Chao Lian Editor at IgMin Research
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Biography
Dr. Lian Chao is currently a research assistant at Northeastern University, and both his master's and doctoral degrees are studying at Northeastern University. His research interests include wearable devices, smart sensors, intelligent detection, human activity recognition (HAR), data mining, deep learning, etc. He has published more than 20 SCI papers in internationally renowned journals such as Advanced Intelligent Systems, IEEE Transactions on Instrumentation and Measurement, IEEE Sensors Journal, etc. He has served as a reviewer for several journals such as IEEE Sensors Journal, Sensors, International Journal of Sensors and Sensor Networks. He also has participated in the review of some important academic conferences, such as CVVR2023, MEAAC2023, etc.
Research Interest
Wearable devices, Smart sensors, Intelligent detection, Human activity recognition (HAR), Data mining, Deep learning
Editor
Work Details
Research Assistant
Northeast University
School of Information Science and Engineering
China
Contribution by Topic Area
Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Adaptation of the Physical Literacy Scale for Adults into Turkish and Examination of its Psychometric Properties
- Prevalence of Diabetic Retinopathy among Self-reported Newly Diagnosed Diabetics
- The Impact of Stress on Periodontal Health: A Biomarker-Based Review of Current Evidence
- Contribution to the Knowledge of Ground Beetles (Coleoptera: Carabidae) from Pakistan
- Unveiling the Hidden Beat: Heart Rate Variability and the Vagus Nerve as an Emerging Biomarker in Breast Cancer Management
- From Traditionalism to Algorithms: Embracing Artificial Intelligence for Effective University Teaching and Learning
