|Phone:||+49 711 685-67721|
|Fax:||+49 711 685-63658|
|Email:||ganesh _at_ icp.uni-stuttgart.de|
Institute for Computational Physics
My research involves computational modeling of solid state devices / materials for next generation label free DNA sequencing (and proteomics ) on High-performance computers. The device simulations are performed with the framework of Density functional theory (DFT) combined with Non-Equilibrium Greens Function (NEGF) Formalism. In addition, I am interest in the application of Machine learning to Nanotechnology and Materials modeling.
- Nucleobase interactions with lower diamondoids.
- The solid state device simulation involves gold electrodes embedded with diamond caged molecules (i.e. Diamondoids) for tunneling based electric DNA sequencing devices .
- Mutation and methylations detection
- Material modeling of Semiconducting (2H) / metallic (1T) phase in MoS2 monolayer for novel nanoscale bio-sensing application.
- Machine learning based molecular classifier : coulomb matrix has been developed as a feature to map and predict molecular properties. I aim to implement a molecular classifier based on sorted coulomb matrix. Implementation is done with Apache Spark (Python API) and machine learning is performed with the Spark built in MLlib.
publications → here.
"Effect of The Protein Electric Field on The Spectral Tuning Of A Photosynthetic System" (267 KB), 2012, CBBC Group, Sapienza University of Rome, Italy.