Polina Golland


photo courtesy Allegra Boverman 		Contact:
MIT CSAIL
32 Vassar Street 32-D470
Cambridge, MA 02139
tel: 617-253-8005
email: polina at csail.mit.edu
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Last updated
Aug 04, 2025

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We gratefully acknowledge the following sponsors, programs and grants whose financial support has made our research possible:
  • Bringing coherent fetal brain volumes and automated metrics to the radiology workflow
    NIH NIBIB 1R01EB036945

  • Developing novel MR tools to optimize surgical planning and fetal outcome in TTTS
    NIH NICHD 1R01HD114338

  • Fetal MRI: robust self-driving brain acquisition and body movement quantification
    NIH NIBIB 1R01EB032708

  • DISCOVERY: Determinants of incident stroke cognitive outcomes and vascular effects on recovery
    NIH NINDS U19NS115388

  • MIT CSAIL-Wistron Program

  • Chou Family Transformative Research Fund

  • MIT-IBM Watson AI Lab

  • MIT Jameel Clinic

The students in our group have also received support from these great training programs and fellowships:
  • NSF Graduate Fellowship

  • MIT Health and Life Sciences Collaborative

  • The MIT/Harvard Neuroimaging Training Program
    (NIH 5T32EB001680)

  • The MIT-Takeda Fellowship

  • Google Graduate Fellowship

Past Funding

  • Novel MRI Assessment of Placental Structure and Function throughout Pregnancy
    NIH NICHD R01HD100009

  • MIT Lincoln Lab Collaboration: Weekly Supervised Multimodal Learning for Battlefield Medical Diagnosis
    MIT Lincoln Lab

  • MRI-Based Mapping of Congenital Heart Disease for Diagnosis, Surgical Planning and Patient Monitoring
    MIT-Philips Collaboration

  • Imaging Analysis of Chest X-rays for Heart Failure
    MIT-Philips Collaboration

  • The Neuroimaging Analysis Center
    NIH NIBIB NAC P41EB015902

  • MIT -Takeda Collaboration: Machine learning for image-based liver phenotyping and drug discovery
    Takeda

  • Noninvasive Realtime Assessment of Placental Structure and Function with Novel MR Imaging Methods
    NIH NICHD U01HD087211

  • MRI-Genetics Interface Exploration: MRI-GENIE Study
    NIH NINDS R01NS086905

  • The NIH NICHD R01 grant on Using Cognitive Neuroscience to Predict Dyslexia among Kindergarten Children
    (NIH NICHD R01HD067312)

  • Learning from limited image data
    Suzhou Industrial Park (SIP)

  • The MIT Lincoln Lab Collaboration Grant: Connectivity Analysis: Latent Structure and Anomaly Detection in Graphs

  • The National Alliance for Medical Image Computing
    (NIH NIBIB NAMIC U54-EB005149)

  • Finding Structure in the Space of Activation Profiles in fMRI
    (NSF IIS/CRCNS 0904625)

  • NSF CAREER: Computational Modeling of Spatial Activation Patterns in fMRI
    (NSF CAREER 0642971)

  • The NIH NINDS R01 grant on Computational Modeling of Shape Distributions
    (NIH NINDS R01NS051826)

  • The MIT McGovern Institute Neurotechnology Program

  • The Morphometry Biomedical Informatics Research Network
    (NIH NCRR mBIRN U24-RR021382)

  • The Engineering Research Center for Computer-Integrated Surgical Systems and Technology
    (NSF JHU ERC CISST)

  • The MIT EECS/Whitehead/Broad Training Program in Computational Biology
    (NIH DK070069)