Introduction
Hello, my name is Sihao(Leo) Li. I am a PhD candidate with a passion for wireless sensor networks and Wi-Fi fingerprint indoor localization. With three years of experience in indoor localization, I have developed a deep understanding and expertise in Wi-Fi fingerprint based indoor positioning and navigation.
Throughout my career, I have had the opportunity to work on various projects and collaborate with talented individuals, which has enriched my skills and broadened my perspectives. I am constantly seeking new challenges and opportunities to expand my knowledge and contribute to innovative solutions.
My areas of expertise include [Wireless Sensor Networks, Unslotted CSMA in IEEE 802.15.4, Optimal Message Bundling, and COOJA Simu/Emulator]. Moreover, I am proficient in [Python Programming for Neural Networks] and have a strong understanding of [LaTex Paper Writing].
In addition to my technical skills, I am a strong communicator and enjoy working in collaborative environments. I believe in the power of teamwork and effective communication to drive successful outcomes.
I am excited to share my knowledge and experiences through this blog, where I will be discussing topics related to [Xi’an Jiaotong Liverpool University & Liverpool University MSc CAN 406/403 courses resources, Semi-Supervised Learning, and COOJA Simu/Emulator]. I hope you find my articles informative and engaging.
Thank you for visiting my blog and joining me on this journey of exploration and learning.
If you have any ideas or questions, please e-mail me at: leoworkspace@163.com.
Award & Publications
Sihao Li, Zhe Tang, Kyeong Soo Kim, and Jeremy Smith, “Exploiting unlabeled RSSI fingerprints in multi-building and multi-floor indoor localization through deep semi-supervised learning based on mean teacher,” awarded the “Best/Outstanding Paper Award” by CANDAR, Oct. 2023.
Sihao Li, Kyeong Soo Kim, Zhe Tang, and Jeremy Smith, “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,” International Workshop on GPU Computing and AI (CANDARW/GCA), Sep. 2023.
Sihao Li, Zhe Tang, Kyeong Soo Kim, and Jeremy Smith, “Exploiting unlabeled RSSI fingerprints in multi-building and multi-floor indoor localization through deep semi-supervised learning based on mean teacher,” International Symposium on Computing and Networking (CANDAR) 2023, Sep. 2023.
Sihao Li, Kyeong Soo Kim, Linlin Zhang, Xintao Huan, and Jeremy Smith, “Energy-efficient message bundling with delay and synchronization constraints in wireless sensor networks,” MDPI Sensors, Jul. 2022.
Zhe Tang, Ruocheng Gu, Sihao Li, Kyeong Soo Kim, and Jeremy Smith, “Static vs. dynamic databases for indoor localization based on Wi-Fi fingerprinting: A discussion from a data perspective,” International Conference on Artificial Intelligence in Information and Communication (ICAIIC) as an invited paper, Dec. 2023.
Zhe Tang, Sihao Li, Kyeong Soo Kim, and Jeremy Smith, “On the multi-dimensional augmentation of fingerprint data for indoor localization in a large-scale building complex based on multi-output Gaussian processes,” MDPI Sensors, Dec 2023.
Zhe Tang, Sihao Li, Kyeong Soo Kim, and Jeremy Smith, “Multi-output Gaussian process-based data augmentation for multi-building and multi-floor indoor localization,” IEEE International Conference on Communications Workshop, May 2022.
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