Chandrajit L. Bajaj


Chandrajit L. Bajaj graduated with a Bachelor’s degree in 1980, with highest distinction (10.0/10.0 GPA) in Electrical Engineering from the Indian Institute of Technology, Delhi. He received his Masters and Ph.D. degrees in Computer Sciences working with John Hopcroft, from Cornell University in 1983, and 1984 respectively. Bajaj is currently a Professor of Computer Sciences at the University of Texas at Austin, and the director of the Center for Computational Visualization, in the Institute for Computational and Engineering Sciences (ICES). He holds the Computational Applied Mathematics Chair in Visualization. He is also an affiliate faculty member of Mathematics, Electrical Engineering, Bio-Medical Engineering, and also a member of the Institutes of Cell and Molecular Biology, and Neurosciences, the Center for Learning and Memory, and the Center for Perceptual Systems. Bajaj is a fellow of the American Association for the Advancement of Science (AAAS).

His computational biology and bioinformatics research interests span the algorithmic and mathematics underpinnings of Structural Biology and Biophysics. Current research in his lab includes:

  1. The structure elucidation and reconstruction of spatially realistic models of molecules, organelles, cells from cryo-electron microscopy, and bio-imaging,
  2. Fast high-dimensional search and scoring engine for identifying energetically favorable molecular binding conformations (e.g virtual screening for anti-viral drugs),
  3. Integrated approaches to computational modeling, mathematical analysis and interrogative visualization, in particular, of the dynamics of electrical signaling and oscillations (3–10 Hz) amongst neurons in the hippocampus (the central area of learning and memory), and
  4. Patient specific and spatially accurate modeling, analysis and visualization of human cardio-vasculature.


“Geometric Modeling and Quantitative Visualization of Virus Ultrastructure”, Modeling Biology: Structures, Behaviors, Evolution, ed. by M. Laublichler and G. Muller, MIT Press, 2007, pages 115-137

“Modeling Cardiovascular Anatomy from Patient-Specific Imaging”, (with S. Goswami), Advances in Computational Vision and Medical Image Processing, ed. by Joao Tavares and Renato Jorge, Springer, 2008, Chapter 1, pgs 1-28

“F2Dock: Fast Fourier Protein-Protein Docking”, (with R. Chowdhury, V. Siddahanavalli), IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2009, Accepted for publication


A Reconstructed 3D Map of the Herpes Simplex Virus (HSV) Segmentation Based on the Global (icosahedral) Symmetry and on the Local 6-Fold Symmetry. A total of 10 different types of subunits are segmented and indicated by different colors. This visualization is created with AnimMaker, an animation tool that is part of our Volume Rover software. Volume Rover is a volumetric visualization software tool developed at the Computational Visualization Center at the University of Texas at Austin.