I am focusing on building a strong Digital R&D program in close collaboration with Shell's research centre in Brazil. The digital R&D program in Brazil leverages external ecosystem partners such as academia as well as industrial collaborations. The scope of the program spans subsurface, mid-stream as well as downstream Digital R&D.

In my this role, I lead Scientific Image Analysis and Simulations (SIAS) team at Shell Technology Centre Bangalore. I seeded a capability centre to leverage step-ups in scientific imaging and mesoscale simulation techniques to derive insights about porous materials encountered Shell. Porous materials are ubiquitous in energy industry e.g. hydrocarbon bearing sedimenraty rocks, porous catalysts for speeding up reactions and materials used in batteries such as membranes, electrodes to name a few. We developed industry leading methods to analyze electron micrographs of catalysts, 3D CT scanned images of reservoir rocks, photographs of metallic corrosion in assets and lubricant characterization. Scientific Imaging Analysis was complemented with simulations and modeling for extracting actionable insights from experiments for making better materials and processes. SIAS capability grew with support from strategic partnerships with multiple academic and industrial partners. ILead the deployment of scientific software on cloud computing environment for the first time in Shell. We have developed DIRAC, first high performance computing platform in Shell for scientific computing. DIRAC allows us to scale scientific simulations on demand while bringing simulations and image analysis in the hands of our experimental partners to accelerate research.Representative publications from this capability centre-"Siamese-SR: A Siamese Super-Resolution Model for Boosting Resolution of Digital Rock Images for Improved Petrophysical Property Estimation"IEEE Transactions on Image Processing, vol. 31, pp. 3479-3493, 2022, doi: 10.1109/TIP.2022.3172211."References and benchmarks for pore-scale flow simulated using micro-CT images of porous media and digital rocks" Advances in Water Resources, VOl 109, 211 (2017)."Renormalization group theory outperforms other approaches in statistical comparison between upscaling techniques for porous media" Physical Review E 96 (3), 033313.

Led a team focused on developing simulations for surfactant screening in enhanced oil recovery applications. We developed and validated coarse grained molecular simulations for estimating interfacial properties of microemulsions of hydrocarbon-water-surfactant. These methods were developed in multi year partnerships with University of Leiden and and a start-up Culgi B.V.Representative publication - Langmuir 2013, 29, 7, 2136–2151,

As part of a nascent Computational Chemistry team of 5 staff, I was tasked with developing proof of concepts for Computational Chemistry methods in various areas of Shell business. Demonstrated workflows for physics based insights for accelerating research in Catalyst development, Fuels and Lubricants property prediction using density functional theory and molecular dynamics simulations.Leveraged academic partnership with Indian Institute of Sciences and Jawaharlal Nehru Centre for Advanced Scientific Reserach for accelerating capability development in Shell.

I was part of a small team of Computational Chemistry expertise group. As a team we delivered methods for screening materials for gas sensing applications, composite membranes for CO2 separation and special additives in polymers. We implemented computational physics protocols for quantume mechanical simulations and then experimentaly validate the same.Representative publication"Composite membrane for separation of carbon dioxide" US Patent 7811359

As part of the technology team of G.E. Plastics business, I was part of an advanced composites research team. I was part of a team developing thermoplastic composites for magnetic and thermal applications. This was a fun journey with a lot of learning in the domain of polymer processing. Got my exposure to the principles of Design of Experiments through Six Sigma rigour.Representative PatentsThermally Conducting and Electrically Insulating Moldable Compositions and Methods of Manufacture Thereof US Patent 6872325Polymeric resin bonded magnets US Patent 6872325