Principal Investigator: George Barbastathis
Professor, Department of Mechanical Engineering, Massachusetts Institute of Technology, USA.
Singapore-MIT Alliance for Research and Technology (SMART) Centre, Singapore.
- Our work on AI-based particle size estimator for manufacturing medicine is reported in MIT News.
- Our paper on learning-based speckle analysis for a powder particle size distribution estimator has been published in Nature Communications. (03/2023)
- Qihang successfully passed his doctoral defense. Congratulations, Dr. Zhang! (01/2023)
- Iksung successfully passed his doctoral defense. Congratulations, Dr. Kang! (05/2022)
- Our paper on a dynamical machine learning approach for reconstructing dense-layered phase objects has been published in Light: Science and Applications. (04/2021)
- Our recurrent neural network approach to reveal transparent objects through dynamic scattering media has been published in Optics Express. (01/2021)
- A deep-learning approach to predict the behavior of COVID-19 nationwide spread has been published in Cell: Patterns. (11/2020)
- Check out our new paper published in arXiv on the use of machine learning to estimate the forward scattering Lippmann-Schwinger model. (10/2020)
- Welcome Van and Zhen to be part of our team! (09/2020)
- Check out our new paper published in arXiv on limited-angle tomographic reconstruction by a dynamical machine learning approach. (07/2020)
- Our paper on the interplay between physical and content priors in deep learning for computational imaging published in Optics Express. (07/2020)
- Our paper on the use of coherent modulation imaging and deep learning for high-fidelty inversion under low-photon conditions published in Optics Express! (07/2020)
- Mo successfully passed his doctoral defense, and Kwabena and Iksung finished their Master of Science theses. Congratulations, Dr. Mo Deng, Kwabena, and Iksung! (05/2020)
- Qihang Zhang joined our group as a graduate student. He will first pursue his Master's degree. Welcome Qihang! (05/2020)
- Our paper on Learning to Synthesize Deep Neural Network for high-fidelity phase retrieval in the low-photon regime published in Light: Science and Applications! (03/2020)
- Paper on the analysis on artifacts in Perceptual Loss Trained Phase Extraction Neural Network in the low-photon condition published in Optics Express! (01/2020)