| Predicting the band gap of ZnO quantum dots via supervised machine learning models PR Regonia, CM Pelicano, R Tani, A Ishizumi, H Yanagi, K Ikeda Optik 207, 164469, 2020 | 35 | 2020 |
| Machine learning-enabled nanosafety assessment of multi-metallic alloy nanoparticles modified TiO2 system PR Regonia, JP Olorocisimo, F De los Reyes, K Ikeda, CM Pelicano NanoImpact 28, 100442, 2022 | 6 | 2022 |
| Modeling heterogeneous brain dynamics of depression and melancholia using energy landscape analysis PR Regonia, M Takamura, T Nakano, N Ichikawa, A Fermin, G Okada, ... Frontiers in Psychiatry 12, 780997, 2021 | 6 | 2021 |
| Machine-Learned Fermi Level Prediction of Solution-Processed Ultrawide-Bandgap Amorphous Gallium Oxide (a-Ga2Ox) D Purnawati, PR Regonia, JP Bermundo, K Ikeda, Y Uraoka ACS Applied Electronic Materials 4 (12), 5838-5846, 2022 | 2 | 2022 |
| Understanding the Performance of (Ni-Fe-Co-Ce)Ox-based Water Oxidation Catalysts via Explainable Artificial Intelligence Framework PR Regonia, CM Pelicano CHEMELECTROCHEM, 2024 | | 2024 |
| Understanding the Performance of (NiÀ FeÀ CoÀ Ce) Ox-based Water Oxidation Catalysts via Explainable Artificial Intelligence Framework PR Regonia, CM Pelicano | | 2024 |
| Solution processed ultrawide bandgap insulator to semiconductor conversion of amorphous gallium oxide via fermi level control JP Bermundo, D Purnawati, PR Regonia, K Ikeda, Y Uraoka | | 2023 |
| 31‐2: Student Paper: Fermi Level Prediction of Solution‐processed Ultra‐wide Band gap a‐Ga2Ox via Supervised Machine Learning Models D Purnawati, PR Regonia, JP Bermundo, K Ikeda, Y Uraoka SID Symposium Digest of Technical Papers 53 (1), 369-372, 2022 | | 2022 |
| In Pursuit of Depression Biomarkers: Exploring the Neural Energy Landscapes of Melancholic Depression PRR Regonia Nara Institute of Science and Technology, 2022 | | 2022 |
| Energy landscape analysis of depressive brain state dynamics PR Regonia, M Takamura, N Ichikawa, T Nakano, K Ikeda, G Okada, ... IBRO Reports 6, S282, 2019 | | 2019 |
