I am a Research Fellow at the Singapore University of Technology and Design (SUTD), working with Prof. Jihong Park. My work bridges theory and implementation in wireless networking systems — from algorithm design to real-time prototyping on programmable hardware.
"Making wireless networks smarter through graph learning, reinforcement learning, and AI-native protocol design."
- 📍 Location: Singapore
- 🎓 Ph.D. in Engineering, The University of Sydney (2023)
- 🔬 Research Fellow @ SUTD since Nov 2024
- 🏆 Best Student Paper Award, AAAI 2026 ML4Wireless Workshop (for LocDreamer)
- 🤝 Industry collaborations: NVIDIA, Morse Micro, Telstra
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| Year | Title | Venue |
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| 2026 | Duality-Guided Graph Learning for Real-Time Joint Connectivity and Routing in LEO Mega-Constellations | arXiv preprint |
| 2026 | Joint Laser Inter-Satellite Link Matching and Traffic Flow Routing in LEO Mega-Constellations via Lagrangian Duality | arXiv preprint |
| 2026 | Reinforcement Learning for Opportunistic Routing in Software-Defined LEO-Terrestrial Systems | IEEE Wireless Commun. Letters |
| 2025 | Scalable Interference Graph Learning for Low-Latency Wi-Fi Networks using Hashing-based Evolution Strategy | arXiv preprint |
| 2025 | SIG-SDP: Sparse Interference Graph-Aided Semidefinite Programming for Large-Scale Wireless TSN | arXiv preprint |
| 2024 | Opportunistic Scheduling Using Statistical Information of Wireless Channels | IEEE Trans. Wireless Commun. |
| 2024 | Graph Representation Learning for Contention and Interference Management in Wireless Networks | IEEE/ACM Trans. Networking |
| 2021 | Knowledge-Assisted Deep Reinforcement Learning in 5G Scheduler Design | IEEE JSAC |
📖 Full list on Google Scholar | Personal Website
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Live demo for LEO mega-constellation digital twin research. Visualizes large-scale satellite connectivity dynamics in real time.
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Scalable neural graph modeling for Wi-Fi 7 contention and interference management.
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Sparse interference graph-aided semidefinite programming for large-scale wireless time-sensitive networking.
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Knowledge-assisted deep reinforcement learning scheduler for 5G RAN (IEEE JSAC 2021).
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Graph representation learning for contention and interference management in wireless networks (IEEE/ACM Trans. Networking 2024).
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NS-3 simulation codes for the graph representation learning paper on contention and interference management (IEEE/ACM Trans. Networking 2024).
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- 🥇 Best Student Paper Award — AAAI 2026 Workshop on ML for Wireless Communication and Networks (LocDreamer)
- 🎖️ NVIDIA Academic Grant Program (2025)
- 🎓 Postgraduate Completion Scholarship, The University of Sydney (2022)
- 🏅 Australian Research Training Program Stipend (2019)
Technical Program Committee: WCNC 2026 · ICCC 2025 · VTC2026-Spring · VTC2026-Fall
Reviewer: IEEE TWC · IEEE TMC · IEEE TCOMM · IEEE JSAC · IEEE IoTJ · IEEE Network · INFOCOM · GLOBECOM · WCNC