Dikun Hu | Psychophysiological Computing | Best Researcher Award

Dr. Dikun Hu | Psychophysiological Computing | Best Researcher Award

Student | Institute for Beijing University of Posts and Telecommunications (BUPT) | China

Short Biography 🌟

Diku Hu, a dedicated researcher and academic, is a prominent figure in the field of Information and Communication Engineering. Born on September 29, 1992, in China, Diku Hu has made significant strides in the study of biomedical signal processing and psychophysiological computing. Currently pursuing his PhD at Beijing University of Posts and Telecommunications (BUPT), Hu’s research focuses on innovative algorithms for sleep health monitoring using piezoelectric ceramic sensor arrays. His work is not only advancing the boundaries of health data analysis but also contributing to the broader understanding of multi-source physiological data integration. With a background that spans across undergraduate, master’s, and doctoral studies, Hu has consistently demonstrated his commitment to enhancing healthcare technologies through rigorous research and academic excellence. For more information.

Profile

ORCID

Education 🎓

Diku Hu’s educational journey reflects a strong commitment to advancing knowledge in the field of Information and Communication Engineering. He embarked on his doctoral studies at Beijing University of Posts and Telecommunications (BUPT) in September 2020, focusing on the signal processing and analysis methods of health data in the biomedical domain. His research emphasizes the development of novel algorithms for sleep health monitoring using piezoelectric ceramic sensor arrays, marking a significant contribution to the field. Prior to his PhD, Hu completed his Master’s degree at BUPT from September 2017 to June 2020, where he explored intelligent sleep staging methods based on BCG signals from micro-motion mattresses. His academic foundation was further established during his undergraduate studies at XiDian University (XDU) from September 2011 to June 2015, where he pursued a major in Information and Communication Engineering. This comprehensive educational background has equipped Hu with the theoretical knowledge and practical skills essential for his research and professional endeavors.

Work Experience 💼

Diku Hu’s professional experience includes a notable role at the Hubei Unicom Operation and Maintenance Department, where he worked from September 2015 to March 2016. During this period, Hu was involved in various operational and maintenance tasks related to telecommunications. This experience provided him with practical insights into the challenges and intricacies of managing and maintaining communication infrastructure. It also offered him a valuable perspective on the application of engineering principles in real-world scenarios. This hands-on experience has been instrumental in shaping his research approach and understanding of the technological landscape, complementing his academic achievements and research interests.

Research Interest 🔬

Diku Hu’s research interests are deeply rooted in the intersection of biomedical signal processing and psychophysiological computing. His work is centered on the analysis and mining of multi-source physiological data to improve health monitoring systems. A significant focus of his research is on developing advanced algorithms for sleep health monitoring using piezoelectric ceramic sensors. This involves quantifying, fusing, and analyzing physiological data to enhance the accuracy and effectiveness of health monitoring technologies. Hu’s research also extends to psychophysiological computing, where he investigates the integration of physiological data to better understand and address health-related issues. His contributions in these areas are paving the way for innovations in health technology and improving the quality of life through enhanced data analysis techniques.

Awards 🏆

Diku Hu has been recognized for his outstanding academic performance with several prestigious awards. He received the First-Class Scholarship at Beijing University of Posts and Telecommunications (BUPT) for the academic year 2017/2018, acknowledging his exceptional achievements during his Master’s studies. Additionally, he was awarded the Second-Class Scholarship for the academic years 2019/2020 and 2020/2021, reflecting his continued excellence and dedication throughout his academic career. These scholarships are a testament to Hu’s commitment to his studies and his contributions to the field of Information and Communication Engineering.

Publications 📚

Diku Hu has made significant contributions to the academic community through his research publications. His notable works include:

  1. Research on Evaluation Norms of Human Health Status, China Medicine and Pharmacy, 2022, 12(20): 7-29. This paper explores evaluation norms for human health, contributing valuable insights into health status assessment.
  2. Cross Domain Based Deep Neural Network for Obstructive Sleep Apnea Detection via Piezoelectric Ceramic Sensor Array, SMC 2023. This research presents an advanced deep neural network approach for detecting obstructive sleep apnea using piezoelectric ceramic sensors.
  3. Smart Sleep Monitoring: Sparse Sensor-Based Spatiotemporal CNN for Sleep Posture Detection, Sensors, 2024, 24, 4833. The paper discusses a novel spatiotemporal convolutional network for detecting sleep posture using sparse sensors.
  4. STConvSleepNet: A Spatiotemporal Convolutional Network for Sleep Posture Detection, EMBC 2024. This publication introduces STConvSleepNet, a new network for sleep posture detection.
  5. Piezoelectric Ceramic Sensor Array Based Obstructive Sleep Apnea Event Detection, IEEE Journal of Biomedical and Health Informatics (submitted). This study focuses on detecting obstructive sleep apnea events using piezoelectric sensors.
  6. A Non-Iterative SGTM-based Cascade Structure with Nonlinear Input Extension for IoMT Data Analysis, IEEE Transactions on Neural Networks and Learning Systems (submitted). This paper presents a non-iterative cascade structure for analyzing IoMT data.