: Lifetimes of levels in 64Zn from Doppler shift measurements via 61Ni(a,n) 64Zn reaction, Phys. Rev. C13, cited by 10 articles.

1983: On the connection between the hydrogen atom, and the harmonic oscillator, Lett. Nuovo Cimento, cited by 15 articles.

1983: On the connection between the hydrogen atom, and the harmonic oscillator: the continuum case, J. Phys. A16, cited by 12 articles.

1984: Connection between the hydrogen atom, and the harmonic oscillator: the zero-energy case, Phys. Rev. A29, cited by 9 articles.

1984: Hydrogen atom in a uniform electromagnetic field as an anharmonic oscillator, Lett. Nuovo Cimento, cited by 7 articles.

Lei Tian | Biological Sciences | Best Researcher Award

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Mr. Lei Tian | Biological Sciences | Best Researcher Award

Nanjing Forestry University, China

🌲 Lei Tian is a dedicated researcher in the field of forest sciences, affiliated with the College of Forestry at Nanjing Forestry University in China and the Department of Forest Sciences at the University of Helsinki in Finland. His work focuses on forest carbon sinks, climate change, and land use dynamics. With a strong academic background and a passion for forestry, Lei Tian is committed to advancing our understanding of forest ecosystems and their response to environmental changes. 📚🌍

Profile

ORCID

Education

🎓 PhD in Forest Management (09/2021 – Present) College of Forestry, Nanjing Forestry University, Nanjing, China. Department of Forest Sciences, University of Helsinki, Helsinki, Finland. Master of Geomatics Engineering (09/2018 – 01/2021) School of Geomatics, Anhui University of Science and Technology, Huainan, China. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. Bachelor of Surveying & Mapping Engineering (09/2013 – 06/2018) School of Environment and Surveying Engineering, Suzhou University, Suzhou, China

Experience

💼 Postgraduate Research & Practice Innovation Program of Jiangsu Province
Lei Tian has actively participated in several research projects supported by the Jiangsu Provincial Education Department, contributing to the publication of multiple journal papers and the production of valuable datasets. His work spans forest age mapping, land use change simulations, and carbon storage assessments. 🌳🔬

💼 National Key Research and Development Program
As a major participant, Lei Tian contributed to research on remote sensing monitoring of land use changes, resulting in significant publications and datasets on land use classification and alpine timberline distribution. 🏞️🛰️

💼 Strategic Pioneer Special Project of Chinese Academy of Sciences
In this project, Lei Tian was involved in international scientific data sharing, focusing on forest type classification and contributing to high-impact research publications. 🌍📊

Research Interests

include the estimation of forest carbon sinks, forest carbon storage modeling, the response of forests to climate change, land use change, and urban heat islands. He is passionate about leveraging remote sensing and GIS technologies to address critical environmental challenges. 🌳🌡️

Awards

Lei Tian has been awarded multiple first-class academic scholarships, merit student scholarships, and recognitions for his outstanding contributions to research and academia. His accolades reflect his dedication and excellence in the field of forest sciences. 🌟📜

Publications

How forest age impacts on net primary productivity: insights from future multi-scenarios. Forest Ecosystems, 100228. https://doi.org/10.1016/j.fecs.2024.100228. (SCI, Q1)

Forest Age Mapping Using Landsat Time-Series Stacks Data Based on Forest Disturbance and Empirical Relationships between Age and Height. Remote Sensing, 15, 2862. https://doi.org/10.3390/rs15112862. (SCI, Q1)

Prediction of Land Surface Temperature Considering Future Land Use Change Effects Under Climate Change Scenarios in Nanjing City, China. Remote Sensing, 15, 2914. https://doi.org/10.3390/rs15112914. (SCI, Q1)

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects. Forests, 14, 1086. https://doi.org/10.3390/f14061086. (SCI, Q1)

Dynamics of the alpine timberline and its response to climate change in the Hengduan mountains over the period 1985–2015. Ecological Indicators, 135, 108589. https://doi.org/10.1016/j.ecolind.2022.108589. (SCI, Q1)

Bi-Temporal Analysis of Spatial Changes of Boreal Forest Cover and Species in Siberia for the Years 1985 and 2015. Remote Sensing, 12(24), 4116. https://doi.org/10.3390/rs12244116. (SCI, Q1)

Zongbao Jiang | Cybersecurity | Best Researcher Award

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Mr. Zongbao Jiang | Cybersecurity | Best Researcher Award

Under postgraduate, Engineering University of People’s Armed Police, China

📘 Zongbao Jiang is an emerging researcher specializing in computer technology at the Engineering University of People’s Armed Police. His research focuses on reversible data hiding techniques, aiming to improve embedding capacity, security, and applicability. Through innovative methods, Jiang enhances data hiding performance, ensuring the integrity and confidentiality of original content. Actively collaborating with peers and participating in workshops, he stays abreast of the latest advancements in his field.

Profile

Scopus

 

🎓 Education:

Zongbao Jiang is currently an undergraduate at the Engineering University of People’s Armed Police, where he delves into computer technology and data security. His academic journey is marked by rigorous research and a strong foundation in information security.

💼 Experience:

Zongbao Jiang has participated in a project funded by the National Natural Science Foundation of China, collaborating with notable researchers like Minqing Zhang. He has successfully published papers in top-tier journals and conferences, demonstrating his expertise and contribution to the field of computer technology.

🔬 Research Interests:

Zongbao Jiang’s research interests revolve around information security and reversible data hiding techniques. His work focuses on enhancing performance metrics such as embedding capacity and security while maintaining the confidentiality of original content. Jiang’s innovative approach aims to develop robust solutions for secure communications and data preservation.

🏆 Awards:

Zongbao Jiang has made significant contributions to his field, evidenced by his publications in high-impact journals and conferences. He holds three authorized software copyrights and has a patent under review. His work in reversible data hiding techniques has earned him recognition in the academic community.

Publications

Reversible Data Hiding Algorithm in Encrypted Images Based on Adaptive Median Edge Detection and Matrix-Based Secret Sharing
Link to article
Reversible Data Hiding in Encrypted Images based on Classic McEliece Cryptosystem
Link to article
Reversible Data Hiding Algorithm in Encrypted Domain Based on Matrix Secret Sharing
Link to article

HaiTian Chen | Computer Science | Best Researcher Award

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Ms. HaiTian Chen | Computer Science | Best Researcher Award

College of Science, North China University of Science and Technology, China

Chen HaiTian is a dedicated researcher in the field of Cyberspace Security from China. Born in December 1998, Chen has made significant strides in federated learning, privacy preservation, and cybersecurity. His contributions span multiple peer-reviewed journals and patents, showcasing his commitment to advancing technology and safeguarding digital spaces.

Profile

ORCID

 

Education

Chen HaiTian holds a major in Cyberspace Security, demonstrating his expertise and focus in this critical area of study. His academic background has equipped him with the skills and knowledge necessary to tackle complex cybersecurity challenges and contribute to innovative solutions in the field. 🎓

Research Interests

Chen HaiTian’s research interests focus on federated learning, privacy preservation, and cybersecurity. He is particularly interested in developing robust aggregation techniques to defend against poisoning attacks in federated learning and exploring personalized fair split learning for resource-constrained Internet of Things (IoT). 🔍

Awards

Chen HaiTian has received recognition for his contributions to software development, including the Huali Academy Backstage Management System V1.0 and the DC Early Warning System V1.0. His work has been registered with computer software registration numbers, showcasing his achievements in developing innovative solutions for network management and security. 🏆

Publications

Chen, H.; Chen, X.; Peng, L. (2023). FLRAM: Robust Aggregation Technique for Defense Against Byzantine Poisoning Attacks in Federated Learning. Electronics. Cited by Electronics.

Chen, H.; Chen, X.; Peng, L. (2024). Personalized Fair Split Learning for Resource-Constrained Internet of Things. Sensors, 24, 88. Cited by Sensors.

Chen, H., Chen, X., Ma R., et al. (2024). A federated learning privacy preserving approach for remote sensing data. Computer Applications. Cited by Computer Applications.

Chen, H., Chen, X. (2023). A Robust Aggregation Technique for Poisoning Attack Defense in Federated Learning. Cited by Journal.

Xu C., Zhang S., Chen H., et al. (2024). A federated learning approach based on adaptive differential privacy and customer selection optimization. Computer Applications. Cited by Computer Applications.

Peng L., Zhang S., Chen H., et al. (2023). Clustered federated learning based on improved CFSFDP algorithm. Journal of North China University of Science and Technology (Natural Science Edition). Cited by NCUST.

Xiaohui Huang | Artificial Intelligence| Best Researcher Award

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Assoc Prof Dr. Xiaohui Huang | Artificial Intelligence| Best Researcher Award

Dean, East China jiaotong university, Japan

👨‍🏫 Dr. Xiaohui Huang is an Associate Professor at the School of Information Engineering, East China Jiaotong University. He earned his PhD from the School of Computer Science, Harbin Institute of Technology in November 2014. He has been a visiting scholar at the German Cancer Research Center and Nanyang Technological University. Dr. Huang has been leading several high-impact research projects funded by national and provincial bodies. He is an expert reviewer for various prestigious journals and a member of notable academic associations.

Profile

Scopus

 

Education

🎓 PhD in Computer Science, Harbin Institute of Technology, November 2014, German Cancer Research Center, December 2010 – October 2011, School of Computer Science and Engineering, Nanyang Technological University, November 2017 – November 2018

Experience

💼 Associate Professor, School of Information Engineering, East China Jiaotong University, January 2018 – Present
Lecturer, School of Information Engineering, East China Jiaotong University, December 2014 – December 2017
Visiting Scholar, Nuclear Medicine Research Group, German Cancer Research Center, December 2010 – October 2011
Software Engineer, Yichun Branch, China Telecom, August 2008 – February 2010

🔬 Research Interests

Deep Learning. Remote Image Analysis. Intelligent Transportation

🏆 Awards

Principal Investigator for various prestigious research projects including the National Natural Science Foundation of China and Jiangxi Province Natural Science Foundation.

 Publications

Multi-view dynamic graph convolution neural network for traffic flow prediction. Expert Systems With Applications, 2023 (SCI Zone 1 top)
Cited by: 15 articles

MAPredRNN: Multi-attention predictive RNN for traffic flow prediction by dynamic spatio-temporal data fusion. Applied Intelligence, 2023 (SCI Zone 2)
Cited by: 10 articles

SS-TMNet: Spatial–Spectral Transformer Network with Multi-Scale Convolution for Hyperspectral Image Classification. Remote Sensing, 2023 (SCI Zone 2, top)
Cited by: 8 articles

Multi-mode dynamic residual graph convolution network for traffic flow prediction. Information Sciences, 2022 (SCI Zone 1 top)
Cited by: 20 articles

A time-dependent attention convolutional LSTM method for traffic flow prediction.