Assistant Professor (RESEARCH INTERESTS: Heterogeneous and High Performance Computing, Computational and Systems Biology, Mathematical Systems Theory, Modeling and Optimization, Quantum Computing Information and Control)
This course covers the principles and theory of programming-in-the-large. The phases of software development, requirements development, software design software coding, and module testing, and software verification will be discussed in detail. Documents, rapid phototyping, top down, bottom up, successive refinement, functional and data abstraction will be discussed. Black and white box testing methods will be covered. Hierarchical and democratic term organization structures and the effects of personalizing and group dynamics will be discussed.
A participating seminar on topics of current interest and importance in Computer Engineering
Schaefer School of Engineering & Science
Electrical and Computer Engineering
Electrical Engineering / Computer Engineering
Research & Education
Ph.D - Electrical and Systems Engineering, Washington University in St. Louis, Dec 2006.
M.S - Systems Science and Mathematics, Washington University in St. Louis, Dec 2002.
B. Tech - Electrical Engineering, Indian Institute of Technology, Kharagpur, May 2000.
High Performance Computing, Heterogenous and Massively Parallel Architectures
Computational Biology and Bioinformatics
Mathematical Modeling and Optimization
Quantum Information and Control
Experience & Service
Dec 2006 - Nov 2007- Research Associate at the Washington University School of Medicine
Dec 2007 - Dec 2009 - PostDoctoral Research Associate at Washington University, Dept. of Computer Science and Engineering
Dec 2007 - Dec 2009 - Adjunct Faculty at Washington University, Dept. of Electrical and Systems Engineering.
Jan 2010 - Jul 2010 - Senior Research Scientist at the University of Delaware, Computer and Information Sciences Dept.
Dr.Ganesan received his Ph.D from Washington University in St.Louis, department of Electrical and Systems Engineering, Dec 2006. His dissertation was on Quantum-Information and Decoherence free Quantum-Computation, in order to advance Quantum Computing a step closer to reality. The framework developed during his research can now be applied to all Quantum systems including the practical Optical Cavity Electro-Dynamic System in order to perform error free Quantum Computation.
From 2006-2007, he was a research associate at the Washington University, School of Medicine, where he worked on mathematical modeling of neuronal systems and their response to visual and vestibular stimuli, which helps explain and predict the perception of signals by the brain. From 2007-2009, he worked at the Department of Computer Science and Engineering at Washington University as a post-doctoral researcher and Adjunct faculty. His work primarily focused on Hybrid Computing on heterogeneous platforms, such as FPGAs, Graphics Processing Units(GPUs) and multi-core processors. The goal of the research was to effectively utilize various computing architectures for scientific data and compute intensive problems. As different architectures play different roles in High Performance Computing, finding the right set of platforms to deploy a specific application involves both redesigning the algorithm to the underlying architecture as well as tailoring the hybrid platform to the problem.
From 2010 to 2011 as a senior research scientist, he was the lead behind the development of an optimized Molecular Dynamics simulation package implemented on GPUs, at the University of Delaware. The study benefits several high-impact applications such as drug-design, protein-ligand interaction and multi-scale modeling. The algorithmic redesign accompanied with sophisticated acceleration techniques specifically designed for the massively multi-core platform delivers highly competitive performance. The software suite, is available to Chemists and Biologists for free in order to further scientific progress in related fields.