and Systems Biology
University of Pittsburgh
3501 Fifth Avenue
3064 Biomedical Science Tower 3
Pittsburgh PA 15260
Email: shf28 AT pitt DOT edu
Ph (O): (412) 383 7475
Fax: (412) 648 3163
Faculty listing: csb at pitt
Research Assistant Professor
Department of Computational and Systems Biology
University of Pittsburgh , Pittsburgh, PA
PhD (Dec 2010)
Electrical Engineering (Minor: Mathematics)
The University of Arizona, Tucson, AZ
My background straddles the fields of computational imaging, image science, image processing and analysis, and machine learning. My research work has leveraged the interconnections between these fields to develop optical and computational imaging modalities, mathematical models of image formation, image understanding, and image transforms applied to diverse areas such as predicting cancer progression and risk stratification, characterizing nanoscale nuclear morphology during cell proliferation and chromatin decondensation, situational awareness applications, temporal compressive imaging, optical coherence tomography, color science, computer-aided diagnostics, diffraction tomography, and pathology informatics.
More recently, my research work has expanded to studying computational biophysics, spatial heterogeneity in tumor microenvironment, and graphical models. I will be adding details later in the year.
Nassima Bouhenni successfully completed TECBio
summer research program for undergraduate students. (May-July, 2017)
Research topic: Probabilistic modeling of structure and dynamics of intrinsically disordered proteins.
Invited paper, SPIE Photonics West (BIOS) 2017:
Y. Liu, S. Uttam, H. V. Pham, and D. J. Hartman, "Improved cancer risk stratification and diagnosis via quantitative phase microscopy," Quantitative Phase Imaging III, Paper 10074-40 (2017).
Paper on the theory and applications of Fourier
phase in Fourier domain optical coherence tomography has been published in
Journal of Optical Society of America A:
S. Uttam and Y. Liu,
Fourier phase in Fourier-domain optical coherence tomography, J. Opt. Soc. Am. A; 32: 2286-2306 (2015).
Paper on early prediction of cancer progression
based on nanoscale nuclear architecture mapping (nanoNAM) has been published in Cancer Research:
S. Uttam, H. V. Pham, J. LaFace, B. Leibowitz, J. Yu , R. E. Brand, D. J. Hartman, and Y. Liu,
Early prediction of cancer progression by depth-resolved
nanoscale mapping of nuclear architecture from unstained tissue specimens, Cancer Res.; 75: 4718-4727 (2015).
Pitt Innovator Award, November 2014. (University of Pittsburgh award for technology innovation and translation.)
Director's Award for Scientific Excellence, University of Pittsburgh Cancer Institute, Scientific Retreat 2013.Back to top of page