Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing. - Juan Pablo Correa-Baena; Kedar Hippalgaonkar; Jeroen van Duren; Shaffiq Jaffer; Vijay Ramaseshan Chandrasekhar; Vladan Stevanovic; Cyrus Wadia; Supratik Guha; Tonio Buonassisi (CoRR, 2018)

Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks. - Felipe Oviedo; Zekun Ren; Shijing Sun; Charlie Settens; Zhe Liu; Noor Titan Putri Hartono; Ramasamy Savitha; Brian L. DeCost; Siyu I. P. Tian; Giuseppe Romano; Aaron Gilad Kusne; Tonio Buonassisi (CoRR, 2018)

Machine learning enables polymer cloud-point engineering via inverse design. - Jatin Nitin Kumar; Qianxiao Li; Karen Y. T. Tang; Tonio Buonassisi; Anibal L. Gonzalez-Oyarce; Jun Ye (CoRR, 2018)

Perovskite PV-powered RFID: enabling low-cost self-powered IoT sensors. - Sai Nithin R. Kantareddy; Ian Mathews; Shijing Sun; Mariya Layurova; Janak Thapa; Juan Pablo Correa-Baena; Rahul Bhattacharyya; Tonio Buonassisi; Sanjay E. Sarma; Ian Marius Peters (CoRR, 2019)

Bayesim: A tool for adaptive grid model fitting with Bayesian inference. - Rachel C. Kurchin; Giuseppe Romano; Tonio Buonassisi (Comput. Phys. Commun., 2019)

Long Range Battery-Less PV-Powered RFID Tag Sensors. - Sai Nithin R. Kantareddy; Ian Mathews; Rahul Bhattacharyya; Ian Marius Peters; Tonio Buonassisi; Sanjay E. Sarma (IEEE Internet Things J., 2019)

Inverse design of crystals using generalized invertible crystallographic representation. - Zekun Ren; Juhwan Noh; Siyu I. P. Tian; Felipe Oviedo; Guangzong Xing; Qiaohao Liang; Armin Aberle; Yi Liu; Qianxiao Li; Senthilnath Jayavelu; Kedar Hippalgaonkar; Yousung Jung; et al. (CoRR, 2020)

A robust low data solution: Dimension prediction of semiconductor nanorods. - Xiaoli Liu; Yang Xu; Jiali Li; Xuanwei Ong; Salwa Ali Ibrahim; Tonio Buonassisi; Xiaonan Wang 002 (Comput. Chem. Eng., 2021)

Online Preconditioning of Experimental Inkjet Hardware by Bayesian Optimization in Loop. - Alexander E. Siemenn; Matthew Beveridge; Tonio Buonassisi; Iddo Drori (CoRR, 2021)

Autonomous Optimization of Fluid Systems at Varying Length Scales. - Alexander E. Siemenn; Evyatar Shaulsky; Matthew Beveridge; Tonio Buonassisi; Sara M. Hashmi; Iddo Drori (CoRR, 2021)

Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains. - Qiaohao Liang; Aldair E. Gongora; Zekun Ren; Armi Tiihonen; Zhe Liu 040; Shijing Sun; James R. Deneault; Daniil Bash; Flore Mekki-Berrada; Saif A. Khan; Kedar Hippalgaonkar; Benji Maruyama; et al. (CoRR, 2021)

Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing. - Zhe Liu 040; Nicholas Rolston; Austin C. Flick; Thomas Colburn; Zekun Ren; Reinhold H. Dauskardt; Tonio Buonassisi (CoRR, 2021)

Opportunities for Machine Learning to Accelerate Halide Perovskite Commercialization and Scale-Up. - Rishi E. Kumar; Armi Tiihonen; Shijing Sun; David P. Fenning; Zhe Liu 040; Tonio Buonassisi (CoRR, 2021)

Interpretable and Explainable Machine Learning for Materials Science and Chemistry. - Felipe Oviedo; Juan Lavista Ferres; Tonio Buonassisi; Keith Butler (CoRR, 2021)

Introducing flexible perovskites to the IoT world using photovoltaic-powered wireless tags. - Sai Nithin Reddy Kantareddy; Rahul Bhattacharya; Sanjay E. Sarma; Ian Mathews; Janak Thapa; Liu Zhe; Shijing Sun; Ian Marius Peters; Tonio Buonassisi (CoRR, 2022)

Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films. - Siyu Isaac Parker Tian; Zekun Ren; Selvaraj Venkataraj; Yuanhang Cheng; Daniil Bash; Felipe Oviedo; J. Senthilnath 001; Vijila Chellappan; Yee-Fun Lim; Armin G. Aberle; Benjamin P. MacLeod; Fraser G. L. Parlane; et al. (CoRR, 2022)

Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization. - Alexander E. Siemenn; Zekun Ren; Qianxiao Li; Tonio Buonassisi (CoRR, 2022)

Human Evaluation of Text-to-Image Models on a Multi-Task Benchmark. - Vitali Petsiuk; Alexander E. Siemenn; Saisamrit Surbehera; Zad Chin; Keith Tyser; Gregory Hunter; Arvind Raghavan; Yann Hicke; Bryan A. Plummer; Ori Kerret; Tonio Buonassisi; Kate Saenko; et al. (CoRR, 2022)

A Dataset for Learning University STEM Courses at Scale and Generating Questions at a Human Level. - Iddo Drori; Sarah J. Zhang; Zad Chin; Reece Shuttleworth; Albert Lu; Linda Chen; Bereket Birbo; Michele He; Pedro Lantigua; Sunny Tran; Gregory Hunter; Bo Feng; et al. (AAAI, 2023)

Decreasing the Computing Time of Bayesian Optimization Using Generalizable Memory Pruning. - Alexander E. Siemenn; Tonio Buonassisi (HPEC, 2023)

Vision-driven Autocharacterization of Perovskite Semiconductors. - Alexander E. Siemenn; Eunice Aissi; Fang Sheng; Armi Tiihonen; Hamide Kavak; Basita Das; Tonio Buonassisi (CoRR, 2023)

Deep learning robotics using self-supervised spatial differentiation drive autonomous contact-based semiconductor characterization. - Alexander E. Siemenn; Basita Das; Kangyu Ji; Fang Sheng; Tonio Buonassisi (CoRR, 2024)

Batch Bayesian Optimization for High-Dimensional Experimental Design: Simulation and Visualization. - Imon Mia; Armi Tiihonen; Anna Ernst; Anusha Srivastava; Tonio Buonassisi; William G. Vandenberghe; Julia W. P. Hsu (CoRR, 2025)