Qili Chen | Artificial Neural Networks | Best Researcher Award

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Ms. Qili Chen | Artificial Neural Networks | Best Researcher Award

Associate Professor Beijing Information Science and Technology University China

Dr. Qili Chen is an accomplished Associate Professor at Beijing Information Science and Technology University, specializing in artificial neural networks and intelligent systems. With a strong academic foundation and global collaboration experience, she has contributed significantly to the fields of deep learning and small object detection. Her academic journey reflects both international exposure and commitment to scientific excellence, having visited the University of Wisconsin, Milwaukee during her Ph.D. studies. Dr. Chen is a passionate researcher recognized for her innovative work in neural modeling and optimization.

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šŸŽ“ Education

Dr. Chen received both her Masterā€™s (2010) and Ph.D. (2014) degrees in Pattern Recognition and Intelligent System from Beijing University of Technology. During her doctoral studies, she broadened her research perspective through a visiting scholar program (Sept 2012ā€“Aug 2013) at the Department of Mathematical Sciences, University of Wisconsin, Milwaukee, USA.

šŸ’¼ Experience

Dr. Qili Chen currently serves as an Associate Professor at Beijing Information Science and Technology University. She has led and participated in 14 research projects, collaborated with global researchers such as Doug Briggs and Yi Ming Zou, and contributed to both academia and industry through research consultancy. She also served as a Track TPC Member for the 2023 IEEE ICICN Conference. With memberships in prestigious AI and automation committees in China, her professional presence is robust and influential.

šŸ”¬ Research Interests

Her primary research interests include Artificial Neural Networks, Small Object Detection, Modelling, and Optimal Control. Dr. Chen focuses on improving aerial image analysis by enhancing deep learning strategies for detecting small objectsā€”an area critical for applications in surveillance, environmental monitoring, and autonomous systems.

šŸ† Awards

Dr. Chen has been nominated for the Best Researcher Award for her remarkable contributions to deep learning and remote sensing applications. Her research has high impact with 788 citations and an H-index of 10, signifying wide academic recognition. She has authored 1 book, published 3 patents, and contributed to 20 peer-reviewed journals, strengthening her candidacy as an innovative leader in AI.

šŸ“š Publications Top Notes:Ā 

Here are selected publications authored by Dr. Qili Chen, including publication years, journal details, and citation counts:

“A survey of small object detection in aerial images via deep learning”
Published in: Artificial Intelligence Review, 2025
šŸ”— Link to Publication
šŸ“ Cited by: 5 articles

Model predictive control of dissolved oxygen concentration based on a self-organizing RBF neural network

Research on an online self-organizing radial basis function neural network

Road safety performance function analysis with visual feature importance of deep neural nets

An adaptive hybrid attention based convolutional neural net for intelligent transportation object recognition

Accurate ovarian cyst classification with a lightweight deep learning model for ultrasound images

The Chemical Oxygen Demand Modeling Based on a Dynamic Structure Neural Network

An improved pictureā€based prediction method of PM2. 5 concentration

Zihan Li | Artificial Neural Networks | Best Researcher Award

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Mr. Zihan Li | Artificial Neural Networks | Best Researcher Award

student College of information Science and Technology, Donghua University China

Li Zihan, a 24-year-old aspiring engineer from Jingdezhen, Jiangxi, is a Masterā€™s student in Information and Communication Engineering at Donghua University, Shanghai. With a strong academic record and hands-on experience in communication systems, autonomous driving, and resource allocation strategies, Li showcases a passion for innovation and excellence in technology.

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Education šŸŽ“

  • Masterā€™s Program (2022 – Present): Donghua University, Shanghai (211/Double First-Class) in Information and Communication Engineering. Excelling in academics, Li ranks in the top 8% of the class.
  • Undergraduate Degree (2018 – 2022): Donghua University, Shanghai, in Communication Engineering. Ranked in the top 6%, with exceptional grades in core courses like Computer Communication Network (99) and Wireless Mobile Communications (94).

Experience šŸ› ļø

Internship at Shanghai NIO Co., Ltd. (2023.02 – 2023.06):
Worked as a Test Intern in the Intelligent Cockpit Function Test Group, specializing in automated assembly line platforms and vehicle-machine testing. Key contributions included writing Python scripts, conducting functional tests, and maintaining Git repositories to support bug identification and resolution.

Research Interest šŸ”¬

Liā€™s research focuses on resource allocation strategies for the Internet of Vehicles, integrating sensing and communication to optimize V2X systems. Li employs MATLAB simulations to evaluate parameters like bandwidth and modulation, leveraging advanced techniques such as Q-learning for adaptive conflict resolution.

Awards šŸ…

  • “TI” Cup Shanghai College Student Electronic Design Competition (Provincial Second Prize) ā€“ 2020.09
  • National Inspirational Scholarship
  • Donghua University Scholarship
  • Xingze Social Scholarship
  • Postgraduate Academic Scholarship

Publications Top Notes: šŸ“š

Research on Resource Allocation Strategy of Side-chain for IoV Integrated with Sensing and Communication

Published in November 2023

Published by [Journal of Vehicle Networking and Communications]

Cited by: 15 articles

Performance Evaluation of SB-SPS Algorithm in Real-world Connected Vehicle Systems

Published in January 2024

Published by [IEEE Transactions on Vehicular Technology]

Cited by: 10 articles