Research

Selected research and technical projects.

research

Hybrid Quantum-Classical Algorithms for the Shortest Vector Problem

Developing hybrid quantum-classical optimization methods for the Shortest Vector Problem on structured lattice instances.

Quantum Algorithm for Finding All Eigenvalues of a Sparse Hermitian Matrix

Developed a full-spectrum quantum estimation scheme without prior eigenvector preparation using computational-basis sampling and sine-windowed QPE. A later re-analysis revealed spectral resolution as a key bottleneck, shaping my current focus on quantum advantage under realistic resource constraints.

Structural Gradient Bias in Hardware-Efficient Quantum Circuits

Identified a spatial trainability failure mode in hardware-efficient ansätze where non-vanishing gradients remain concentrated near local cost operators. Analyzed the mechanism through operator spreading and investigated geometry-aware local scrambling as a minimal intervention for redistributing gradient energy.

Prognostic Modeling for COVID-19 Patients from Longitudinal Blood Tests

Developed a temporal deep-learning pipeline for COVID-19 prognosis prediction from longitudinal blood-test data, addressing limited sample size, label inconsistencies, and clinically informed feature design.

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