Kilian M. Pohl, PhD
Consulting Assistant Professor
Department of Psychiatry & Behavioral Sciences
333 Ravenswood Ave
Menlo Park, CA 94025
My main research area is computational medical image analysis with a focus
on studying models motivated from a Bayesian perspective, machine learning, and differential geometry. It is my long term goal to enhance personalized medicine by creating algorithms for automatically quantifying and generalizing the information latent in images for tasks such as disease analysis, treatment monitoring, and surgical planning.
2013 - Program Director, Senior Research Scientist - SRI International, Menlo Park, CA
Consulting Assistant Professor - Stanford University, Stanford, CA
2010-2013 Assistant Professor (Tenure Track) - University of Pennsylvania, Philadelphia, PA
2008-2010 Research Staff Member - IBM Almaden, San Jose, CA
2006-2008 Instructor of Radiology (Junior Faculty) - BWH, Harvard Medical
School, Boston, MA
Research Fellow -
BWH, Harvard Medical School, Boston, MA
Research Affiliate, Postdoctoral Associate -
CSAIL, MIT, Cambridge, MA
Research Associate -
CSAIL, MIT, Cambridge, MA
Training Manager - Propack Data, Cary, NC
M.Sc. (Mathematics) -
University Karlsruhe(TH) (Germany)
joins group to idenfy phenotypes by creating maps of medical images
Kilian Pohl: promoted to Program Director at SRI
Kilian Pohl: Presents Logarithm of Odds for Medical Image Analysis at the Joint Statistical Meetings (JSM), Boston
Dolf Pfefferbaum: "White Matter Microstructural Recovery with Abstinence and Decline with Relapse in Alcoholism: A Controlled Longitudinal DTI Study," in press at The Lancet Psychiatry
Kilian Pohl: Guest lecturer at Biomedical Informatics 260, Stanford University
Kilian Pohl: Affiliated with Information Sciences in Imaging at Stanford (ISIS) section, Radiology, Stanford University
Kilian Pohl: Received Creative and Novel Ideas in HIV Research (CNIHR) Award
Kilian Pohl: "Logarithm of Odds for Medical Images Analysis", Divisions of Biostatistics and Bioinformatics, UCSF
Dong Ye: " Auto-Encoding of Discriminating Morphometry from Cardiac MRI", invited for oral presentation to ISBI 2014, Bejing, China.
Dong Ye: "Regional Manifold Learning for Disease Classification", in press at IEEE Transactions on Medical Imaging.
Kilian Pohl: Selected to the Program Committee, MICCAI 2014.
Dongjin Kwon: "PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration", in press at IEEE Transactions on Medical Imaging.
D.H. Ye, B. Desjardins, J. Hamm, H. Litt, K.M. Pohl.
Regional Manifold Learning for Disease Classification, IEEE Transactions on Medical Imaging, 33(6), pp 1236 – 1247, 2014.
D. Kwon, M. Niethammer, H. Akbari, M. Billelo, C. Davatzikos, K.M. Pohl.
PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration, IEEE Transactions on Medical Imaging, 33(3), pp. 651 – 667, 2014.
E. Konukoglu, B. Glocker, D.H. Criminisi, K.M. Pohl.
WESD - Weighted Spectral Distance for Measuring Shape Dissimilarity, IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2284-2297, 2013.
B. Tunc, A. Smith, D. Wassermann, X. Pennec, W.M. Wells, R. Verma, K.M. Pohl.
Multinomial Probabilistic Fiber Representation for Connectivity Driven Clustering, IPMI 2013: The 23rd biennial International Conference on Information Processing in Medical Imaging, Springer, LNCS 7917, pp 730–41, 2013.
E. Bernardis, E. Konukoglu, Y. Ou, D. Metaxas, B. Desjardins, K.M. Pohl.
Temporal Shape Analysis via the Spectral Signature,
MICCAI 2012: Fifteenth International Conference Medical Image Computing and Computer-Assisted Intervention , Springer-Verlag, LNCS 7511, pp. 49-56, 2012.