Scientific Computing, Modeling & Simulation
Savitribai Phule Pune University

Research & Consultancy

Multidisciplinary expertise under one roof!

Collectively, SCMS-SPPU possesses expertise in diverse computational areas such as
  • Machine learning, statistical learning, data science
  • Statistical data modeling & analysis
  • Data-intensive decision support and research
  • Computational epidemiology
  • Complex systems & network science
  • Scientific computing and large-scale numerics
  • Monte Carlo methods
  • Computational physics and materials modeling
  • Industrial and applied mathematics
  • Cryptography
  • Digital signal & image processing
  • Computational fluid dynamics
  • Defence ballistics
  • Free software
For consultancy enquires, please write to
«coordinator AT»

Broad research areas

Publications, preprints, technical reports

Computational Epidemiology

Covid19 Modeling (Snehal Shekatkar, Bhalchandra Pujari): Please visit our Covid19 modeling and Pune 2020 forecast portals.
Covid19 Forecasts for Pune (2020)

Complex Systems
Image Courtesy: Snehal Shekatkar

Complex Systems

Network Science (Snehal Shekatkar): Real-world systems that are composed of many interacting units, such as social networks, transportation networks, world-wide web, metabolic networks. Real-world phenomena such as traffic jams, spread of rumours, epidemics and riots, opinion formation and polarization in social networks, etc.

Statistical Science, Data-Intensive Science, Machine Learning

Astrostatistics, etc. (Mihir Arjunwadkar): Development (or: apt and meaningful use) of statistical and computational methodologies for data-intensive science. Current and past focus areas include genomic sequence analysis, areas of astrostatistics such as CMB data analysis, pulsar astronomy, compressed-sensing methods for radio astronomy, etc.

DSP/DIP & Machine Learning (Bhalchandra Gore): Automated identification of voice, gender, features, handwriting recognition for use in congitive detection systems.
Statistical Science
Image Courtesy

Materials Modeling
Image Courtesy: Bhalchandra Pujari

Computational Materials Science and Materials Modeling

Ab initio and other approaches (Vaishali Shah, Bhalchandra Pujari, Ankita Katre): Centre has an long-standing, intensive research programme in computational materials science Using the state-of-the-art techniques, electronic and atomistic properties are investigated to gain macroscopic insights from microscopic point-of-view. From graphene to quantum dots and from semiconductors to random alloys, the members of this group have a long history of working at the cutting edge of materials science.

Industrial and Applied Mathematics

Computational Fluid Dynamics, Defence Ballistics, etc. (Sukratu Barve)

Cryptography and Optimization (Smita Bedekar): Measuring security strength of cryptographic keys (in terms of time for breaking) using discrete mathematics and boolean satisfiability.
Image Courtesy

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