Available — Embedded & Automotive Roles

Malluri Sai Raghu

Embedded Systems Engineer  ·  Android Developer

STM32  ·  ESP32  ·  CAN Bus  ·  FreeRTOS  ·  Embedded Linux  ·  Sensor Fusion  ·  GPS/GNSS  ·  Automotive Safety  ·  EV Systems

Download Resume GitHub Email +91 9963174618
Education
B.Tech EEE
KL University · CGPA 8.72
Training
South Central Railway
6 Months · Electrical Dept
Patent
Published 2025
Sensor Fusion: Campus Robot
Availability
Open
Internship · Graduate · Full-Time
Engineering Profile

Building firmware where hardware meets
real-time constraints.

Embedded Systems Engineer with hands-on hardware and firmware experience across STM32, ESP32, Raspberry Pi 5, CAN Bus, Embedded Linux, and GPS/GNSS sensor fusion. Currently completing B.Tech EEE at KL University (2024–2027), with a prior Diploma EEE from KHIT (2021–2024).

6-month industrial training at South Central Railway's Electrical Department provided exposure to mission-critical infrastructure and safety-grade operational workflows. Published a patent in sensor fusion–based autonomous robotics.

Primary focus: Automotive embedded, Embedded Linux, and EV systems. Secondary capability: Android (Kotlin/Jetpack Compose).

Target industries: Automotive, Semiconductor, EV, and IoT product companies across India and Europe.

Patent Published — Sensor Fusion: Campus Delivery Robot (2025)
STM32 · ARM Cortex-M CAN Bus · UART · SPI · I2C FreeRTOS NEO-M8N GPS Sensor Fusion Embedded Linux Automotive Safety EV Systems
Location Vijayawada, AP, India — open to relocation (India + Europe)
Status Final Year B.Tech — actively seeking roles
Core Platforms STM32, ESP32, Raspberry Pi 5, ARM Cortex-M
Protocols CAN Bus 2.0A/B · UART · SPI · I2C · GPIO · PWM
RTOS FreeRTOS on ESP32 · Real-Time task scheduling
Linux Embedded Linux · Shell Scripting · Device Drivers
Languages C · Embedded C · Python · MicroPython · Kotlin
Target Companies HARMAN · Aptiv · Valeo · KPIT · Bosch · NXP · Continental
Education B.Tech EEE — KL University · CGPA 8.72
Diploma EEE — KHIT (2021–2024)
Engineering Projects

Featured Work

@sairaghu401-cloud

All projects have public repositories. Architecture, protocols, and measurable outcomes are documented.

ESP32 embedded development board
Patent Published
System Architecture
ESP32 (Main Controller)
├─ NEO-M8N GPS ←→ UART
├─ MPU6050 IMU ←→ I2C
├─ HC-SR04 ←→ GPIO
├─ L298N Driver ←→ PWM
└─ Firebase ←→ WiFi
Robotics · GPS/GNSS · ESP32 · Sensor Fusion · Autonomous Navigation

KLNavBot

Autonomous campus delivery robot on ESP32 integrating NEO-M8N GNSS real-time path tracking, MPU6050 IMU orientation, ultrasonic obstacle avoidance, and Firebase cloud telemetry with live dashboard.

<200msSensor Fusion Latency
10HzGPS Update Rate
<0.5mNav Accuracy
Real-TimeFirebase Telemetry
Data Flow
NEO-M8N + MPU6050 IMU + HC-SR04
↓ Sensor Fusion Engine (ESP32 · FreeRTOS)
Waypoint Navigation → L298N Drive + Cloud Telemetry
Fused NEO-M8N GNSS (UART) + MPU6050 IMU (I2C) achieving sub-0.5m navigation accuracy under real-time constraints Collision avoidance logic reacts to dynamic obstacles without halting the delivery path Position data streamed to Firebase Realtime DB over WiFi at 10Hz for live dashboard monitoring Patent filed and published: "Sensor Fusion: Campus Delivery Robot" (2025)
Embedded CMicroPythonESP32NEO-M8N GNSSMPU6050FreeRTOSI2CUARTPWMFirebase
View Repository →
Automotive ADAS sensor system
System Architecture
Raspberry Pi 5 (Host Processor)
├─ VL53L0X ToF → I2C (0x29)
├─ Radar Module → GPIO/SPI
├─ Camera → CSI / USB
├─ ML Inference → Risk Classifier
└─ Haptic Motor → GPIO PWM
Automotive Safety · EV · Raspberry Pi 5 · ML · Sensor Fusion

EV Collision Warning System

Real-time collision warning on Raspberry Pi 5 fusing VL53L0X ToF and radar sensors. ML classifier surpasses threshold-only accuracy. Haptic motor output delivers eyes-free driver alerts — purpose-built for EVs where low acoustic signature makes proximity sensing critical.

20HzSensor Polling Rate
<50msDetection Latency
3 ProfilesLighting Conditions
50msTemporal Filter Window
Data Flow
VL53L0X ToF + Radar + Camera Frame
↓ Sensor Fusion + Temporal Filter (50ms window)
ML Risk Classifier → Haptic Motor Alert
20Hz sensor polling with real-time ML collision risk classification — below 50ms end-to-end latency Cross-validated radar against ToF depth and camera frames, eliminating phantom braking from shadows Temporal filter tracks detection consistency across 50ms windows, suppressing transient false positives Adaptive confidence thresholds tuned across 3 lighting profiles: direct sun, overcast, low-angle glare
PythonRaspberry Pi 5VL53L0X ToFRadarML ClassificationI2CGPIOOpenCV
View Repository →
EV charging station
Data Architecture
Local JSON Dataset (150+ stations)
├─ OSRM Route Engine
├─ Leaflet.js Map Layer
├─ Battery Range Calculator
└─ Cloudflare CDN Deployment
Electric Vehicles · Route Planning · EV Infrastructure · Web

ChargeX

EV route planning and charging optimization platform with smart navigation, battery analytics, and 150+ station database. Zero external API dependencies — all filtering runs client-side. Deployed on Cloudflare Pages CDN.

150+EV Stations
<100msFilter Speed
20–50×Faster vs API-based
ZeroRuntime API Cost
Offline-capable local station dataset — no API calls, no latency, no runtime cost OSRM-powered route planning with battery range estimation and charging stop suggestions 20–50× faster filtering than API-based alternatives; production-deployed on Cloudflare CDN
HTMLJavaScriptCSSOSRMLeaflet.jsCloudflare Pages
View Repository →

Additional Engineering Work

Automotive ECU network
Automotive Networks

CAN Bus Protocol Study

Deep-dive into CAN 2.0A/B, AUTOSAR layered architecture, MCP2515 controller with STM32 integration, and vehicle network diagnostics — targeting automotive-grade embedded development.

CAN BusSTM32AUTOSAREmbedded C
ADAS safety sensor system
ADAS · Sensor Fusion · Computer Vision

ADAS Phantom Braking Mitigation

Cross-validates radar against ToF depth and camera frames before speed intervention. 50ms temporal filter suppresses transient false triggers. Adaptive thresholds across 3 lighting profiles.

RadarToFOpenCVPython
Android development
Android · Kotlin (Secondary)

SmartSpend Finance Tracker

Personal finance tracker in Kotlin with Jetpack Compose, MVVM architecture, Room Database, and spending alerts. Secondary skill demonstrated alongside core embedded work.

KotlinJetpack ComposeMVVMRoom DB
Technical Expertise

Skills

All technologies demonstrated through active projects and public GitHub repositories. No unverified claims.

Core Embedded
C Embedded C ESP32 Raspberry Pi 5 ARM Cortex-M FreeRTOS Real-Time Systems Python MicroPython MATLAB
Automotive & Protocols
CAN Bus UART SPI I2C AUTOSAR Automotive Safety ADAS EV Systems
Navigation & Sensors
NEO-M8N GPS GNSS MPU6050 IMU Sensor Fusion VL53L0X ToF HC-SR04 Ultrasonic Radar Camera/CV
Embedded Linux & Tools
Embedded Linux Shell Scripting Device Drivers System Programming Git / GitHub VS Code Firebase Cloudflare
Secondary: Kotlin · Jetpack Compose · MVVM · Android Studio · Room Database — demonstrated in SmartSpend project
Experience & Education

Timeline

2024 – Present
B.Tech — Electrical & Electronics Engineering
KL University (Koneru Lakshmaiah Education Foundation) · CGPA 8.72
Embedded systems projects with focus on automotive-grade firmware, sensor fusion, CAN bus, and embedded Linux. Building GitHub portfolio targeting ASML, NXP, Bosch, Continental, HARMAN, KPIT.
Nov 2023 – May 2024
Industrial Trainee — Electrical Department
South Central Railway · Vijayawada Division
6-month hands-on industrial training in mission-critical electrical infrastructure, safety protocols, and real-world operational workflows.
2025
Patent Published
Sensor Fusion: Campus Delivery Robot
Filed and published patent for autonomous robot system integrating GPS, IMU, and ultrasonic sensor fusion.
2021 – 2024
Diploma — Electrical & Electronics Engineering
Kallam Haranadhareddy Institute of Technology (KHIT)
2021
Secondary School Certificate
JMJ EM High School

Industrial Training Highlight

Industrial Trainee — Electrical Dept
South Central Railway · Vijayawada Division
Nov 2023 – May 2024
6-month industrial training with hands-on exposure to mission-critical electrical infrastructure and maintenance
Observed live railway electrical operations, safety protocols, and industrial workflows under real operating conditions
Applied EEE classroom theory to real-world electrical infrastructure, bridging academic and field practice
Recruitment

Open To Opportunities

Targeting Embedded Software, Automotive Embedded, Embedded Linux, and EV Engineering roles. Based in India — open to relocation globally including Netherlands, Germany, and international startups.

Target Roles
Embedded Software Engineer Embedded Linux Engineer Automotive Embedded Engineer EV Systems Engineer Embedded Test Engineer Android Developer (Secondary)
Target Companies
HARMAN International Aptiv · Valeo · KPIT ASML · NXP Semiconductors Bosch · Continental AG Demcon · VDL Groep International EV Startups
Location & Availability
Vijayawada, Andhra Pradesh Open to Relocation — India-wide Open to International Relocation Internship & Graduate Roles Full-Time Opportunities
Get In Touch

Let's Build Something Real

Embedded Systems, Automotive Safety, Embedded Linux, EV Technology, or GPS/GNSS? Reach out — I respond promptly.

Download Resume sairaghu971@gmail.com +91 9963174618 LinkedIn GitHub