Adrian Vasile Dalca

Postdoctoral Fellow     curriculum vitae | Linkedin

Computer Science and Artificial Intelligence Lab
EECS, Massachusetts Institute of Technology

A.A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital, Harvard Medical School

32 Vassar St, 32-G904, Cambridge, MA, 02139 
adalca at mit dot edu

I am a postdoctoral fellow at CSAIL, MIT and MGH, Harvard Medical School, working with Mert Sabuncu and John Guttag. I completed my PhD in September, 2016, in the Medical Vision Group, CSAIL, EECS, MIT, advised by Polina Golland. My research focuses on probabilistic models and machine learning for biomedical data, with a focus on medical image analysis.

My wife, Monica, completed her PhD at MIT in the Biology department doing exciting research in cancer biology.

Recent Updates

Nov 2018 Several papers accepted at NIPS ML4H: Machine Learning for Health and MED NIPS: Medical Imaging Meets NIPS
Sep 2018 Voxelmorph (Probabilistic Diffeomorphic registration) is a Finalist for best paper (Young Scientist) award at MICCAI2018!
Sep 2018 Our paper, led by Paolo Casale, on using Gaussian Process Priors in Variational Autoencoders, accepted at NIPS 2018!
Jul 2018 Our paper on "Medical Image Imputation from Image Collections" accepted at IEEE Transactions on Medical Imaging.
Jul 2018 Our paper led by Danielle Pace on Iterative Segmentation from Limited Training Data accepted at MICCAI-DLMIA: Deep Learning in Medical Image Analysis!
Jun 2018 News articles about VoxelMorph and pose warping [1] [2] came out during the week of cvpr where we presented three papers.
Apr 2018 Our paper "Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration" is an early-accept at MICCAI 2018, where we will present it as an oral presentation! We show how CNNs can be used to obtain probabilistic diffeomorphic registration.
Apr 2018 Our paper led by Katie Bouman on Reconstructing Video of Time-varying Celestial Objects accepted at IEEE Transactions on Computational Imaging!
Mar 2018 We will be organizing a new technical workshop at MICCAI this year focusing on integrating medical imaging and non-imaging modalities to answer novel clinical and healthcare challenges.
Feb 2018 Three papers accepted at CVPR 2018!
Oct 2017 Paper accepted for spotlight presentation at NIPS ML4H:
"Spatial Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation"
Sep 2017 Our edited book Imaging Genetics is out, combining work from MICGen.
Also, check out this year's proceedings from MICGen and SWITCH!
Jul 2017 Population Based Image Imputation wins Best Poster Award at IPMI 2017
Jun 2017 Read the MIT News take on our imputation paper: New technique makes brain scans better
Jul 2017 Paper from our clinical stroke team accepted in Neurology: Genetics: "Design and Rationale for Examining Neuroimaging Genetics in Ischemic Stroke: the MRI-GENIE Study"
Feb 2017 Two papers accepted at IPMI 2017: "Population Based Image Imputation" and "Frequency Diffeomorphisms for Efficient Image Registration"
Oct 2016 "Patch-Based Discrete Registration of Clinical Brain Images" wins Best Paper Award at PatchMI 2016. Register images with our patch based method code.
Sep 2016 I wrote a Thesis!
Jul 2016 The Boston Timescape Project has gotten some media narratives.
See MIT Technology Review or Boston Magazine for example.
Jan 2016 New website for the Boston Timescape Project is up!
Sep 2015 Predict entire MRIs using genetics! Short video | paper | web | news

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