2010 IR Workshop

Rohit Bhargava

[Click here for the talk abstract]


Prof. Rohit Bhargava is an assistant professor of Bioengineering, Beckman Institute, Micro and Nanotechnology Laboratory, Computational Science and Energy and Sustainability programs at the University of Illinois at Urbana-Champaign.

He is also a faculty fellow at the Center for Advanced Study and at the National Center for Supercomputing Applications. Rohit received dual B.Tech. degrees (in Chemical Engineering and Polymer Science and Engineering) from the Indian Institute of Technology, New Delhi.

His Ph.D. work at Case Western Reserve University was in the area of polymer spectroscopy. Subsequently, he worked as a Research Fellow at the National Institutes of Health in the area of biomedical vibrational spectroscopy.

Current research in the Bhargava laboratories focuses on fundamental optical theory for vibrational spectroscopic imaging, developing new instrumentation, application of spectroscopic imaging to biomedical and polymer problems and numerical analyses.

The research is supported by the NIH, NSF, DoD, Komen for the Cure, NIST, industrial partners and the Grainger, Geyer and Beckman Foundations. The spectroscopy research work has received several awards, including the Society of Applied Spectroscopy Meggers Award (twice). Rohit’s work has been recognized with several research awards and he is routinely nominated to the list of teachers ranked excellent at Illinois.



New Opportunities in Infrared Microspectroscopy

Spectroscopic imaging is proving increasingly useful for biomedical applications when used with chemometrics to recognize diverse cell types and diseases in complex tissue. The automated recognition, in turn, facilitates high throughput, low variability and high confidence in diagnoses or scientific understanding of molecular processes.

While the molecular basis of chemometrics is well established, integration of the emerging understanding of the physics of spectroscopic signals and image formation can significantly augment chemometric analyses. Here, we first present a systematic approach to including light propagation within structured materials and spectral images acquired from such samples.

The nature of spectral distortions due to heterogeneity of tissue samples is discussed and the sources of variance in data from spectral images are identified. Next, the improvements in quality and fidelity of chemometric data analysis through such models are demonstrated.

Last, we discuss unique abilities of coming instrumentation that is enabled both by the theoretical understanding proposed here and recent progress at the SRC beamline. The described approaches are illustrated using examples from prostate, breast and colon cancer pathology.