User:JecyT/sandbox

= Sri Rama Prasanna Pavani =

Prasanna is an engineer, architect, and a leader—the kind that brings out the best in people and technology to create opportunities of a lifetime. Dr. Prasanna is the Founder and CEO of Exnodes, where he pioneers Computational Parallel Inspection® to maximize yields of computing chips.

Education
Prasanna Pavani is from Chennai. He holds the Bachelor of Engineering degree in Electronics and Communication Degree from Government College of Technology, Coimbatore and the Master of Science degree in ECE from University of Colorado, Boulder. Prasanna has been recognized by the University of Colorado's Outstanding Ph.D. Award in 2009. He was a Postdoctoral Scholar in EE at California Institute of Technology. Prasanna studied Business Strategies and Entrepreneurship at Stanford University.

Career
Prasanna served as VP Engineering at Arecont Vision (leader in security video) and has held senior engineering positions at Ricoh Innovations (leader in enterprise imaging), KLA-Tencor (leader in process control), and D. E. Shaw & Co (leader in computational finance).He serves as an Editor of Computational Imaging, Member of Program Committee of COSI conference, and as a Panel Member of U.S. National Science Foundation. In 2014, he became the founder and Chief Executive officer of Exnodes.

Acheivements and Publications
Prasanna's 24 patents and 45 publications have earned 1650 citations.

Prasanna has been recognized by the University of Colorado's Outstanding PhD award, U.S. EB-1 Extraordinary Ability Classification, OSA Outstanding Paper Award, SPIE Science and Engineering Award, CPIA Awards, and GCT Coimbatore Gold Medal.

Articles
Research Articles written by Pavani are ,


 * Three-dimensional, single-molecule fluorescence imaging beyond the diffraction limit by using a double-helix point spread function
 * Three dimensional tracking of fluorescent microparticles using a photon-limited double-helix response system.
 * Optimal 3D single-molecule localization for superresolution microscopy with aberrations and engineered point spread functions.