jordão bragantini

I’m a computer vision and machine learning software engineer at Chan Zuckerberg Biohub, where I develop methods and tools for processing terabytes of microscopy data. I obtained my MSc in Computer Science and BSc in Statistics from the University of Campinas, Brazil. During that time, I spent four wonderful years doing research at LIDS under the supervision of Prof. Alexandre Falcão. In 2019-2020, I was fortunate enough to do a research internship at LIGM under the supervision of Prof. Laurent Najman.

Zebra-fish embryo cell segmentation and tracking from [1];

Download video: mp4 or webm

Publications

  1. M. Lange, A. Granados, S. VijayKumar, J. Bragantini, S. Ancheta, S. Santhosh, and others, “Zebrahub–Multimodal Zebrafish Developmental Atlas Reveal the State-Transition Dynamics of Late-Vertebrate Pluripotent Axial Progenitors,” bioRxiv, 2023. | website | pdf
  2. I. F. Silva, A. M. Sousa, A. X. Falcão, and J. Bragantini, "Differential Dynamic Trees for Interactive Image Segmentation," International Conference on Pattern Recognition (ICPR), pp. 4328-4334, 2022.
  3. B. Yang, M. Lange, A. Millett-Sikking, X. Zhao, J. Bragantini, S. VijayKumar, M. Kamb, R. Gómez-Sjöberg, A. C. Solak, W. Wang, and others, “DaXi—high-resolution, large imaging volume and multi-view single-objective light-sheet microscopy,” Nature methods, vol. 19, no. 4, pp. 461–469, 2022. | link | pdf
  4. J. Bragantini, A. Falcão, and L. Najman, “Rethinking Interactive Image Segmentation: Feature Space Annotation,” Pattern Recognition, vol. 131, p. 108882, 2022. | link | pdf | github
  5. J. Bragantini, “Interactive Image Segmentation: From Graph-based Algorithms to Feature-Space Annotation,” Master's thesis, Universidade Estadual de Campinas, Instituto de Computação, 2021. | pdf
  6. J. Bragantini, B. Moura, A. X. Falcão, and F. A. M. Cappabianco, “Grabber: A tool to improve convergence in interactive image segmentation,” Pattern Recognition Letters, vol. 140, pp. 267–273, 2020. | link | pdf | github
  7. S. B. Martins, J. Bragantini, A. X. Falcão, and C. L. Yasuda, “An adaptive probabilistic atlas for anomalous brain segmentation in MR images,” Medical Physics, vol. 46, no. 11, pp. 4940–4950, 2019. | link
  8. A. X. Falcão and J. Bragantini, “The Role of Optimum Connectivity in Image Segmentation: Can the Algorithm Learn Object Information During the Process?,” Int. Conf. on Discrete Geometry for Computer Imagery, pp. 180–194, 2019. | link
  9. J. Bragantini, S. B. Martins, C. Castelo-Fernandez, and A. X. Falcão, “Graph-based image segmentation using dynamic trees,” Iberoamerican Congress on Pattern Recognition, pp. 470–478, 2018. | link | github