Embedded Systems & Electrical Engineer · EV Powertrain · Motor Control · Nanotechnology
🎓 B.Tech EEE — Amrita Vishwa Vidyapeetham | Erasmus Scholar — Grenoble-INP Phelma, France 📄 2× IEEE Published Researcher — IPMSM Demagnetization Fault Detection (FEA + ML) 🔧 Robert Bosch · Schneider Electric · AInsurCo (Database Architect) 🎯 Targeting: Embedded Systems · PCB Design · Automotive Electronics · Power Electronics · Semiconductor Hardware · EV Powertrain Engineering
- ⚡ Developed and validated Embedded C firmware modules for CAN communication on live HV testbeds at Robert Bosch — analyzed 100+ CAN frames using CANalyzer across EV benchmarking infrastructure and VCU interfaces
- 🧲 Authored 2 IEEE papers on IPMSM demagnetization fault detection combining Finite Element Analysis (ANSYS Motor-CAD) with machine learning
- 🧪 Completed Erasmus Exchange in Nanotechnology at Grenoble-INP Phelma — coursework in Advanced CMOS, VLSI, Spintronics, Semiconductor Physics, Nanoelectronics
- 🗄️ Currently designing relational database schemas, SQL architectures, and Python automation at AInsurCo (London, Remote) while actively building embedded hardware, PCB design, and power electronics projects for my engineering portfolio.
- 🌍 English (C1 · IELTS 7.0) · Tamil (Native) · Telugu (Native) · Deutsch (A1 · Goethe)
| Year | Title | Venue |
|---|---|---|
| 2025 | Demagnetization in V-shaped IPMSM: A Fusion of Finite Element Analysis and Machine Learning | IEEE CONECCT 2025 |
| 2025 | Machine Learning-based Analysis on Non-uniform Demagnetization Fault in IPMSM Using FEM | ICPERS 2025 |
| Project | Stack | Highlight |
|---|---|---|
| 🔋 Li-Ion Battery Protection PCB | KiCad 9 · LTspice · PCB Design · Gerbers | Designed a manufacturing-ready 90 × 40 mm PCB featuring reverse-current protection, battery voltage monitoring, ground plane optimization, DRC verification, LTspice simulation, Gerber generation, and complete engineering documentation. |
| ⚡ IPMSM Demagnetization Fault Prediction | ANSYS Motor-CAD · Python · Machine Learning | Developed machine learning models using FEM-generated datasets across multiple demagnetization severity levels for EV traction motors. |
| 🔋 SOH Prediction — LiFePO₄ Batteries | Raspberry Pi 4 · Python · ML | Built a regression pipeline to estimate battery State-of-Health from charge/discharge cycles for Battery Management Systems. |
| 🖥️ 32-bit RISC Processor Subsystems | Verilog · Vivado | Designed and verified ALU, Register File, and Data Memory modules for FPGA implementation and performance comparison. |
| 🎲 MTJ-based Random Number Generator | Python · Stochastic Modelling | Simulated stochastic magnetic tunnel junction switching for low-power embedded security applications. |
- 🔋 Designed a complete manufacturing-ready PCB using KiCad 9
- ⚡ Created professional electrical schematics following industry practices
- 📐 Optimized PCB component placement and manual routing
- 🌐 Implemented copper ground planes and power/signal net classes
- 🧪 Verified designs using ERC, DRC, LTspice simulation, and Gerber Viewer
- 📦 Generated fabrication-ready Gerber, Excellon Drill, BOM, and engineering documentation
- 🔧 Experienced with Embedded Hardware, Automotive Electronics, Power Electronics, and Electronic Prototyping
🔋 Li-Ion Battery Protection PCB
A manufacturing-ready PCB designed using KiCad 9, featuring reverse-current protection, battery voltage monitoring, LTspice simulation, Gerber generation, fabrication package, engineering documentation, and GitHub-ready project organization.
➡️ Repository:
https://github.com/imguxuuuu/Battery-Protection-PCB
"Engineering intelligence from atomic lattices to embedded systems, power electronics, and scalable hardware."