My group develops artificially-intelligent discovery machines that use active learning and high-throughput approaches to discover new, synthesizable, and processable materials in unexplored chemical and structural spaces. We investigate processing-structure-property-design (PSP-D) interrelationships in tough, strong, lightweight, multi-functional, and sustainable materials. My group couples advanced additive manufacturing techniques to control hierarchical structures from sub-nano to macro-scale with data-driven numerical approaches to discover material nature. Currently, I am an Associate Professor at the Department of Chemical and Materials Engineering, San Jose State University.  Let me know if you have any questions at [email protected].  Click for my Google Scholar

Some of my current research projects are:

*. Processing discovery: Machine learning-enhanced high throughput (HT) structure control in selective laser melted titaniums, zirconias, BZT-BCT lead-free piezeocereamics, and quantum dot containing thermosets.

*. Structure discovery: HT characterization of nanoscale hierarchical toughening in quantum dot containing polymer and ceramic composites

*. Data-driven recycling planning for smart cities: How to change materials, manufacturing policies to drive sustainable socio-economic development?

*. Mechanics of additively manufactured bioinspired composites and polymers

*. Automatic discovery machines for ultrasonic mixing, nano-liter droplet deposition, and robotic sample preparation coupled with field-assisted additive manufacturing

*. Hierarchical toughening in thermosetting structural battery composites

*. Hierarchical toughening in selective laser melted (SLMed) mechanobiologically optimized metal scaffolds

*. Effects of texture on the mechanical reliability of alumina, stabilized zirconia, and lead-free piezoceramics

*. Shape memory ductile ceramics: HT-Synthesis approaches for single crystal zirconia template particles for reactive templated grain growth (RTGG)

*. Extreme value statistics vs. machine-learned Monte Carlo predictions in systems/device/material reliability

*. Electric field effects on stress distributions in high electron mobility transistors (HEMT) 

*. Thin film materials, manufacturing for stochastic computing, random telegraph noise (RTN) devices, and resistive memories.

*. Virtual reality engineering education (VR-EE), Virtual learning environments for engineers and society

*. Atlas of Materials Complexity, accelerating multi-functional design, materials, manufacturing innovation