I am currently a PhD candidate in Robotics Institute of Carnegie Mellon University, under supervision of Dr. Simon Lucey and Dr. Michael Kaess . I am interested in robot vision, especially for 3D reconstruction and efficient real-world deep network applications. Before CMU, I graduated from Electrical Engineering department of National Taiwan University in 2012, directed by Dr. Li-chen Fu. And worked in Quanta Computer and MediaTek as ISP (Image Signal Processor) algorithm developer for 3 years.

Contact: mf.allie.chang at gmail dot com

Recent Publications

Google Scholar

  1. Ming-Fang Chang, Ratnesh Kumar, De Wang, and James Hays, “Systems and methods for producing amodal cuboids”, US patent application (link)

  2. Ming-Fang Chang, Yipu Zhao, Rajvi Shah, Jakob J. Engel, Michael Kaess, and Simon Lucey, “Long-term Visual Map Sparsification with Heterogeneous GNN”, on CVPR2022 (link)

  3. Ming-Fang Chang, Wei Dong, Joshua Mangelson, Michael Kaess, and Simon Lucey, “Map Compressibility Assessment for LiDAR Registration”, on IROS2021 (link)

  4. Ming-Fang Chang, Joshua Mangelson, Michael Kaess, and Simon Lucey, “HyperMap: Compressed 3D Map for Monocular Camera Registration”, on ICRA2021 (link)

  5. Ming-Fang Chang*; John Lambert*; Patsorn Sangkloy*; Jagjeet Singh*; Slawomir Bak; Andrew Hartnett; De Wang; Peter Carr; Simon Lucey; Deva Ramanan; James Hays, “Argoverse: 3D Tracking and Forecasting With Rich Maps”, on CVPR2019 Oral (Thanks to the hard work of all co-authors!!) (link) (website)

  6. Calvin Murdock, Ming-Fang Chang, Simon Lucey, Deep Component Analysis via Alternating DirectionNeural Networks, on ECCV2018 (link)

  7. Christopher Ham, Ming-Fang Chang, Simon Lucey, and Surya Singh , “Metric Monocular Depth from Small Motion Video Accelerated”, on 3DV2017 (Spotlight) (link)

Recent News


  1. TA for Robot Localization and Mapping(16833), 2019 fall at CMU
  2. TA for Computer Vision(16720B), 2018 fall at CMU


Reviewers for CVPR, RA-L, ICRA, and IROS