01
Domain-Level Optimization
Hamiltonian-level compilation (HATT), constant-depth
TFIM circuits, and application-specific simulation
circuit generation.
02
Gate-Set Independent Optimization
Hardware-agnostic transpilation, scalable synthesis
(QSearch ≤4q, LEAP ≤6q, QFAST ≤8q, QGO to 60+
qubits), routing & mapping, classical optimizers
for NISQ/VQE.
03
AI-Driven Scalability
Machine learning approaches to synthesis, plus
QFactor — a tensor-network-based instantiation
optimizer that processes 12+ qubit circuits directly
and enables 100+ qubit optimization pipelines in
BQSKit.
04
Fault-Tolerant Synthesis
High-precision Clifford+T synthesis via unitary
diagonalization, and application-scale compilation
with controlled error budgets.
05
Controlling Error & Approximation
Empirical evaluation of approximations on real noisy
hardware (SC 2021), and QUEST — robust
resource-efficient circuit approximation (ASPLOS
2022).
06
QEC Implementation
Lattice surgery compilation (TopoLS), magic state
scheduling, and syndrome measurement scheduling
(AlphaSyndrome, ASPLOS 2026).