collaborators

5 papers

cs.LG2024

On the Perturbed States for Transformed Input-robust Reinforcement Learning

Tung M. Luu, Haeyong Kang, Tri Ton +2

Reinforcement Learning (RL) agents demonstrating proficiency in a training environment exhibit vulnerability to adversarial perturbations in input observations during deployment. T…

cond-mat.str-el2024

Incipient nematicity from electron flat bands in a kagome metal

Nathan Drucker, Thanh Nguyen, Manasi Mandal +16

Engineering new quantum phases requires fine tuning of the electronic, orbital, spin, and lattice degrees of freedom. To this end, the kagome lattice with flat bands has garnered g…

physics.app-ph2023

Defects Vibrations Engineering for Enhancing Interfacial Thermal Transport

Yijie Zhou, Robert Ciarla, Artittaya Boonkird +10

To push upper boundaries of effective thermal conductivity in polymer composites, a fundamental understanding of thermal transport mechanisms is crucial. Although there is intensiv…

cond-mat.mtrl-sci2023

Precise Fermi-level engineering in a topological Weyl semimetal via fast ion implantation

Manasi Mandal, Abhijatmedhi Chotrattanapituk, Kevin Woller +10

The precise controllability of the Fermi level is a critical aspect of quantum materials. For topological Weyl semimetals, there is a pressing need to fine-tune the Fermi level to…

cond-mat.mtrl-sci2023

Topological superconductors from a materials perspective

Manasi Mandal, Nathan C. Drucker, Phum Siriviboon +6

Topological superconductors (TSCs) have garnered significant research and industry attention in the past two decades. By hosting Majorana bound states which can be used as qubits t…