.png)
.png)
.png)
.png)
.png)
.png)
.png)
Define what should be built
Understand the real problem, technical constraints, user need, and evidence required before choosing the system to build.
I work across AI/ML, engineering software, scientific computing and simulation, and connected hardware—taking complex problems from definition through coordinated execution, validation, and delivery.
- Based in
- Bengaluru, India
- Working across
- Deeptech products · AI/ML · engineering software · simulation · connected hardware · technical execution
Selected recognition
- IIT Roorkee Department Gold Medal
- NIDHI-PRAYAS grant
- DST-supported Slush Finland delegation
- Patent and published research
Selected work
Technical ventures, products, and systems built for real use.
Selected work across deeptech products, engineering software, AI/ML, simulation systems, synthetic data, and connected hardware.
Recent work and milestones
What I have been building, testing, and advancing.
Recent work across deeptech ventures, product development, technical programmes, engineering software, AI/ML, simulation, research, and publications.
Three connected parts of the work.
Build and coordinate the technical system
Bring together computation, software, hardware, research, and collaborators to turn the definition into a working capability.
Validate, deliver, and improve
Test against real requirements, deliver usable outcomes, and strengthen the product through evidence and iteration.
Technical foundation
Engineering depth behind the products and programs.
A foundation in simulation, scientific machine learning, engineering software, computational engineering, 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 deeptech ventures, products, and programs.
More about my journeyEngineering and computational research
Mechanical engineering, nanotechnology, numerical methods, multiphysics simulation, and scientific computing at IIT Roorkee.
Co-founding a deeptech engineering company
Owning technical products and programs across engineering software, AI/ML, scientific computing, and simulation for international customers and R&D collaborations.
Co-founding a connected hardware–software product
Leading product development across pressure and motion sensing, embedded systems, analytics, software interfaces, and healthcare applications.
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 deeptech venture building, technical products, and complex engineering systems.
My foundation in mechanical engineering, numerical simulation, and scientific computing expanded into solver development, AI/ML, engineering software, connected sensing systems, and venture building. The common thread is turning difficult technical problems into reliable capabilities, tools, and products.
Let’s talk about what you’re building.
I’m open to conversations around deeptech products, technical product roles, technical program and project leadership, AI/ML, engineering software, and connected hardware–software systems.