Room temperature observation of point defect on gold surface using thermovoltage mapping. - Arijit Roy 001; Cher Ming Tan; Sean J. O'Shea; Kedar Hippalgaonkar; Wulf Hofbauer (Microelectron. Reliab., 2007)

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)

Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials. - Léo Laugier; Daniil Bash; Jose Recatala; Hong Kuan Ng; Savitha Ramasamy; Chuan-Sheng Foo; Vijay Ramaseshan Chandrasekhar; Kedar Hippalgaonkar (CoRR, 2018)

Graph Convolutional Neural Networks for Polymers Property Prediction. - Minggang Zeng; Jatin Nitin Kumar; Zeng Zeng; Ramasamy Savitha; Vijay Ramaseshan Chandrasekhar; Kedar Hippalgaonkar (CoRR, 2018)

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)

Extrapolative Bayesian Optimization with Gaussian Process and Neural Network Ensemble Surrogate Models. - Yee-Fun Lim; Chee Koon Ng; U. S. Vaitesswar; Kedar Hippalgaonkar (Adv. Intell. Syst., 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)

Efficacious symmetry-adapted atomic displacement method for lattice dynamical studies. - Chee Kwan Gan; Yun Liu; Tze Chien Sum; Kedar Hippalgaonkar (Comput. Phys. Commun., 2021)

Optimising Ferroelectric Thin Films with Evolutionary Computation. - Eléonore Vissol-Gaudin; Yee-Fun Lim; Kedar Hippalgaonkar (GECCO Companion, 2023)

Explainable machine learning to enable high-throughput electrical conductivity optimization of doped conjugated polymers. - Ji Wei Yoon; Adithya Kumar; Pawan Kumar; Kedar Hippalgaonkar; J. Senthilnath 001; Vijila Chellappan (CoRR, 2023)

Transfer Learning of Full Molecular Weight Distributions via High-Throughput Computer-Controlled Polymerization. - Jin Da Tan; Balamurugan Ramalingam; Swee Liang Wong; Jayce Jian Wei Cheng; Yee-Fun Lim; Vijila Chellappan; Saif A. Khan; Jatin Kumar; Kedar Hippalgaonkar (J. Chem. Inf. Model., 2023)

Battling Botpoop using GenAI for Higher Education: A Study of a Retrieval Augmented Generation Chatbots Impact on Learning. - Maung Thway; Jose Recatala-Gomez; Fun Siong Lim; Kedar Hippalgaonkar; Leonard W. T. Ng (CoRR, 2024)

Explainable machine learning to enable high-throughput electrical conductivity optimization and discovery of doped conjugated polymers. - Ji Wei Yoon; Adithya Kumar; Pawan Kumar; Kedar Hippalgaonkar; J. Senthilnath 001; Vijila Chellappan (Knowl. Based Syst., 2024)

Constructing custom thermodynamics using deep learning. - Xiaoli Chen; Beatrice W. Soh; Zi-En Ooi; Eléonore Vissol-Gaudin; Haijun Yu; Kostya S. Novoselov; Kedar Hippalgaonkar; Qianxiao Li (Nat. Comput. Sci., 2024)

Wyckoff Transformer: Generation of Symmetric Crystals. - Nikita Kazeev; Wei Nong; Ignat Romanov; Ruiming Zhu; Andrey Ustyuzhanin; Shuya Yamazaki; Kedar Hippalgaonkar (CoRR, 2025)