Dr. Yong Ju | Sensors and Biosensors | Best Researcher Award

Dr. Yong Ju | Sensors and Biosensors | Best Researcher Award

Doctorate at UCLA/ Department of Molecular and Medical Pharmacology, United States

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🎓 Academic Background

Yong Ju is a postdoctoral researcher in the Department of Molecular and Medical Pharmacology at the David Geffen School of Medicine, UCLA. He earned his Ph.D. from KAIST (Korea Advanced Institute of Science and Technology) in 2022, specializing in the field of nucleic acid-based nanobiotechnology. His research expertise lies in the development of cutting-edge biosensing technologies for infectious diseases and cancer diagnostics.

🔬 Research Focus and Contributions

Yong Ju has made significant contributions to the field of nanobiotechnology by developing novel sensing strategies for detecting infectious viruses such as COVID-19, influenza, and respiratory syncytial virus (RSV). His work extends to the creation of nanotechnology- and microfluidics-enabled diagnostic platforms capable of processing blood samples for analyzing liquid biopsy markers, including circulating tumor cells (CTCs) and extracellular vesicles (EVs). These advancements are crucial for non-invasive cancer detection and improving diagnostic accuracy in clinical settings.

🏅 Professional Memberships

Yong Ju actively participates in various professional organizations, demonstrating his commitment to scientific collaboration and advancing biotechnology research. He is a member of:

           Korean Society for Biotechnology and Bioengineering (KSBB)

           Korean Institute of Chemical Engineers (KIChE)

           Korean BioChip Society (KBCS)

           Korean Electrochemical Society (KECS)

🔍 Areas of Research Interest

His research primarily focuses on the development of nucleic acid-based nanotechnology and microfluidic platforms to revolutionize non-invasive molecular diagnostics. By integrating sample preparation, diagnostics, and translational analysis, he aims to create innovative solutions that could bring paradigm shifts in drug discovery and clinical patient management. His vision is to bridge the gap between fundamental research and real-world clinical applications, improving early disease detection and personalized medicine.

Noted Publications📚

  • Article: B7-H3-Liquid Biopsy for the Characterization and Monitoring of the Dynamic Biology of Prostate Cancer
    • Authors: Yong Ju, Joshua Watson, Jasmine J. Wang, Ying-Tzu Yen, Lilit Gevorkian, Zijing Chen, Kai Han Tu, Brenda Salumbides, Aaron Phung, Chen Zhao et al.
    • Journal: Drug Resistance Updates
    • Year: 2025
  • Article: Click chemistry-mediated enrichment of circulating tumor cells and tumor-derived extracellular vesicles for dual liquid biopsy in differentiated thyroid cancer
    • Authors: Bing Feng, Jing Wang, Ryan Y. Zhang, Anna Yaxuan Wei, Chen Zhao, Ying-Tzu Yen, You-Ren Ji, Hyoyong Kim, Yong Ju, Matthew Smalley et al.
    • Journal: Nano Today
    • Year: 2024
  • Article: Multifunctional self-priming hairpin probe-based isothermal nucleic acid amplification and its applications for COVID-19 diagnosis
    • Authors: Hansol Kim, Seoyoung Lee, Yong Ju, Hyoyong Kim, Hyowon Jang, Yeonkyung Park, Sang Mo Lee, Dongeun Yong, Taejoon Kang, Hyun Gyu Park
    • Journal: Biosensors and Bioelectronics
    • Year: 2024
  • Article: A personal glucose meter-utilized strategy for portable and label-free detection of hydrogen peroxide
    • Authors: Sang Mo Lee, Hyoyong Kim, Junhyeok Yoon, Yong Ju, Hyun Gyu Park
    • Journal: Biosensors and Bioelectronics
    • Year: 2024
  • Article: A novel isothermal digital amplification system and its application for absolute quantification of respiratory infectious virus
    • Authors: Yong Ju, Yong Ju, Younseong Song, Jaemin Kim, Hyo Yong Kim, Yan Li, Kyoung G. Lee, Seok Jae Lee, Hyun Gyu Park
    • Journal: Biosensors and Bioelectronics: X
    • Year: 2023

 

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

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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