About Me

👋 Hi there! I’m Ziming Dai (戴子明), a second-year Master’s student in the College of Intelligence and Computing at Tianjin University 🇨🇳. I currently conduct research at the Edge Big Bang Lab, under the supervision of Prof. Xiaofei Wang and Prof. Chao Qiu.

🎓 I received my Bachelor of Engineering in Artificial Intelligence from Tianjin University in 2019–2023, where my undergraduate thesis on blockchain-based group federated learning was awarded as an Outstanding Graduation Thesis. Currently, I am pursuing my Master of Engineering in Electronic and Information Engineering at the same institution, expected to graduate in 2026.

💼 In the summer of 2022, I interned as an Algorithm Engineer at Beijing Wenge Technology Co., Ltd., where I joint a team focused on Named Entity Recognition (NER) in low-resource languages, coordinating efforts across model pretraining and linguistic enhancement modules.

💡 My research centers on federated learning, edge intelligence, and large language model (LLM) personalization. I’m especially interested in enabling LLMs to adapt to local contexts by efficiently leveraging private data in decentralized, resource-constrained environments.

⚙️ I aim to build intelligent systems that are not only powerful but also deployable in real-world edge scenarios, particularly where privacy and energy efficiency are essential.

🔍 Research Interests

• ⚡ Federated & Edge Learning Systems
• 🤖 Customization and Distillation of LLMs
• 🔐 Privacy-Preserving AI
• 🌱 Green AI & Efficient Model Deployment

🚀 I’m currently exploring how to combine LLMs with edge devices through distributed learning and distillation — making intelligence more personal, private, and practical.

📄 You can view or download my latest CV here:
👉 CV_ZimingDai.pdf

🛠 Feel free to check out my blog, or reach out if you’d like to connect!