Distributed compilation
Qubit mapping, circuit transformation, Telegate and Teledata scheduling, and dependency-aware execution across capacity-constrained QPUs.
Research
Reliable quantum computing, distributed by design.
My research centers on distributed and fault-tolerant quantum computing. I study how logical operations, error correction, entanglement supply, communication, and constrained hardware resources interact when quantum workloads span multiple processors.
Fault-tolerant architectures
Surface-code-based computation, logical operations, magic-state factories, buffers, and QEC-aware allocation and scheduling.
Entanglement & reliability
End-to-end models spanning generation, purification, encoding, QEC, storage aging, and remote logical execution.
Quantum networking
Photonic interconnects, scalable switching and routing, communication-aware resource management, and performance modeling.
Selected work
Publications
Resource Allocation for Distributed Fault-Tolerant Quantum Computing with Surface Codes
Labubu: Layer-Buffered Bundled Optimization for Efficient Remote Gate Scheduling in Distributed Quantum Computing
Remote Gate Scheduling in Distributed Quantum Computing
Joint Optimization of Circuit Transformation and Qubit Mapping for Distributed Quantum Computing
A Nonblocking Multistage Switching Network for Distributed Quantum Computing
Performance Analysis of Interconnection Networks for Distributed Quantum Computing
Background
Research & teaching
Graduate Research Assistant
High Performance Computing and Networking Research Laboratory · Stony Brook UniversityAdvisor: Prof. Yuanyuan Yang. Research in distributed quantum systems, fault-tolerant architectures, compilation, scheduling, resource allocation, and quantum interconnects.
Teaching Assistant
Stony Brook UniversityESE 333 Real-Time Operating Systems, ESE 123 Introduction to Electrical and Computer Engineering, and ESE 272 Electronics.
Researcher — Computer Vision & Medical Imaging
Nanjing UniversityDeveloped and evaluated CNN-, ResNet-, and Transformer-based breast-ultrasound classification pipelines using Python and PyTorch.
Methods
Technical toolkit
PythonQiskitQiskit AerPennyLaneGurobiNumPySciPyPyTorchMonte Carlo simulationInteger programmingQuantum error correctionSurface codesStabilizer methodsGitLaTeX
Contact
Let’s connect.
I am interested in research collaborations and opportunities in distributed quantum computing, fault-tolerant systems, quantum networking, compilation, and architecture.