Liansheng Ling | sensor | Best Researcher Award

Prof. Dr. Liansheng Ling | sensor | Best Researcher Award

Sun Yat-Sen University/School of Chemistry, China

Author Profile

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Academic Background

Lian-Sheng Ling obtained his Ph.D. in Analytical Chemistry from Wuhan University in 2000. He then pursued postdoctoral research at the Institute of Chemistry, Chinese Academy of Sciences (CAS) from 2000 to 2002, followed by another postdoctoral position at the renowned Max Planck Institute for Polymer Research in Mainz, Germany, between 2003 and 2004.

Academic Career

In 2005, he joined the School of Chemistry at Sun Yat-Sen University, where he continued his academic and research journey. Due to his outstanding contributions in the field, he was promoted to Professor of Chemistry in December 2011.

Research Interests

His research is primarily focused on developing biosensing methods for detecting DNA, RNA, and biomarkers related to cancer. To achieve this, he utilizes a combination of advanced techniques, including fluorescence-based sensing, colorimetric detection, and dynamic light scattering (DLS). These innovative approaches aim to provide highly sensitive and specific detection tools for early diagnosis and monitoring of cancers.

Notable Publications


Novel dynamic light scattering immunosensor for prostate specific antigens based upon dual-tyramine signal amplification strategy

Journal: Sensors and Actuators B: Chemical

Year: 2024


Chemical-Chemical Redox Cycle Signal Amplification Strategy Combined with Dual Ratiometric Immunoassay for Surface-Enhanced Raman Spectroscopic Detection of Cardiac Troponin I

Journal: Analytical Chemistry

Year: 2023


Colorimetric and dynamic light scattering dual-readout assay for formaldehyde detection based on the hybridization chain reaction and gold nanoparticles

Journal: Sensors and Diagnostics

Year: 2023


RGB color analysis of formaldehyde in vegetables based on DNA functionalized gold nanoparticles and triplex DNA

Journal: Analytical Methods

Year: 2022


Hybridization chain reaction and DNAzyme-based dual signal amplification strategy for sensitive fluorescent sensing of aflatoxin B1 by using the pivot of triplex DNA

Journal: Food Research International

Year: 2022


CRISPR/Cas12a-based biosensor for colorimetric detection of serum prostate-specific antigen by taking nonenzymatic and isothermal amplification

Journal: Sensors and Actuators B: Chemical

Year: 2022

Ms. Yingjuan Tang, Sensors and Biosensors, Best Researcher Award

Ms. Yingjuan Tang, Sensors and Biosensors, Best Researcher Award

Ms. Yingjuan Tang, Beijing Institute of Technology, China

Professional Profiles

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🌟 Summary

Ms. Yingjuan Tang is a dedicated Ph.D. candidate at Beijing Institute of Technology, specializing in environment perception and trajectory prediction for autonomous vehicles. With a strong background in computer vision and deep learning, she has contributed extensively to the field through publications in prestigious journals. Yingjuan holds a Master’s degree in Artificial Intelligence from King’s College London and a Bachelor’s degree in Computer Science and Technology from Zhengzhou University.

🎓 Education

Doctorate in Environment Perception and Trajectory Prediction
Beijing Institute of Technology
Master’s in Artificial Intelligence
King’s College London
Bachelor’s in Computer Science and Technology
Zhengzhou University

đź’ĽProfessional Experience

Ph.D. Researcher
Beijing Institute of Technology
Focused on environment perception and trajectory prediction for self-driving commercial vehicles. Published multiple papers in leading journals on 3D object detection and trajectory prediction.

🔬 Research Interests

Computer Vision: Exploring advanced techniques for image recognition and processing.

Deep Learning: Applying neural networks to enhance autonomous vehicle perception and decision-making.

Autonomous Vehicles: Developing models for trajectory prediction and environment sensing.

🏆 Honors & Awards

Outstanding Graduate (Henan Province)
National Motivational Scholarship (2016-2017 & 2017-2018)
Second Prize in ACM Program-Designing Competition

Publications Top Noted📚

Towards efficient multi-modal 3D object detection: Homogeneous sparse fuse network

Authors: Tang, Y., He, H., Wang, Y., Wu, J.

Journal: Expert Systems with Applications

Year: 2024

Using a Diffusion Model for Pedestrian Trajectory Prediction in Semi-Open Autonomous Driving Environments

Authors: Tang, Y., He, H., Wang, Y., Wu, Y.

Journal: IEEE Sensors Journal

Year: 2024

Hierarchical vector transformer vehicle trajectories prediction with diffusion convolutional neural networks

Authors: Tang, Y., He, H., Wang, Y.

Journal: Neurocomputing

Year: 2024

Remote Sensing Building Change Detection With Global High-Frequency Cues Guidance and Result-Aware Alignment

Authors: Mao, Z., Luo, Z., Tang, Y.

Journal: IEEE Geoscience and Remote Sensing Letters

Year: 2024

Multi-modality 3D object detection in autonomous driving: A review

Authors: Tang, Y., He, H., Wang, Y., Mao, Z., Wang, H.

Journal: Neurocomputing

Year: 2023

Cooperative energy management and eco-driving of plug-in hybrid electric vehicle via multi-agent reinforcement learning

Authors: Wang, Y., Wu, Y., Tang, Y., Li, Q., He, H.

Journal: Applied Energy

Year: 2023