Towards an Intelligent Microscope: Adaptively Learned Illumination for Optimal Sample Classification. - Amey Chaware; Colin L. V. Cooke; Kanghyun Kim; Roarke Horstmeyer (ICASSP, 2020)

Physics-Enhanced Machine Learning for Virtual Fluorescence Microscopy. - Colin L. V. Cooke; Fanjie Kong; Amey Chaware; Kevin C. Zhou; Kanghyun Kim; Rong Xu; D. Michael Ando; Samuel J. Yang; Pavan Chandra Konda; Roarke Horstmeyer (ICCV, 2021)

Increasing a microscope's effective field of view via overlapped imaging and machine learning. - Xing Yao; Vinayak Pathak; Haoran Xi; Amey Chaware; Colin L. V. Cooke; Kanghyun Kim; Shiqi Xu; Yuting Li; Timothy Dunn; Pavan Chandra Konda; Kevin C. Zhou; Roarke Horstmeyer (CoRR, 2021)

Digital staining in optical microscopy using deep learning - a review. - Lucas Kreiss; Shaowei Jiang; Xiang Li; Shiqi Xu; Kevin C. Zhou; Alexander Mühlberg; Kyung Chul Lee; Kanghyun Kim; Amey Chaware; D. Michael Ando; Laura Barisoni; Seung Ah Lee; et al. (CoRR, 2023)

Detecting immune cells with label-free two-photon autofluorescence and deep learning. - Lucas Kreiss; Amey Chaware; Maryam Roohian; Sarah Lemire; Oana-Maria Thoma; Birgitta Carlé; Maximilian Waldner; Sebastian Schürmann; Oliver Friedrich; Roarke Horstmeyer (CoRR, 2025)