.png)
.png)
.png)
.png)
.png)
.png)
Build computational systems
Numerical solvers, simulation workflows, synthetic-data pipelines, scientific machine-learning models, and validation methods.
I build as a
I work across numerical simulation, scientific machine learning, solver development, engineering software, and research-led products.
- Based in
- Bengaluru, India
- Working across
- Simulation, SciML, and engineering software
Selected recognition
- IIT Roorkee Department Gold Medal
- NIDHI-PRAYAS grant
- DST-supported Slush Finland delegation
- Patent and published research
Selected work
From computational models to usable engineering products.
Selected work across numerical simulation, scientific machine learning, solver development, synthetic data, engineering software, advanced materials, and sensing systems.
Recent work and milestones
What I have been building, testing, and advancing.
Recent work across simulation, scientific machine learning, engineering software, product development, research, publications, and technical programmes.
Three connected parts of the work.
Translate them into engineering tools
Engineering software, analysis workflows, interfaces, automation, and decision-support systems built around real technical use cases.
Integrate products where needed
Sensing hardware, embedded systems, prototypes, and hardware–software integration when the problem requires a physical product.
Technical focus
Engineering domains and computational interests.
Work across thermal and thermomechanical analysis, computational mechanics, scientific machine learning, solver development, optimisation, and semiconductor systems.
See the projects01Multiphysics simulationThermal,
thermomechanical, electromagnetic, structural, dynamic, optimisations and coupled-physics studies for
complex engineering systems.
02Scientific machine learningSimulation-driven
datasets, surrogate and operator-learning models, inverse problems, reduced-order modelling, and
physics-aware validation.
03Scientific softwareCustom solver
development,
automated simulation pipelines, mesh and data-generation workflows, post-processing, engineering
software, and scientific tools.
04Computational engineering across
industriesApplied modelling and analysis for semiconductors, automotive systems, aerospace
and space applications, defence, energy systems, and advanced materials.
Engineering research became the foundation for simulation, software, and products.
More about my journeyEngineering and computational research
Mechanical engineering, nanotechnology, numerical methods, multiphysics simulation, and scientific computing at IIT Roorkee.
Simulation and scientific-computing systems
Building custom solvers, simulation pipelines, synthetic-data workflows, scientific machine-learning systems, and engineering software for complex technical problems.
Sensing and movement analytics
Developing a connected product around pressure sensing, embedded electronics, gait analytics, software interfaces, and customised insoles.
Writing about simulation, scientific machine learning, engineering software, and technical products.
First-order vs higher-order finite elements
How mesh density, polynomial order, geometry, and solution smoothness affect accuracy and computational cost.
Where physics enters operator-learning workflows
How problem formulation, data, architecture, constraints, and validation preserve physical behaviour.
Best Practices for Running Simulations on Google Cloud: Lessons in Cost Management
Practical lessons for controlling cloud costs while running FEniCS simulations and simulation-driven data-generation workloads.
Physical systems
Computation
Evidence
Product building
I work at the intersection of computational science, engineering software, and product development.
My background began in mechanical engineering, numerical simulation, and scientific computing. That work expanded into solver development, scientific machine learning, engineering software, sensing systems, and venture building. The common thread is using computation to understand physical systems and turn technical capability into reliable engineering tools and products.
Let’s talk about what you’re building.
I’m open to conversations around engineering simulation, scientific machine learning, numerical solvers, engineering software, sensing systems, and research-led products.