Liwei Deng- Autonomous Driving- Best Researcher Award

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Liwei Deng- Autonomous Driving-Best Researcher Award

Prof. Liwei Deng distinguished academic and researcher in the field Autonomous Driving. 

🌐 Professional Profile

Educations📚📚📚

He holds a Ph.D. in Control Science and Engineering from the Harbin Institute of Technology, Harbin, China, which he earned in 2014. His dissertation focused on “Control Theory and Its Applications of Fractional Order Sliding Mode” under the supervision of Professor Shenmin Song. Prior to this, he completed a Master of Science in Control Theory and Control Engineering at Harbin University of Science and Technology in 2010, where his thesis was titled “Pressure Data Acquisition and Control System Based on ARM,” supervised by Professor Junshan Gao. He began his academic journey with a Bachelor of Engineering in Automation from Jiamusi University, Jiamusi, China, graduating in 2007.

 Experience:

He began his academic career as a Lecturer in the School of Automation at Harbin University of Science and Technology, serving from October 2014 to August 2018. Following this, he was promoted to Associate Professor within the same school, a role he held from August 2018 to August 2023. In September 2023, he was further promoted to the position of Professor at the School of Automation. Additionally, since May 2023, he has been serving as a Doctoral Supervisor in the School of Computer Science and Technology at Harbin University of Science and Technology.

Projects 

He has been actively involved in various research projects over the years. From 2021 to 2024, he led the Key R&D Program Guidance Projects of Heilongjiang Province (Grant No. GZ20210065), focusing on the development of intelligent winding equipment for hydrogen cylinders based on robots. As the Principal Investigator for the National Science Foundation for Young Scientists of China (Grant No. 61806060) from 2019 to 2021, he researched diabetic retinal image analysis algorithms using fractional order differential and deep learning. During the same period, he also served as Principal Investigator for a project funded by the Natural Science Foundation of Heilongjiang Province, China, which focused on the key technology of defect detection of wind turbine blades based on images taken by unmanned aerial vehicles. From 2017 to 2020, he was the Principal Investigator for the Harbin Program of Science and Technology (Grant No. 2017RAQXJ006), which aimed to develop key technologies for the automatic production line for rubber bridge bearing members. Additionally, he played significant roles in several other projects, including being a Principal Participant in the National Natural Science Foundation of China project (Grant No. 61174037) on distributed motion autonomous coordination control of on-orbit multi-spacecraft expectation mode (2011-2015), a Participant in the State Key Program of National Natural Science of China (Grant No. 61333003) on coordination control technology for networked satellite clusters (2012-2016), and a Principal Participant in a project funded by the Natural Science Foundation of Heilongjiang Province, China (Grant No. F030101) on the dynamic morphology of hyperchaotic attractors (2013-2016).

📝🔬Publications📝🔬

    • Deng, L., Zou, Y., Yang, X. et al. L2NLF: a novel linear-to-nonlinear framework for multi-modal medical image registration[J]. Biomed. Eng. Lett.(2024).（WOS:001139763600001）
    • Deng, L., Lan, Q., Zhi, Q. et al. Deep learning-based 3D brain multimodal medical image registration[J]. Med Biol EngComput .2024,62: 505–（WOS:001098686900001）
    • Biao Zhang, Sheng Wang, Liwei Deng, et al.Ship motion attitude prediction model based on IWOA-TCN-Attention[J].Ocean Engineering,2023,272:113911
    • Liwei Deng, Henan Sun, Jing Wang, et al.A Novel Unsupervised MRI Synthetic CT Image Generation Framework with Registration Network[J].CMC-Computers, Materials & Continua,2023,77(2):2271–（WOS:0011269599000 24）
    • Liwei Deng, Zhen Liu,Jiandong Wang et al.ATT-YOLOv5-Ghost: Water surface object detection in complex scenes[J].Journal of Real-Time Image Processing,2023,20:97.（WOS:001050358900001）
    • LiweiDeng,ShanshanLiu,WeiShi,et al.Defect Detection and Classification of Offshore Wind Turbine Rotor Blades[J].Nondestructive Testing and Evaluation,2023.（WOS:001025791800001）
    • Yuheng Yin, Yangang Guo, Liwei Deng, et al.Improved Pspnet-Based Water Shoreline Detection in Complex Inland River Scenarios[J]. Complex & Intelligent Systems, 2022,9(1): 233-245.（WOS:000816995100001）
    • Liwei Deng, Yue Wang, Qi Lan,etal.Remote sensing image building change detection based on efficient-UNet++[J].Journal of Applied Remote Sensing,2023,17(3):034501.（WOS:00177860300006）
    • Liwei Deng, He Cao,QingboDong,etal.Semi-Supervised Lane Detection for Continuous Traffic Scenes[J].Traffic Injury Prevention.2023,24(6):452-457.（WOS:001008469300001）
    • Liwei Deng, Yanchao Zou, SijuanHuang,et al. Deformable 3D Medical Image Registration with ConvolutionalNeural Network and Transformer[J].Journal of Instrumentation.2023,(18):P04029（WOS:000986658100 001）
    • Rui Zhang, Cong Xie, Liwei Deng. A Fine-Grained Object Detection Model for Aerial Images Based on Yolov5 Deep Neural Network[J]. Chinese Journal of Electronics, 2023, 32(1): 51-63.（WOS:000932261100001）
    • Liwei Deng, Yufei Ji, Sijuan Huang, et al.Synthetic CT generation from CBCT using Double-Chain-CycleGAN[J].Computers in Biology and Medicine.2023,106889.（WOS:001006917800001）
    • Liwei Deng, JiandongWang, Zhen Liu. Cascaded Network Based on EfficientNet and Transformer for Deepfake Video Detection[J].Neural Processing Letters.2023.（WOS:000961765200002）
    • Liwei Deng, QiangZhi, Sijuan Huang, et al. A Deformable Patch-based Transformer for 3D Medical Image Registration[J].International Journal of Computer Assisted Radiology and Surgery.2023.（WOS:000990481800001）
    • Liwei Deng, Yuanzhi Zhang, Xin Yang, et al. Meta-learning Multi-scale Radiology Medical Image Superresolution[J].CMC-Computers, Materials & Continua.2023,75(2) :2671-2684.（WOS:000980836000018）
    • Liwei Deng, Yuanzhi Zhang, Jing Wang, et al. Improving Performance of Medical Image Alignment through Super-resolution[J].Biomedical Engineering Letters.2023.（WOS:000934806000001）
    • LiweiDeng ,Mingxing Zhang , JingWang, et al.Improving Cone-Beam Ct Quality Using a Cycle-Residual Connection with a Dilated Convolution-Consistent Generative Adversarial Network[J]. Physics in Medicine & Biology, 2022,67(14): 145010.（WOS:000822102200001）
    • Liwei Deng, Jie Hu, Jing Wang, et al.Synthetic CT Generation Based on CBCT Using Respath-cycleGAN[J]. Medical Physics, 2022,49(8): 5317-5329.（WOS:000792418600001）
    • Zhe Yan, Shuchun Chu, Liwei Deng. Visual SLAM Based on Instance Segmentation in Dynamic Scenes[J]. Measurement Science and Technology.2021,32(9):095113.（WOS:000662668300001）

    Conference Papers

    • Liwei Deng*, Yuanzhi Zhang, Xiaofei Wang. High-definition Processing of Remote Sensing Images Based on CUT-CycleGAN[C], The 40th Chinese Control Conference, CCC 2021.( EI：20214311045982).
    • Liwei Deng*, YueWang, Jing Han. Optical Disc Location Based on Similarity toImproved Harris Algorithm[C], The 40th Chinese Control Conference, CCC 2021.( EI：20214311046402).
    • Liwei Deng*, Hongfei Suo, Haonan Ren. Research on Tension Control System of Winding Machine Based on Fuzzy PID Algorithm[C], The 40th Chinese Control Conference, CCC 2021.( EI：20214311045650).
    • Yuheng Yin, Yangang Guo, Liwei Deng*. Research on Image Processing Application of Improved Adaptive Filter Based on LPSO Algorithm[C], The 40th Chinese Control Conference, CCC 2021.( EI：20214311045948).
    • Yanshu Jiang, Mingqi Jia, Biao Zhang, Liwei Deng. Malicious Domain Name Detection Model Based on CNN-GRU-Attention[C], The 33rd Chinese Control and Decision Conference, CCDC 2021.
    • Liwei Deng, Xiaofei Wang.A New Fracture Image Segmentation Method Based on MSA-k Clustering Algorithm[C], The 39th Chinese Control Conference, CCC 2020.( EI：20203909242340).
    • Liwei Deng,Jie Hu,Jingjing Qi. Super-Resolution Reconstruction of Finger Vein Image Based on Regression Tree Model[C],The 32nd Chinese Control and Decision Conference, CCDC 2020.( EI：20204009254996).

Changwei Wu – Network Properties- Best Researcher Award

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Changwei  Wu – Network Properties

Prof.  Changwei W.Wu distinguished academic and researcher in the field Network Properties.  Changwei W. Wu, a Professor at the Graduate Institute of Mind, Brain, and Consciousness at Taipei Medical University – Shuang-Ho campus in New Taipei, Taiwan, is also affiliated with the Research Center of Sleep Medicine at Taipei Medical University Hospital. He specializes in Mindfulness-based Interventions (MBI) and conducts research on simultaneous EEG-fMRI for sleep neuroimaging. Additionally, he is proficient in medical image and signal processing.

 

🌐 Professional Profiles

Educations📚📚📚

He  holds a Ph.D. in Electrical Engineering from National Taiwan University, Taipei, Taiwan, awarded in January 2009. His doctoral dissertation, titled “Biophysical Investigations and Developments of Novel Functional MRI Techniques,” was supervised by Jyh-Horng Chen, Ph.D., and Ho-Ling Liu, Ph.D. During his doctoral studies, he also served as a Predoctoral Visiting Fellow at the Neuroimaging Branch of the National Institute on Drug Abuse, National Institutes of Health (NIDA/NIH), in Baltimore, MD, from March 2006 to April 2008, under the supervision of Dr. Yihong Yang. Dr. Wu obtained his B.Eng. in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 2001.

 

Academic Positions:

Dr. Changwei W. Wu has held various academic positions, demonstrating a strong commitment to research and teaching in the field of neuroscience and related disciplines:

  • Professor, Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei, Taiwan (Feb 2021 – Present)
  • Associate Professor, Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei, Taiwan (Aug 2019 – Jan 2021)
  • Associate Professor, Graduate Institute of Humanities in Medicine, Taipei Medical University, Taipei, Taiwan (Aug 2016 – Jul 2019)
  • Adjunct Associate Professor, Department of Biomedical Sciences and Engineering, National Central University, Taoyuan, Taiwan (Sep 2016 – Jul 2019)
  • Adjunct Associate Professor, Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan (Aug 2015 – Jul 2016)
  • Associate Professor, Department of Biomedical Sciences and Engineering, National Central University, Taoyuan, Taiwan (Aug 2015 – Jul 2016)
  • Adjunct Assistant Professor, Brain and Consciousness Research Center, Taipei Medical University, Taipei, Taiwan (Sep 2014 – Jul 2016)
  • Assistant Professor, Graduate Institute of Biomedical Engineering, National Central University, Taoyuan, Taiwan (Aug 2011 – Jul 2015)
  • Postdoc Research Fellow, Neuroimaging Branch, National Institute on Drug Abuse, National Institutes of Health (NIDA/NIH), Baltimore, MD, where he conducted research on spectral analyses of functional connectivity in cocaine users using simultaneous EEG/fMRI recordings.

Honors & Awards

Dr. Changwei W. Wu has garnered several esteemed awards and accolades in recognition of his outstanding contributions to teaching, research, and academic excellence. Notably, he received the Outstanding Teaching Award from the Center of General Education at Taipei Medical University, Taipei, Taiwan, in 2023. In 2020, he was honored with the JMBE Annual Excellent Paper Award by the Taiwanese Society of Biomedical Engineering, as well as the College Student Research Creativity Award from the Ministry of Science and Technology (MOST), Taiwan. Additionally, he was recognized with the Outstanding Teaching Award from the College of Humanities and Social Science at Taipei Medical University, Taipei, Taiwan, and received the Award of Research Program Projects Grant from Taipei Medical University, Taipei, Taiwan, all in the same year. These accolades underscore Dr. Wu’s dedication to advancing education, fostering innovative research, and contributing significantly to his field.

Publication
1. Yi-Chia Kung, Chia-Wei Li, Ai-Ling Hsu*, Chi-Yun Liu, Changwei W. Wu*, WeiChou Chang, Ching-Po Lin*. Neurovascular Coupling in Resting State and EyeOpen-Eye-Close Task: Spectral Correspondence between Concurrent EEG and fMRI. Neuroimage (In press).
2. Hong-Yi Wu, Chih-Mao Huang, Ai-Ling Hsu, Chiao-Nan Chen, Changwei W. Wu*,
Jyh-Horng Chen*. Functional Neuroplasticity of Facilitation and Interference
Effects on Inhibitory Control Following 3-month Physical Exercise in Aging.
Scientific Reports (In press).
3. Timothy J. Lane, Tsan-Hon Liou, Yi-Chia Kung, Philip Tseng*, Changwei W. Wu*.
Functional Blindsight and Its Diagnosis. Frontiers in Neurology 2024; 15:
1207115. doi: 10.3389/fneur.2024.1207115
4. Zhitong John Wang, Hsin-Chien Lee, Chun-Hsiang Chuang, Fan-Chi Hsiao, ShwuHua Lee, Ai-Ling Hsu*, Changwei W. Wu*. Traces of EEG-fMRI Coupling Reveals
Neurovascular Dynamics on Sleep Inertia. Scientific Reports 2024; 14: 1537.
doi: 10.1038/s41598-024-51694-4
5. Yi-Tien Li, Duen-Pang Kuo, Philip Tseng, Yung-Chieh Chen, Sho-Jen Cheng,
Changwei W. Wu, Li-Chun Hsieh, Yung-Hsiao Chiang, Hsiao-Wen Chung,
Yvonne W. Lui, Cheng-Yu Chen*. Thalamocortical Coherence Predicts Persistent
Postconcussive Symptoms. Progress in Neurobiology. 2023; 226: 102464. doi:
10.1016/j.pneurobio.2023.102464
6. Ai-Ling Hsu, Ming-Kang Li, Yi-Chia Kung, John Wang, Hsin-Chien Lee, Chia-Wei
Li, Chi-Wen Huang* and Changwei W. Wu*. Temporal Consistency of
Neurovascular Components on Awakening: Preliminary Evidence from
electroencephalography, cerebrovascular reactivity, and functional magnetic
resonance imaging. Frontiers in Psychiatry 2023; 14: 1058721. doi:
10.3389/fpsyt.2023.1058721
7. Shiao-Fei Guu, Yi-Ping Chao, Feng-Ying Huang, Yu-Ting Jeng, Hei-Yin Hydra Ng,
Chia-Fen Hsu, Chun-Hsiang Chuang, Chih-Mao Huang*, Changwei W. Wu*.
Interoceptive Awareness: MBSR Training Alters Information Processing of
Salience Network. Frontiers in Behavioral Neuroscience 2023; 17:1008086.
doi: 10.3389/fnbeh.2023.1008086
8. Shaoyu Yen, Hong-Yi Wu, Yuhling Wang, Chih-Mao Huang, Changwei W. Wu,
Jyh-Horng Chen, and Lun-De Liao*. Revisiting the Effects of Exercise on Cerebral
Neurovascular Functions in Rats using Multimodal Assessment Techniques.
iScience 2023; 26(4): 106354. doi: 10.1016/j.isci.2023.106354
9. Hei-Yin Hydra Ng; Changwei W. Wu; Feng-Ying Huang; Chih-Mao Huang; ChiaFen Hsu; Yi-Ping Chao*; Tzyy-Ping Jung; Chun-Hsiang Chuang*. Enhanced
Electroencephalography Effective Connectivity in Frontal Low-Gamma Band
Correlates of Emotional Regulation after Mindfulness Training. Journal of
Neuroscience Research 2023; 101(6): 901-915. doi: 10.1002/jnr.25168
10. Deng-Fa Yang, Wen-Ching Huang, Changwei W. Wu, Yu-Chen S. H. Yang, YuTang Tung*. Acute sleep deprivation exacerbates systemic inflammation and
psychiatry disorders through gut microbiota dysbiosis and disruption of circadian
rhythms. Microbiological Research 2023; 268: 127292. doi:
10.1016/j.micres.2022.127292
11. Mengxia Gao, Nichol M.L. Wong, Chemin Lin, Chih-Mao Huang, Ho-Ling Liu,
Cheng-Hong Toh, Changwei Wu, Yun-Fang Tsai, Shwu-Hua Lee*, Tatia M.C.
Lee*. Multimodal Brain Connectome-based Prediction of Suicide Risk in People
with Late-life Depression. Nature Mental Health 2023; 1: 100–113. doi:
10.1038/s44220-022-00007-7
12. Pei-Ying Sarah Chan, Wen-Pin Chang, Chia-Hsiung Cheng, Liu Chia-Yih, Ai-Ling
Hsu*, Andreas von Leupoldt, Changwei Wu*. The Impact of Emotional Context
on Neural Substrates of Respiratory Sensory Gating. Frontiers in Neuroscience
2022; 16:1004271. doi: 10.3389/fnins.2022.1004271
13. Yi-Chia Kung, Chia-Wei Li, Fan-Chi Hsiao, Pei-Jung Tsai, Shuo Chen, Ming-Kang
Li, Hsin-Chien Lee, Chun-Yen Chang, Changwei W. Wu*, Ching-Po Lin*. Crossscale Dynamicity of Entropy and Connectivity in the Sleeping Brain. Brain
Connectivity 2022; 12(9): 835-845. doi: 10.1089/brain.2021.0174
14. Hsuan-Chu Shih, Mu-En Kuo, Changwei W. Wu, Yi-Ping Chao, Hsu-Wen Huang,
Chih-Mao Huang*. The Neurobiological Basis of Love: A Meta-Analysis of Human
Functional Neuroimaging Studies of Maternal and Passionate Love. Brain
Sciences 2022; 12(7): 830. doi: 10.3390/brainsci12070830
15. Hang Wu, Zengxin Qi, Xuehai Wu, Jun Zhang, Changwei Wu, Zirui Huang, Di
Zang, Stuart Fogel, Sean Tanabe, Anthony G. Hudetz, Georg Northoff, Ying Mao*,

Xin Li – Random Graph Models

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Dr. Xin Li  – Leading Researcher in Random Graph Models

 

Assist Prof Dr. Xin Li has held the position of Associate Professor in the School of Mechanical and Electrical Engineering at China University of Mining and Technology. Concurrently, since March 2023, he has also taken on the role of Postdoc Researcher at Zhejiang University and China University of Mining and Technology within the School of Mechanical Engineering. This dual academic engagement underscores his commitment to advancing research and contributing to the academic communities at both institutions.

Education📚

📚 Embarking on an academic journey, he pursued his passion for Mechanical Engineering at Qingdao University of Technology, earning a Bachelor of Arts degree from the School of Mechanical Engineering in the period spanning September 2012 to July 2016. Building upon this foundation, he delved deeper into the intricacies of the field at Hunan University, where he successfully completed his Ph.D. in Mechanical Engineering within the College of Mechanical and Vehicle Engineering from September 2016 to July 2022. This educational odyssey reflects his steadfast dedication to scholarly pursuits and the continual pursuit of knowledge. 🎓

 

Professional Profiles:

RESEARCH INTERESTS

Random Graph Models; Intelligent fault diagnosis; Machine learning; Complex systems🌞

EDITORIAL BOARD
Journal of Dynamics, Monitoring and Diagnostics
Frontiers in Mechanical Engineering

AWARDS

🏆 In recognition of his outstanding contributions to academia and research, he has been honored with a series of prestigious grants and awards. Notably, he secured the National Social Science Foundation Youth Project (62206298) for the period 2022-2025, demonstrating his prowess in the field. Further bolstering his research endeavors, he received support from the Fundamental Research Funds for the Central Universities (20230N1048) in 2023-2024. His commitment to advancing scientific knowledge is also evident through grants from the China Postdoctoral Science Foundation and the Postdoctoral Science Foundation of Zhejiang Province for the years 2023-2025. In addition, he has been recognized by the Natural Science Foundation of Jiangsu Province for the period 2023-2026, solidifying his position as a respected researcher. The accolades continue with the acknowledgment of his contributions to the academic community through the China University of Mining and Technology’s “Sailing Plan” for Young Teachers (102523236) in 2023-2024, as well as the Hunan Graduate Research Innovation Project (CX20200406) for the academic year 2021-2022. These accolades underscore his dedication and success in pushing the boundaries of knowledge in his field. 🌟

TEACHING EXPERIENCE

2023 Spring Engineering Measurement Technology
2022 Autumn Equipment health management and intelligent O&M (Graduate)

SELECTED PUBLICATIONS

Li X, Yang Y, Wu Z, et al. High-accuracy gearbox health state recognition based on graph sparse
random vector functional link network[J]. Reliability Engineering & System Safety, 2021:
108187.
Li X, Li S, Wei D, Si L, Yu K, Yan K. Dynamics Simulation-driven Fault Diagnosis of Rolling
Bearings Using Security Transfer Support Matrix Machine. Reliability Engineering & System
Safety. 2023:109882.
Li X, Cheng J, Shao H, et al. A Fusion CWSMM-based Framework for Rotating Machinery
Fault Diagnosis under Strong Interference and Imbalanced Case[J]. IEEE Transactions on
Industrial Informatics, 2021, 18(8): 5180-5189.
Li X, Shao H, Lu S, et al. Highly-efficient fault diagnosis of rotating machinery under timevarying speeds using LSISMM and small infrared thermal images[J]. IEEE Transactions on
Systems, Man and Cybernetics: Systems, 2022, 52(12): 7328-7340.

Symplectic geometry packet decomposition and its applications to gear fault diagnosis

J Cheng, Y Yang, X Li, J Cheng
Mechanical Systems and Signal Processing 174, 109096