Individual Research Project: Market study of automotive IoT and telematics for Connected and Automated Vehicles in India
- Landscaping the Indian market space for automotive IoT competitiveness
- Evaluating the ecosystem readiness for 5G-based cellular IoT
- Developing a business model to enter the Connected and automated vehicles market
Embedded Driver Engineer | Qualcomm | Bangalore
- Managed complex workstreams in ADAS application projects resulting in safer processors for major European and Chinese automotive manufacturers.
- Elevated product capabilities by 33% in alignment with the product roadmap, expanding market reach and enhancing the product to meet better safety standards, contributing to improved customer trust.
- Unlocked a $500M global market opportunity in ADAS by spearheading the strategic product validation of a new Snapdragon Ride chipset tailored to the mid-tier automotive segment.
- Improved operational efficiency in the testing process by 99% by automating product performance reporting using Python and C/C++, delivering real-time insights to stakeholders, and driving faster, more informed decision-making.
- Achieved unprecedented code quality metric of 100% code coverage by designing ~400 test cases in a record time of 3 days, elevating consumer’s trust in the product and setting new quality benchmarks.
- Shortened testing timelines by 480x by integrating an automation tool into global processes in collaboration with cross-functional stakeholders across 3 countries simultaneously, resulting in sustainable planning efficiency and efficacy.
- Eliminated 75% regressions by mentoring a team of 15 on the best software development practices for audits and methods to maintain traceability of requirements till delivery, saving a significant amount of rework costs.
- Improved delivery timelines by 20% by leveraging tools like Excel, JIRA, DevOps, and Workfront for efficient project management in an Agile environment following the Scrum methodology.
Computer Vision Engineer | Tata Elxsi | Pune
- Designed and implemented complex vision systems to improve embedded products’ robustness and efficiency using state-of-the-art AI models and innovative algorithms for top global medical and food safety technology companies.
- Enhanced process efficiency of a microbiological test by 99.8% with the help of customized AI models.
- Generated an additional revenue of $70K by innovatively solving a common user complaint and resolving project stagnation.
- Improved client satisfaction score by 25% through cross-functional stakeholder management, and timely pitching of strategies and results to Fortune 500 clients.
- Designed compensation algorithms and strategically sourced a critical electronic component that reduced adverse temperature effects by ~30%, enhancing AI model accuracy and product usability.
- Achieved 99.9999% accuracy for an AI model by developing innovative processing strategies within an inference time of 0.5s.
- Achieved 93% accuracy in classification-based AI models by designing complex vision algorithms in Python and C/C++.