The Wireless Intelligent Networks (WIN) Lab at Santa Clara University explores next-generation wireless systems that adapt, learn, and make intelligent decisions — with a focus on efficient resource allocation, smarter access protocols, and user-centered performance.
We focus on technologies like WiFi 7, 5G/6G, and intelligent multiple access protocols—including NOMA, RSMA, and 6TiSCH — alongside research in QoE/QoS optimization, machine learning techniques in wireless network, network economics, wireless multimedia and cognitive radio.
Whether you’re passionate about future wireless networks, curious about how machine learning can shape next gen communications, or eager to build real-world impact through research — the WIN Lab is a collaborative space where your ideas matter, your growth is supported, and your work can shape the networks of tomorrow.
- 🎯 NOMA for 6G Cellular Networks: Designing user-focused algorithms to enhance Quality of Experience (QoE) and fairness in non-orthogonal multiple access networks, leveraging machine learning and game theory.
- 🎯 Multi-Link WiFi 7 for Intelligent LANs: Exploring Multi-Link Operation (MLO) for smarter traffic steering across bands and interfaces to achieve ultra-low latency and high throughput in wireless LANs.
- 🎯 MAC-Layer Optimization for 6TiSCH IoT Networks: Developing distributed game-theoretic algorithms at the MAC layer to enhance scheduling efficiency, reduce energy consumption, and improve reliability in low-power industrial IoT networks built on the 6TiSCH protocol.
- 🎯 RSMA for Next-Gen Spectrum Sharing: Exploring rate-splitting multiple access as a flexible and interference-aware access strategy for multi-user wireless systems, enabling improved spectral efficiency, user fairness, and adaptability under diverse QoS demands.
Undergraduate Students:
Graduate Students:
Ph.D. Students: I’m looking to welcome kind, curious, and self-driven Ph.D. students to join the WIN Lab. If you’re passionate about wireless networks, protocols for 6G, machine learning for networks, or network economics, feel free to email me with your CV and research interests.
M.S. Students: If you’re interested in completing a master’s thesis or working on directed research under my supervision, I’d love to hear from you. RA positions are offered based on performance in prior research, typically through a directed research pathway.
Undergraduate Students: Curious minds are always welcome! If you're excited to explore research, build real-world systems, or dive into wireless and IoT innovations, drop by my office or send a quick note. No prior research experience is required—just enthusiasm and a willingness to learn.