faculty-profile

Narayan Ganesan

ASSISTANT PROFESSOR (RESEARCH INTERESTS: HETEROGENEOUS AND HIGH PERFORMANCE COMPUTING, COMPUTATIONAL AND SYSTEMS BIOLOGY, MODELING AND OPTIMIZATION, QUANTUM COMPUTING INFORMATION AND CONTROL)
Building: Burchard
Room: 412
Phone: 2012168057
Email: nganesan@stevens.edu
Website
School:  Schaefer School of Engineering & Science
Department:  Electrical and Computer Engineering
Program:  Electrical Engineering / Computer Engineering
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.



 

Research

High Performance Computing, Heterogenous and Massively Parallel Architectures

Computational Biology and Bioinformatics

Systems Biology

Mathematical Modeling and Optimization

Quantum Information and Control

Quantum Computing

 

General Information

 

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. 

Appointments

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.

Professional Societies

Member IEEE

Member ACM

 

Courses
  • CPE 640 Software Engineering I
  • CPE 810 Special Topics in Computer Engineering