Chandrajit Bajaj
Left image shows an Iso-surface Rendering of the Haloarcula Marismortui Large Ribosomal 50S subunit (1JJ2) crystal structure(cf. Klein, Schmeing, Moore, Steitz) and based on protein and RNA classification. Light Yellow and Pale Pink are the 5S and 23S Rrna while the remaining colors are proteins.

Additional images and movie for models of ribosomal structures


Research Interests


Computational Biology, Imaging Sciences, Computational Geometry, Geometric Modeling and Optimization, Computer Graphics, Compression, Mesh Generation, Scientific Computation, and Visualization

 

My interdisciplinary research is focused on the algorithmic and computational mathematics underpinnings of Imaging and Geometry Data Sciences, Computer Graphics, Bio-Informatics and Visualization with applications stemming from bio-medical engineering, physical and chemical sciences and bio-inspired architecture. My commitment to the field of computational and predictive medicine is evidenced by my research focus this past decade. I design and implement scalable solutions for : (a) forward and inverse problems in microscopy, spectroscopy, biomedical imaging; (b) constructing spatially realistic and hierarchical phenomenological models; (c) development of fast high-dimensional search/scoring engines for predicting energetically favorable multi-molecular and cellular complexes; and (d) statistical analysis and interrogative visualization of neuronal form-function. Additionally, I have courtesy appointments and supervise M.S and Ph.D. students from several UT departments, including, biomedical and electrical engineering, neurobiology, and mathematics.

 

My research is currently sponsored by grants from the National Science Foundation (NSF) and the National Institutes of Health (NIH).

 
My research publications are available here, as is my Curriculum Vitae. Click here for Google Scholar Citations