Introduction
Leo Li
Mr. Li received his Dr. degree in Electrical and Electronic Engineering at the University of Liverpool, UK, under the supervision of Prof. Kyeong Soo Kim and Dr. Jeremy Smith, in 2025. He obtained his MSc degree in Communications and Networking from Xi’an Jiaotong-Liverpool University (XJTLU), China, in 2021, where he was supervised by Prof. Kyeong Soo Kim.
Research Focus
Research is concentrated in the areas of wireless sensor networks and Wi-Fi fingerprint-based indoor localization. Over three years of specialized investigation in the field of indoor positioning have been dedicated, resulting in a deepened understanding and expertise in methodologies based on Wi-Fi fingerprinting for indoor navigation.
Professional Experience
Multiple research projects have been undertaken, and collaborations have been established with distinguished researchers. These experiences have been utilized to enhance technical capacities and broaden academic perspectives. New challenges are continually sought to facilitate the expansion of knowledge and to contribute to the development of innovative solutions.
Areas of Specialization
- Core Research Domains: Wireless Sensor Networks, Unslotted CSMA as defined in the IEEE 802.15.4 standard, and Optimal Message Bundling.
- Technical Proficiencies: The COOJA Simulator/Emulator is utilized for network simulations, Python is employed for programming neural networks, and scholarly documents are prepared using LaTeX.
Professional Attributes
Effective communication skills are possessed, and collaborative research environments are favored. It is firmly believed that successful outcomes in research are driven by teamwork and clear communication.
Blog Purpose
This platform is intended for the dissemination of knowledge and resources pertaining to specific academic courses and research topics. Topics related to 1) the MSc CAN 406/403 modules offered by Xi’an Jiaotong-Liverpool University and the University of Liverpool, 2) Semi-Supervised Learning, and 3) the COOJA Simulator will be discussed herein. The articles are hoped to be regarded as informative and to stimulate academic discourse.
Your visit to this blog is appreciated. A shared journey of academic exploration is anticipated.
Award & Publications
| Title | Publication | Year |
|---|---|---|
| Multi-output Gaussian process-based data augmentation for multi-building and multi-floor indoor localization | IEEE ICC Workshops | 2022 |
| Energy-efficient message bundling with delay and synchronization constraints in wireless sensor networks | Sensors | 2022 |
| On the Multidimensional Augmentation of Fingerprint Data for Indoor Localization in A Large-Scale Building Complex Based on Multi-Output Gaussian Process | arXiv:2211.10642 | 2022 |
| Stage-Wise and Hierarchical Training of Linked Deep Neural Networks for Large-Scale Multi-Building and Multi-Floor Indoor Localization Based on Wi-Fi Fingerprinting | Eleventh CANDARW | 2023 |
| Exploiting unlabeled RSSI fingerprints in multi-building and multi-floor indoor localization through deep semi-supervised learning based on mean teacher | Eleventh CANDAR | 2023 |
| Multi-Dimensional Wi-Fi Received Signal Strength Indicator Data Augmentation Based on Multi-Output Gaussian Process for Large-Scale Indoor Localization | Sensors | 2024 |
| Static vs. dynamic databases for indoor localization based on Wi-Fi fingerprinting: A discussion from a data perspective | ICAIIC | 2024 |
| On the use and construction of wi-fi fingerprint databases for large-scale multi-building and multi-floor indoor localization: A case study of the UJIIndoorLoc database | Sensors | 2024 |
| Hierarchical Stage-Wise Training of Linked Deep Neural Networks for Multi-Building and Multi-Floor Indoor Localization Based on Wi-Fi RSSI Fingerprinting | IEEE Sensors Journal | 2024 |
| SGP-RI: A Real-Time-Trainable and Decentralized IoT Indoor Localization Model Based on Sparse Gaussian Process with Reduced-Dimensional Inputs | arXiv:2409.00078 | 2024 |
| AGV-Assisted Construction of Dynamic Wi-Fi Fingerprint Databases for Indoor Localization | Twelfth CANDARW | 2024 |
| Mean Teacher based SSL Framework for Indoor Localization Using Wi-Fi RSSI Fingerprinting | arXiv:2407.13303 | 2024 |
Friend Links
- My PhD Supervisors:
- My friends:
Leo
烟雨化桥常相念，塞上门楼空许约。
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