8 citations · 10 across the 9 of their papers we have counts for
10 papers
CrystalMO-TuRBO: Multi-Objective Trust-Region Bayesian Optimization for High-precision Joint Crystal Structure Refinement
Joseph Agada, Yishu Wang, Arpan Biswas
Crystal structure refinement is a fundamental inverse problem in materials characterization, where structural parameters are optimized to reproduce experimental diffraction data. C…
Physically Constrained Ensemble Gaussian Process Modelling for Expensive Quantum Systems with Heteroskedastic Noise
Arpan Biswas, Sutirtha Paul, Joseph Agada +2
Accurate modeling of quantum many-body systems often requires computationally expensive simulations such as Density Matrix Renormalization Group (DMRG) or Quantum Monte Carlo (QMC)…
Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale
Ralph Bulanadi, Jefferey Baxter, Arpan Biswas +5
Self-driving laboratories or autonomous experimentation are emerging as transformative platforms for accelerating scientific discovery. Bayesian optimization (BO) is among the most…
Human-AI Collaborative Autonomous Experimentation With Proxy Modeling for Comparative Observation
Arpan Biswas, Hiroshi Funakubo, Yongtao Liu
Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameters need a rapi…
Physically-Constrained Autoencoder-Assisted Bayesian Optimization for Refinement of High-Dimensional Defect-Sensitive Single Crystalline Structure
Joseph Oche Agada, Andrew McAninch, Haley Day +6
Physical properties and functionalities of materials are dictated by global crystal structures as well as local defects. To establish a structure-property relationship, not only th…
Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments
Ralph Bulanadi, Jawad Chowdhury, Funakubo Hiroshi +4
Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primari…
SANE: Strategic Autonomous Non-Smooth Exploration for Multiple Optima Discovery in Multi-modal and Non-differentiable Black-box Functions
Arpan Biswas, Rama Vasudevan, Rohit Pant +3
Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonia…
Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities
Arpan Biswas, Sai Mani Prudhvi Valleti, Rama Vasudevan +2
Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often non-differentiable parameter spaces, such as phase diagrams…
Autonomous convergence of STM control parameters using Bayesian Optimization
Ganesh Narasimha, Saban Hus, Arpan Biswas +2
Scanning Tunneling microscopy (STM) is a widely used tool for atomic imaging of novel materials and its surface energetics. However, the optimization of the imaging conditions is a…
Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy
Sergei V. Kalinin, Yongtao Liu, Arpan Biswas +5
Machine learning methods are progressively gaining acceptance in the electron microscopy community for de-noising, semantic segmentation, and dimensionality reduction of data post-…