STATUS: ACTIVE IN QUEUE

RAJESH SAHU

CLASS: AI_ML_ENG_V1.3
LEVEL 23

Electronics & Telecommunication student at Pune. Designing robust ML models, custom computer vision deployments (YOLOv8/OpenCV), and hardware-in-the-loop edge integrations.

[ INVITE_TO_PARTY ] [ DOWNLOAD_SAVE_FILE ]
LINK_SLOTS:
USER_SPECIFICATIONS

Character Attributes & Stats

Blending intelligence with real-world edge hardware.

Driven by curiosity and a love for building, I blend software engineering with AI/ML to create solutions that don't just work — they adapt, scale, and solve real problems. From writing modular code in Python, Java, and C++ to experimenting with computer vision frameworks like YOLOv8 and OpenCV, I thrive at the intersection of software design and intelligent physical systems.

Currently, as an AI/ML Intern at Veino Technologies Pvt Ltd, I am developing and optimizing machine learning models for real-time edge applications. My focus is on turning complex ideas into practical, user-ready systems—whether it’s sensor integration with ESP32/Raspberry Pi or designing intuitive GUIs and telemetry dashboards that make technology accessible.

ACTIVE_QUEST

Edge AI optimization, low-latency computer vision pipelines, and Spring Boot microservices.

// POWER_LEVEL_STATS

Python & ML scripting 90%
Edge CV (YOLOv8/OpenCV) 85%
Embedded Hardware Interfacing 75%
Java / Spring Boot Backend 80%
08 Months Interned
100+ Daily Code Streak
03+ Complex Projects
ABILITY_INVENTORY

Core Perks & Capabilities

Languages

  • Python Primary
  • Java Core + OOP
  • C / C++ Firmware
  • SQL DB

AI & ML Vision

  • YOLOv8 Detection
  • OpenCV Pipeline
  • MobileNetV3 Edge ML
  • MediaPipe Keypoints
  • NumPy & Pandas Data

Edge Interfacing

  • Raspberry Pi 4/5
  • ESP32 & Arduino
  • GPIO Hardwiring
  • I2C, SPI, UART
  • Transducers & Sensors

Backend & DB

  • Spring Boot Java
  • Java Servlets MVC
  • JDBC API Storage
  • MySQL Database
  • RESTful Services

UI Presentation

  • HTML5 Semantic
  • CSS3 Grid & Flex
  • JavaScript ES6+
  • Responsive Layouts
  • Control Panels

Tools & Workflow

  • Git & GitHub
  • VS Code IDE
  • Jupyter Labs
  • Power BI
  • CLI / Bash Scripting
QUEST_PROGRESSION

Career Milestones & Campaigns

[ JAN 2026 — PRESENT ]
ACTIVE_CAMPAIGN

AI/ML Intern

Veino Technologies Pvt. Ltd. | Pune, India

Spearheading the engineering and deployment of embedded AI computer vision algorithms onto constrained hardware architecture. Focus on real-time optimization and physical alert systems.

  • Driver Monitoring System (DMS): Deployed a frame-by-frame distracted behavior detector on a Raspberry Pi 4 CPU using custom-trained YOLOv8 models.
  • Hardware Wire Link: Hyperparameter optimized neural weight limits for edge systems and wired dynamic hardware buzzer alarms directly over physical GPIO routes.
  • Performance Tuning: Streamlined processing code to run under strict 8GB RAM budgets while maintaining latency metrics.
MISSION_LOG

Completed Operations

OBJECTIVE: TELEMETRY BINDING

EV Fast Charger Monitoring System

An interactive web-based monitoring dashboard displaying real-time charging telemetry data, overall battery pack metrics, and structural fault detection alarms. Implements a clean architectural separation between firmware layers and UI modules.

Embedded C HTML/CSS JavaScript Telemetry
  • 🏆 Unlocked: Deployed real-time serial-to-web telemetry pipeline.
  • 🏆 Unlocked: Engineered custom system visual status alerts.
  • 🏆 Unlocked: Decoupled firmware structures from web widgets.
[ VIEW_CODEBASE ]
OBJECTIVE: COMPUTER_VISION_EDGE

Driver Monitoring System (DMS)

An edge intelligence application engineered on Raspberry Pi 4 executing real-time distraction and drowsiness detection. Features dynamic buzzer alerts triggered over physical GPIO lines using low-latency model weight optimizations.

Python YOLOv8 OpenCV Raspberry Pi
  • 🏆 Unlocked: Deployed low-latency frame-by-frame inference on Pi.
  • 🏆 Unlocked: Hardwired dynamic GPIO buzzers alerts.
  • 🏆 Unlocked: Optimized YOLOv8 weight budgets under 8GB RAM.
[ VIEW_CODEBASE ]
OBJECTIVE: SCALABLE_DATABASE

Student Management System

A robust backend CRUD application engineered for academic record tracking featuring persistent storage schemas. Structured entirely with formal OOP paradigms, robust encapsulation layers, and clean abstraction interfaces.

Java Core JDBC MySQL OOP Design
  • 🏆 Unlocked: Structured schema indexing for quick sorting queries.
  • 🏆 Unlocked: Decoupled transactional operations via interface hooks.
  • 🏆 Unlocked: Sanitized parameters to secure SQL interfaces.
[ VIEW_CODEBASE ]
INTEL_ARCHIVES

Education Nodes

[ 2023 — 2027 (EXPECTED) ]

B.E. Electronics & Telecommunication

Ajeenkya D.Y. Patil School of Engineering, Pune

Affiliated with Savitribai Phule Pune University. Specializing in hardware-in-the-loop interfaces, signal modulation, processing layouts, and microcontroller firmware compilation.

[ GRADUATED 2023 ]

HSC (Higher Secondary Certificate)

Kendriya Vidyalaya B.E.G., Pune

Focused study in mathematical modules, classical physics theories, analytical chemistry, and core engineering science topics.

ACHIEVEMENTS_UNLOCKED

Unlocked Medals & Trophies

100 Days of Code

METRIC: STREAK_MAX

Maintained daily commits spanning Python scripting, structural Java classes, and C++ edge routing code simultaneously without interruption.

Veino Tech Internship

STATUS: ACTIVE_DUTY

Engineered DMS tracking filters directly inside physical vehicular frameworks, resolving processor memory leaks to enable stable 28+ FPS execution.

Continuous Advancement

LVL: EXPANDING

Compiling skills in enterprise microservices (Spring Boot), complex structure algorithms (DSA), and systematic system integration architectures.

ESTABLISH_COMM_LINK

Send Transmission

Ready for mission briefing.

Looking for software development roles, edge vision collaborations, or firmware deployments. Establish connection through the secure HUD panel interface.

LOCATION_NODE

Pune, Maharashtra, India
CRITICAL: Field required.
CRITICAL: Valid email required.
CRITICAL: Field required.
CRITICAL: Field required.

HUD Diagnostics

Engine FPS: 0
Active Nodes: 0
Active Links: 0
Render Mode: Canvas2D GPU

Visual Mode Skin

Cursor FX Settings

Simulation Parameters

1.0x
60
130px

Cursor Vector Gravity