Celeste Valambhia

• Developing an LSTM time series model for the prediction of SoH based on drive-cycle data of the hybrid cars having a 48V flat-pack system. • Instead of relying on laboratory aging data, the current state of the art involves using real-world drive-cycle based battery aging dataset for state estimation.

Involvement in expanding the test automation. Automating the generation of reports and developing and maintaining scripts for fetching the ECU and signal information from Vehicle measurements. Developed a testing toolchain and test script generation tools, scripts for CICD pipeline, coordinating with international teams. Created scripts on Azure Databricks utilizing PySpark APIs for extracting DTC error codes from Kurztest reports for further analysis.

• Understanding various Software requirements of the product, concept generation, development of applications, programming, integration of interfaces, and bring-ups on various ARM-Based Processors • Customize Operating Systems based on Yocto Linux and AOSP for Qualcomm Processors • Proficiency in customizing BSP, kernel code, device drivers, and HAL code • Experience in version control, and release management using semantic versioning • Expertise in debugging, optimization, testing, and documenting the same

Specialization in Embedded Systems