Rama K Vasudevan Group Leader, Data NanoAnalytics Group at the CNMS Contact VASUDEVANRK@ORNL.GOV All Publications Enhancing hyperspectral EELS analysis of complex plasmonic nanostructures with pan-sharpening Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality Toward Decoding the Relationship between Domain Structure and Functionality in Ferroelectrics via Hidden Latent Variables Reconstruction and uncertainty quantification of lattice Hamiltonian model parameters from observations of microscopic degrees of freedom Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data Exploration of lattice Hamiltonians for functional and structural discovery via Gaussian process-based exploration–exploitation Bayesian inference in band excitation scanning probe microscopy for optimal dynamic model selection in imaging... Super-resolution and signal separation in contact Kelvin probe force microscopy of electrochemically active ferroelectric materials Dynamic Manipulation in Piezoresponse Force Microscopy: Creating Nonequilibrium Phases with Large Electromechanical Response Causal analysis of competing atomistic mechanisms in ferroelectric materials from high-resolution scanning transmission electron microscopy data Fast Scanning Probe Microscopy via Machine Learning: Non‐Rectangular Scans with Compressed Sensing and Gaussian Process Opt... Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy Exploration of Electrochemical Reactions at Organic–Inorganic Halide Perovskite Interfaces via Machine Learning in In Situ Time‐of‐Flight Secondary Ion Mass Spectrometry Guided search for desired functional responses via Bayesian optimization of generative model: Hysteresis loop shape engineering in ferroelectrics Optimizing Individualized Treatment Planning for Parkinson’s Disease Using Deep Reinforcement Learning Visualizing Charge Transport and Nanoscale Electrochemistry by Hyperspectral Kelvin Probe Force Microscopy Phase diagrams of single-layer two-dimensional transition metal dichalcogenides: Landau theory Imaging mechanism for hyperspectral scanning probe microscopy via Gaussian process modelling Thickness and strain dependence of piezoelectric coefficient in BaTiO3 thin films Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study Toward Electrochemical Studies on the Nanometer and Atomic Scales: Progress, Challenges, and Opportunities Building ferroelectric from the bottom up: The machine learning analysis of the atomic-scale ferroelectric distortions... Non-conventional mechanism of ferroelectric fatigue via cation migration Deep data analytics for genetic engineering of diatoms linking genotype to phenotype via machine learning Pagination First page « First Previous page ‹‹ … Page 3 Current page 4 Page 5 … Next page ›› Last page Last » Key Links Curriculum Vitae Google Scholar ORCID LinkedIn Organizations Physical Sciences Directorate User Facilities Center for Nanophase Materials Sciences Theory and Computation Section Data NanoAnalytics Group
Research Highlight Deep Learning with in situ Diagnostics Reveals Non-trivial Correlations to Film Growth
