Ling Zheng | Computer Science and Artificial Intelligence | Research Excellence Award

Dr. Ling Zheng | Computer Science and Artificial Intelligence | Research Excellence Award

Fujian Maternity and Children Health Hospital | China 

The researcher holds advanced training in computer science with a strong specialization in artificial intelligence and machine learning, Computer Science and Artificial Intelligence particularly in efficient attention mechanisms and multimodal large models for medical and healthcare applications. Current research focuses on the development of intelligent systems for placental pathology analysis, automated diagnostic report generation, and AI-assisted clinical decision support. Major contributions include the construction of annotated medical image databases, AI-guided lesion standardization frameworks, and the application of dynamic intelligent models to support maternal health interventions. The research portfolio also extends to large-scale data management, privacy protection, and secure data sharing technologies for auditory and visual cognitive models, as well as knowledge graph representation and swarm intelligence collaboration. In addition to academic research, the work includes close collaboration with industry partners to develop domain-specific large models for gynecologic oncology and multimodal AI systems for placental pathology diagnosis. Scholarly contributions span high-impact peer-reviewed journals in artificial intelligence, medical informatics, data science, and interdisciplinary computational research. The researcher has also contributed to the academic community through service on program committees for leading international conferences in artificial intelligence, computer vision, and data analytics. Overall, the research demonstrates strong innovation, translational impact, and commitment to advancing AI-driven healthcare technologies.

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Featured Publications

Computer-aided detection of prostate cancer in T2-weighted MRI within the peripheral zone
A. Rampun, L. Zheng, P. Malcolm, B. Tiddeman, R. Zwiggelaar – Physics in Medicine & Biology, 61(13), 4796, 2016

Self-adjusting harmony search-based feature selection
L. Zheng, R. Diao, Q. Shen – Soft Computing, 19(6), 1567–1579, 2015

Feature grouping and selection: A graph-based approach
L. Zheng, F. Chao, N. Mac Parthaláin, D. Zhang, Q. Shen – Information Sciences, 546, 1256–1272, 2021

Boundary-aware network with two-stage partial decoders for salient object detection in remote sensing images
Q. Zheng, L. Zheng, Y. Bai, H. Liu, J. Deng, Y. Li – IEEE Transactions on Geoscience and Remote Sensing, 61, 1–13, 2023

A distributed joint extraction framework for sedimentological entities and relations with federated learning
T. Wang, L. Zheng, H. Lv, C. Zhou, Y. Shen, Q. Qiu, Y. Li, P. Li, G. Wang – Expert Systems with Applications, 213, 119216

Mr. Nicolò Antonelli – Immersed Isogeometric Analysis -Young Scientist Award

Mr. Nicolò Antonelli - Immersed Isogeometric Analysis -Young Scientist Award

CIMNE / UPC - Spain

Professional Profile

ORCID

EARLY ACADEMIC PURSUITS 🎓

Born on January 23, 1998, in Gavardo, Italy, Nicolò Antonelli embarked on his academic journey with a strong foundation in mechanical engineering. He earned his Bachelor's degree in Mechanical Engineering from the University of Padua, where he developed a keen interest in numerical methods and mathematical modeling. His thesis on polynomial interpolation and the Virtual Element Method laid the groundwork for his future research endeavors. He continued his education at the University of Padua, pursuing a Master's degree in Mathematical Engineering. His Master's thesis focused on a novel Shifted Boundary Method (SBM) for embedded domains, earning him a summa cum laude distinction.

PROFESSIONAL ENDEAVORS 🏢

Nicolò's professional journey has been marked by significant roles in academia and research. Currently, he is a Ph.D. candidate at CIMNE, Universitat Politècnica de Catalunya, Spain, where he explores IBRA-type discretizations in Computational Fluid Dynamics (CFD). Prior to this, he completed a traineeship at CIMNE, working closely with advisors Riccardo Rossi and Rubén Zorrilla. His work has primarily focused on the development and application of advanced computational methods in engineering.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Nicolò's research contributions are notable in the field of numerical methods and computational mechanics. He has been instrumental in advancing the Shifted Boundary Method (SBM) and its application in Isogeometric Analysis (IGA). His work aims to improve the accuracy and efficiency of simulations involving complex geometries and embedded domains. His contributions extend to conferences and publications, Immersed Isogeometric Analysis where he has presented his findings on SBM in IGA, making significant strides in the integration of computational techniques in engineering analysis.

ACCREDITATIONS AND RECOGNITION 🏅

Nicolò's academic and research excellence has been recognized through various scholarships and awards. He was a four-time recipient of the "Double Career Student-Athlete" scholarship, acknowledging his outstanding balance between academics and sports. Additionally, he received the "Mille e Una Lode" scholarship for academic merit at the University of Padua. His contributions to the field have been published in Immersed Isogeometric Analysis prestigious journals, including "Computer Methods in Applied Mechanics and Engineering," showcasing his research on SBM and its applications.

IMPACT AND INFLUENCE 🌐

Nicolò's work has significantly impacted the fields of numerical methods and computational engineering. His research on SBM and IGA has provided valuable insights into solving complex engineering problems, particularly in CFD. His work on multi-point constraints and embedded Immersed Isogeometric Analysis domain methods has paved the way for more accurate and efficient simulations, influencing both academic research and practical applications in engineering.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Nicolò Antonelli's legacy is defined by his innovative contributions to numerical methods and his dedication to advancing computational engineering. As he continues his Ph.D. research, he aims to further refine and expand the applications of SBM and other computational techniques. His future contributions are expected to shape the field of computational mechanics, offering new solutions and methodologies for complex engineering challenges.

NOTABLE PUBLICATIONS