Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
Published a paper titled 'Non-Separable Covariance Kernels for Spatiotemporal Gaussian Processes Based on a Hybrid Spectral Method and the Harmonic Oscillator' in IEEE Transactions on Information Theory, which discusses a novel approach to generating physically motivated non-separable covariance kernels; also worked on information flow rate between cross-correlated stochastic processes.
Research Experience
Has conducted research on function approximation in high-dimensional spaces, with a particular focus on spatiotemporal Gaussian processes.
Background
Research interests include applications of machine learning and geostatistics in data analysis, particularly in developing non-separable covariance kernels and identifying causal relationships.