Molin Zhang  
(张 墨林)

prof_pic.jpeg

Room 36-776A

50 Vassar St.

Cambridge, MA 02139

Hello! My name is Molin Zhang. I’m currently a Machine Learning Research Engineer at Apple under Camera Algorithm Team.

I got my PhD from Electrical Engineering and Computer Science (EECS) at MIT supervised by Prof. Elfar Adalsteinsson.

My research centers on the intersection of computational imaging, computer vision, and signal processing, with a particular emphasis on medical imaging. I delve into the realm of inverse problems, utilizing numerical simulations to develop innovative solutions.

I completed two significant summer internships. At GE Healthcare, I developed an automated LLD measurement system, contributing to advancements in healthcare technology. At Samsung’s Mobile Processor Innovation (MPI) Lab, I designed frameworks and techniques for next-gen Image Signal Processor (ISP) pipeline, focusing on super high-resolution imaging in mobile devices.

Feel free to reach me at molin [at] mit [dot] edu or zhangmolin18 [at] gmail [dot] com.

news

Jun 24, 2024 I started a new job at Apple as a Machine Learning Research Engineer at Camera Algorithm team!
Jun 17, 2024 Our paper “CoDISP: Exploring Compressed Domain Camera ISP with RGB-guided Encoder” was presented at CVPR workshop (Mobile AI) 2024! Check it out! [Paper]
May 17, 2024 I graduated from MIT EECS and now I’m a PhD!!
Jul 26, 2023 Our paper “Stochastic-offset-enhanced restricted slice excitation and 180° refocusing designs with spatially non-linear B0 shim array fields” was accepted by MRM and published! [Paper] [Code]
Jul 10, 2023 Our paper “Zero-Shot Self-Supervised Joint Temporal Image and Sensitivity Map Reconstruction via Linear Latent Space” was presented at MIDL 2023! Check it out! [Paper] [Code]
May 30, 2023 I join Samsung Research America (SRA) as a research engineer intern, working on next generation real-world computational imaging and computer vision! Lets keep making impacts!
Mar 16, 2023 Our paper entitled “Latent Signal Models: Learning Compact Representations of Signal Evolution for Improved Time-Resolved, Multi-contrast MRI” was accepted by MRM! [paper]
Jan 1, 2023 I will be serving as reviewer for MICCAI 2023, AAAI 2024 and AAAI workshop 2024.

selected publications

  1. ×
    Zero-Shot Self-Supervised Joint Temporal Image and Sensitivity Map Reconstruction via Linear Latent Space
    In Medical Imaging with Deep Learning – MIDL 2023
  2. ×
    Stochastic-offset-enhanced restricted slice excitation and 180° refocusing designs with spatially non-linear ∆B0 shim array fields.
    Molin ZhangYamin Arefeen, Nicolas Arango, Jason P Stockmann, and 2 more authors
    Magnetic Resonance in Medicine, 2023
  3. ×
    Selective RF excitation designs enabled by time-varying spatially non-linear ∆B0 fields with applications in fetal MRI
    Molin Zhang, Nicolas Arango, Jason P Stockmann, Jacob White, and 1 more author
    Magnetic Resonance in Medicine, 2022
  4. ×
    Enhanced Detection of Fetal Pose in 3D MRI by Deep Reinforcement Learning with Physical Structure Priors on Anatomy
    Molin Zhang*Junshen Xu*, Esra Abaci Turk, P. Ellen Grant, and 2 more authors
    In Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
  5. ×
    Fetal Pose Estimation in Volumetric MRI using a 3D Convolution Neural Network
    Junshen Xu*Molin Zhang*Esra Abaci Turk, Larry Zhang, and 4 more authors
    In Medical Image Computing and Computer Assisted Intervention – MICCAI 2019