Elfar Adalsteinsson

Core Faculty
Phone: (617) 324-3597
Email: elfar@mit.edu
room: 36-766
MIT address: 77 Massachusetts Ave., Cambridge, MA 02139
Administrative Assistant: Megumi Masuda-Loos
assistant phone: (617) 324-3542
assistant email: mriadmin@mit.edu

Elfar Adalsteinsson

Core Faculty


  • Eaton-Peabody Professor, Electrical Engineering and Computer Science and Institute for Medical Engineering and Computer Science, Massachusetts Institute of Technology


Elfar Adalsteinsson, Professor of Electrical Engineering and Computer Science and of MIT’s Division of Health Sciences and Technology, joined the MIT faculty and the Research Laboratory of Electronics in 2004.


  • PhD in Electrical Engineering, Stanford University, 1995
  • MS in Electrical Engineering, Stanford University, 1991
  • BS in Electrical Engineering, University of Iceland Reykjavik, 1989

selected awards/societies

  • College of Fellows Inductee, American Institute for Medical and Biological Engineering, 2016
  • International Society of Magnetic Resonance in Medicine (ISMRM)
  • Fulbright Fellowship

research interests

Research interests include magnetic resonance imaging (MRI) in pregnancy, including the fetus and placenta, quantitative MRI, deep learning and AI for medical imaging applications, parallel transmission, power deposition in MRI, oxygenation imaging with MRI, and reconstructions of dramatically under-sampled MR imaging and spectroscopy.

selected publications

  • Placental MRI: Developing Accurate Quantitative Measures of Oxygenation. Abaci Turk E, Stout JN, Ha C, Luo J, Gagoski B, Yetisir F, Golland P, Wald LL, Adalsteinsson E, Robinson JN, Roberts DJ, Barth WH Jr, Grant PE. Top Magn Reson Imaging. 2019 Oct;28(5):285-297
  • In Vivo Quantification of Placental Insufficiency by BOLD MRI: A Human Study. Luo J, Abaci Turk E, Bibbo C, Gagoski B, Roberts DJ, Vangel M, Tempany-Afdhal CM, Barnewolt C, Estroff J, Palanisamy A, Barth WH, Zera C, Malpica N, Golland P, Adalsteinsson E, Robinson JN, Grant PE. Sci Rep. 2017 Jun 16;7(1):3713.
  • The ultimate signal-to-noise ratio in realistic body models. Guérin B, Villena JF, Polimeridis AG, Adalsteinsson E, Daniel L, White JK, Wald LL. Magn Reson Med. 2017 Nov;78(5):1969-1980.

A full list of Professor Adalsteinsson’s publications can be found on his website.

courses taught

  • HST 580/6.556 Data Acquisition and Image Reconstruction in MRI Data Acquisition and Image Reconstruction in MRI
  • 6.003 Signal Processing
  • 6.03 Introduction to EECS from a Medical Technology Perspective
  • 6.011 Signals, Systems & Inference