Centre for Informatics : Centers & Institutes : Shiv Nadar University
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Center for Informatics

Informatics is the science of information, information processing, and the study of structures, algorithms, behavior, and interactions of natural and artificial systems that store, process, access and communicate information. The science of informatics thus overlaps a wide range of disciplines.

 

The Center for Informatics was founded under the aegis of the School of Natural Sciences (SoNS), Shiv Nadar University. Informatics is the science of information, information processing, and the study of structures, algorithms, behaviors and interaction of natural and artificial systems that store, process, access and communicate information. The science of informatics thus overlaps a wide range of disciplines. The center also encompasses research - linking different subject areas and fields.

Specific research programs and areas in the Center are set by the individual faculty, who nucleate inter-disciplinary research in select areas, exploiting synergies between overlapping programs in one or more schools the University. The current research focus includes Bioinformatics and Cheminformatics; Computational Nanoscience; Design of Organic Dyes and Organic / Polymer Semiconductors.

To know more on the Center and its activities, please contact:

Dr. N. Sukumar - n.sukumar@snu.edu.in

Head, Center for Informatics

Conference Presentations

  • N. Sukumar, Michael P. Krein, “Mapping Chemical and Biological Networks using Molecular Fragments and Fingerprints” CHI Structure-Based Drug Design conf., Cambridge, MA, June 2012
  • Ganesh Prabhu, Sudeepto Bhattacharya, Michael Krein, N. Sukumar, “Network measures in polymer space” First National Conference on Mapping the “Materials Genome”, Shiv Nadar University, India, March 8-10, 2013

Arpan Krishna Deb

Research details
Materials Modeling for MIEC Access Diodes
– Analyzing the successful working mechanism of certain materials as access diodes.
– Predicting and designing new materials which can be used as MIEC access diodes.
A patent has been filed from IBM on a material with tunalbe band gap for tunable voltage margin when used as access diodes.
A paper (confidential) in collaboration with the experimental transport results, submitted to VLSI conference.

Magus

Computational facilities include a high performance IBM cluster (“Magus”) consisting of 63 compute nodes (1008 cores) with a total capacity of 30 TF of Theoretical Peak Performance, plus 8 nodes with high-end CPUs. Additionally, several Linux workstations are used for teaching as well as research purposes. Software for bioinformatics and cheminformatics, molecular modeling, molecular dynamics, quantum chemistry, data analysis and statistical learning are also available.

Niteesh Sahni

Niteesh has 15 years of teaching experience in pure and applied mathematics at undergraduate and graduate level. He works in Functional Analysis and Dynamical systems. The highlight of his research has been to settle an open problem in Hardy-Hilbert spaces. Presently, he is involved in solving problems related to invariant subspaces of Bergman spaces, BMOA, and vector valued Hardy spaces.

Journal Publications

  1. Ganesh Prabhu, Sudeepto Bhattacharya, Michael P.Krein, N. Sukumar, Investigation of similarity and diversity threshold networks generated from diversity-oriented and focused chemical libraries, J. Math. Chem. (in press) 2016. DOI: 10.1007/s10910-016-0657-0

Priya Johari

Dr Priya Johari has joined Physics department of SNU in 2012. She obtained her Ph.D. degree in Physics from I.I.T. Bombay in 2006 and master degree in physics from Jai Narain Vyas University, at Jodhpur, Rajasthan, in 2001. Just after submitting her Ph.D. synopsis, she joined as a post-doctoral research assistant at University of Leoben, Austria (2006-2008) in the Department of Material Science. Between 2008-2009, she worked in the Department of Physics at I.I.T.

N. Sukumar

My research uses computational and cheminformatic methods for the design of drug-like molecules, polymers and nanomaterials with specific chemical and biological properties, and the development of cheminformatics software and network measures for moleclar design. Current research interests include analysis of chemical space networks and application of machine learning in chemistry. I have also worked on the development of novel molecular descriptors and robust property modeling methods for the prediction and interpretation of protein-ligand binding and protein similarity classification.

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