ROOT NODE

Rahul Nerella

Embedded Systems & Hardware Engineer // RISC-V, FPGAs, IoT and edge ML.

activeVellore, IndiaRahulnerella86@gmail.com
SYSTEM STATUS
  • Role: Embedded Systems & Hardware Engineer
  • Location: Vellore, India
  • Status: active

SECTION 01

System Overview

ABSTRACT

Electronics and Communication Engineering student at VIT Vellore with hands-on experience in embedded systems, automotive sensor integration, and hardware-software co-design. Passionate about ADAS, VLSI, and building intelligent edge devices. Targeting placement/internship roles in embedded, automotive, and semiconductor domains.

EDUCATION

VIT Vellore

B.Tech, Electronics and Communication Engineering

2024 - 2028CGPA: 8.1 | Reg: 24BEC0071

GT Aloha Vidhya Mandir, Chennai

High School

2022 & 202410th: 90% | 12th: 89%

SECTION 02

Node Types

LANGUAGES(6)
  • C
  • Embedded C
  • Python
  • Verilog
  • MATLAB
  • JavaScript
MICROCONTROLLERS(5)
  • STM32 (U5/F4)
  • PIC32CM
  • ESP32
  • Arduino
  • 8051
PROTOCOLS(6)
  • I2C
  • SPI
  • UART
  • CAN
  • BLE
  • LoRa
TOOLS & IDEs(7)
  • KiCAD
  • PlatformIO
  • Keil µVision
  • STM32CubeIDE
  • Icarus Verilog
  • Xilinx FPGA
  • NI MAX
FRAMEWORKS(4)
  • FreeRTOS
  • TinyML (TFLite Micro)
  • PySpice
  • Streamlit
ADAS / HIL(4)
  • OxTS NCOM
  • Bosch BHI360
  • Sensor Fusion
  • HIL Test Bench

SECTION 03

Operational History

Valeo

ADAS Sensor Integration Intern (anSWer Division)

Summer 2026active

Integrated Bosch BHI360 IMU and Volvo camera modules into ADAS validation pipeline. Developed C drivers for I2C/SPI communication with IMU peripherals. Parsed OxTS NCOM binary telemetry and Bosch BHI360 binary data in Python to extract roll/pitch/yaw, acceleration (x/y/z), and GNSS data. Built calibration and benchmarking framework comparing BHI360 with OxTS INS (xNAV650) for production replacement feasibility. Performed HIL (Hardware-in-the-Loop) testing and sensor data validation across dynamic scenarios. Set up Dell 7280 servers with NI Workbench and worked with NI PXIe-1085 using NI MAX software. Worked on flashing ECUs with software for cameras and sensors for ADAS systems in Volvo Trucks. Completed short training in EV charger processes, power systems, and Electronic Processing Unit (EPU) design.

Embedded SystemsAutomotiveSensor ValidationIMUPythonHIL

SECTION 04

Selected Modules

All modules

An advanced, open-source health monitoring smart ring built on the ESP32 Mini. It uses a PPG sensor (MAX30101) and an IMU (MPU6050) to measure extensive physiological and kinetic data. Processing happens entirely on the edge using TinyML models (TensorFlow Lite Micro). Features include Vitals tracking (Heart Rate, SpO2, HRV, Stress Index), Activity monitoring (Step Counter, Fall Detection), and TinyML inference for Sleep Staging, Gesture Recognition, and HR Anomaly Detection.

ESP32TinyMLBluetoothC++

Built wearable platform using STM32U5 microcontroller with FreeRTOS task scheduling. Integrated heart-rate, step-counter, and ambient light sensors over I2C/SPI. Designed MIPI DSI round-display UI using STM32U5G9J-DK1 Discovery Kit and NeoChrom GPU. Implemented low-power modes (Stop 2 / Standby) achieving multi-day battery life.

STM32FreeRTOSCMIPI DSI

An Arduino-controlled 6 Degrees of Freedom (6DOF) robotic arm that uses a rotary encoder and three push buttons for manual servo control. Features intuitive button navigation for joint selection and precise angle adjustment. Replicates human-like motion using six servo motors. (Also developed a PIC32CM LS00 version which won 2nd place at Microchip Designathon 2026).

ArduinoPIC32RoboticsC++

A complete single-cycle RV32I-style RISC-V CPU written in Verilog. Implemented the full ISA including ALU, register file, data/instruction memory, and control unit. Functional simulation with Icarus Verilog + Verilator; synthesis with Yosys. Completed OpenLane / Sky130 ASIC flow: floorplan, placement, routing, DRC/LVS clean. Built two variants: a Verilog version driven by testbench input, and a Python/localhost webpage version with user input.

VerilogRISC-VOpenLaneASICPython

An IoT-based safety solution to monitor firefighters in real-time during hazardous operations. Integrates health monitoring (heart rate, temperature), environmental sensing (MQ gas sensors, flame sensor), location tracking (GPS NEO-6M), and long-range communication (LoRa SX1278). Features Edge AI (TinyML) for fall detection, activity recognition, and air quality classification.

LoRaESP32TinyMLIoTSensors

SECTION 05

Auxiliary Inputs

HACKATHONS & COMPETITIONS
  • 2nd PlaceMicrochip Designathon 2026: IMU gesture-controlled 6-DOF robotic arm
  • 1st PlaceCSI Club Hackathon 2025: AI recruiting platform concept
  • 3rd PlaceAI GENhack, VIT Gravitas 2025: AI comic generator
  • Top 10ECE Annual Hackathon 2025: FPGA-based 4-DOF robotic arm
CERTIFICATIONS
  • Embedded Engineering: Embedded C (EDUCBA), IoT & Embedded Systems (UC Irvine), Arduino Programming (UC Irvine)
  • Hardware & VLSI: Digital Design in VLSI (L&T EduTech), Computer Architecture (ARM), Semiconductor Devices 1 & 2 (KAIST), Micro:bit (ARM)