Area of research
Statistical and Nonlinear Physics · Materials Chemistry
Research interest
Research interests include Computer science, Bayesian optimization, Inverse, Artificial intelligence, Absorbance, and Artificial neural network.
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs
Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics
Constructing custom thermodynamics using deep learning
Deep learning via dynamical systems: An approximation perspective
Two-step machine learning enables optimized nanoparticle synthesis
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Multi‐Fidelity High‐Throughput Optimization of Electrical Conductivity in P3HT‐CNT Composites
Machine learning enables polymer cloud-point engineering via inverse design
An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning