Berthy Feng
Scholar

Berthy Feng

Google Scholar ID: xTpZi2oAAAAJ
PhD Candidate, California Institute of Technology
computational imagingcomputer visionmachine learning
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Citations & Impact
All-time
Citations
355
 
H-index
9
 
i10-index
9
 
Publications
17
 
Co-authors
0
 
Contact
Emailberthy@mit.eduCVOpen ↗GitHubOpen ↗
Publications
2 items
Position-Blind Ptychography: Viability of image reconstruction via data-driven variational inference
2025
Cited
0
Teaching Humans Subtle Differences with DIFFusion
2025
Cited
0
Resume (English only)
Academic Achievements
  • 1. Paper 'Visual Surface Wave Elastography: Revealing Subsurface Physical Properties via Visible Surface Waves' accepted to ICCV 2025
  • 2. Paper 'Neural Approximate Mirror Maps for Constrained Diffusion Models' accepted to ICLR 2025
  • 3. Paper 'Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors' published in The Astrophysical Journal (ApJ) 2024
  • 4. Paper 'Variational Bayesian Imaging with an Efficient Surrogate Score-based Prior' published in Transactions on Machine Learning Research (TMLR) 2024
  • 5. Paper 'Score-Based Diffusion Models as Principled Priors for Inverse Imaging' accepted to ICCV 2023
  • 6. Paper 'Visual Vibration Tomography: Estimating Interior Material Properties from Monocular Video' accepted to CVPR 2022
  • 7. Best Poster Award at ICCP 2021
  • 8. NSF Graduate Research Fellowship
  • 9. Best Paper Finalist at CVPR 2022
Research Experience
  • 1. Postdoctoral Fellow at MIT and IAIFI
  • 2. Led the IAIFI panel at the Boston Diffusion Day workshop
  • 3. Delivered a keynote at the ML4Astro workshop
  • 4. Taught the EHT Black-Hole Imaging course at the ICCP Summer School
  • 5. Presented invited talks at the SCIEN seminar series at Stanford University, imaging reading group at Carnegie Mellon University, Deep Learning for Inverse Problems workshop at DESY in Hamburg, Germany, and Computational Imaging workshop hosted by IMSI at the University of Chicago
  • 6. Co-organized the Quo Vadis, Computer Vision? workshop at ICCV 2023
  • 7. Spoke at the Astro + Imaging Workshop at Northwestern
  • 8. Presented a Spotlight poster at ICCP 2023
Education
  • 1. Ph.D. - California Institute of Technology, Advisor: Prof. Katie Bouman
  • 2. B.S. - Princeton University, Major: Computer Science, Minor: Statistics & Machine Learning
Background
  • Works on computational imaging for science. Currently a Postdoctoral Fellow at MIT and IAIFI, advised by Prof. Bill Freeman. Obtained PhD from Caltech, advised by Prof. Katie Bouman. Graduated summa cum laude from Princeton University, majoring in Computer Science and minoring in Statistics & Machine Learning.
Miscellany
  • Personal interests and hobbies not mentioned
Co-authors
0 total
Co-authors: 0 (list not available)