8 citations · 10 across the 9 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…