My Work

I specialize in leading complex, cross‑functional engineering and transformation programs across the automotive and mobility ecosystem.

What I Do

I help global automotive and mobility organizations accelerate their transformation into software‑defined, data‑driven, and safety‑centric enterprises. My work sits at the intersection of engineering, strategy, and leadership — turning complex technical challenges into scalable, repeatable, and business‑aligned solutions.

Software Defined Vehicle

I lead SDV transformation programs that unify architecture, tooling, and supplier ecosystems. My focus is on building platforms that reduce complexity, increase reuse, and enable faster, safer feature delivery across vehicle lines.

AI Development

I integrate AI‑driven insights, automation, and decision‑support models to improve development velocity, quality, and cross‑platform consistency.

Functional Safety

I guide organizations in building safety‑critical systems that meet global standards. My work spans across Functional Safety (ISO 26262)

Cybersecurity

I help teams embed safety and security into the development lifecycle — not as checkboxes, but as strategic enablers of trust and reliability focused on meeting ISO/SAE 21434

Standardization

I architect advanced benchmarking and evaluation frameworks that bring structure and transparency to ECU development.

New Frameworks

I design and implement new frameworks that solve complex, cross‑functional challenges.

My Latest Innovations

Cloud-native Architecture

Cloud to Edge implementation of Automotive features built using AWS Graviton EC2 instance deployed on NXP iMX8 hardware.

Conversational AI

Enhanced in‑vehicle Conversational AI capabilities by introducing a natural‑language–driven climate‑control system built on the NVIDIA toolchain and AWS cloud services. The solution integrates NVIDIA NIMs with Cognizant’s AWS‑based architecture running on EC2 G‑series instances powered by Arm v8. Using advanced ASR pipelines, the system converts driver voice commands into precise text outputs, which are then translated into CAN messages for seamless, hands‑free actuation of climate functions—improving usability, safety, and overall driving experience.

ECU Virtualization

Virtual validation is a process in which we create Virtual ECU (VECU) that enables developers to test ECU software early in the development phase within a desktop-based environment. Traditional ECU testing depends on costly, late-available hardware prototypes with incomplete software, delaying issue detection and increasing R&D costs. This ECU virtualization approach helps identify integration issues early, enhances software completeness, reliability and provides a scalable, efficient and reliable testing enviornment.

Gen AI Based Test Case Generation

Test case writing is a time-consuming aspect of validation activities, often prone to manual errors. Ensuring comprehensive test coverage and maintaining traceability are persistent challenges. By harnessing the power of LLMs, we can streamline the test case generation process, thereby reducing the likelihood of errors and enhancing overall efficiency.

Voice AI-Powered Seat Massage Experience

Developed an innovative Voice‑AI–driven solution that integrates Sensory’s speech capabilities with Gentherm’s seat‑control module. Built on advanced NLP tools, the system enables seamless, hands‑free actuation of seat functions, enhancing both safety and occupant comfort by eliminating the need for manual interaction.

AI-Driven Analytics for Safety Applications

Led the development of industry‑first AI frameworks leveraging Kleidi AI on ARM‑based platforms with the SOAFEE architecture, delivering a 15% boost in inference accuracy and a 20% reduction in latency for real‑time decision‑making. These advancements directly enhanced system safety, operational predictability, and overall vehicle performance. Designed and deployed an automotive TPMS solution using PyTorch, vLLM, Qwen, LLaMA3, and custom Python/Pandas pipelines to enable predictive AI analytics and early‑warning insights for safer, more reliable vehicle operation.

Digital Twin

Championed the adoption and integration of the Siemens PAVE360 toolchain to build high‑fidelity digital twins for system‑of‑systems verification and validation in ADAS and Autonomous Vehicle programs. Designed an architecture that leverages PAVE360 Backplane, ANA, and PreScan components to seamlessly connect perception, planning, annotation, and decision‑making clients within a unified simulation environment. Developed advanced ADAS applications—including Intelligent Speed Assist, Adaptive Cruise Control, and Automatic Emergency Braking—that accelerated validation cycles and enabled a true shift‑left methodology for safer, more predictable, and scalable vehicle development.

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