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pari1999/README.md

Parikshith

Embedded AI Engineer | Autonomous Systems Specialist

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πŸ‘¨β€πŸ’» System Profile

Education: ....... M.Eng, AI Engineering of Autonomous Systems
Experience: ...... 4+ Years Professional Embedded Specialist
Current Role: .... Robotics & AI Engineer @ Hilti
Core Tech: ....... ROS2, Edge AI, Embedded C/C++, PX4 Stack
Toolchain: ....... ISAAC SIM, Gazebo, STM32 CubeIDE, GZ SITL
Programming: ..... C, C++, Python
Frameworks: ...... PyTorch, TensorFlow Lite, MAVSDK
Edge AI Ops: ..... VLMs, LLMs (llama.cpp), CNNs
- Specializations --------------------------------
* Sensor Data Fusion, Embedded AI Software Design
* Embedded Systems (BSP, Drivers, PCB Design)
* UAV Firmware Development & System Design
- Achievements -----------------------------------
* 2x National Level Hackathon Winner
* Founding Team: Vyomastra (Defense Drones)
- Contact ----------------------------------------
Email: ........... [email protected]
LinkedIn: ........ [www.linkedin.com/in/parikshith-y-s-388068183]
Location: ........ Ingolstadt, Germany

⚑ Runtime Environment

Architecture: Heterogeneous Computing (Edge + Cloud)

Layer Technologies
High-Level Intelligence PyTorch, TensorFlow Lite, VLMs, LLMs (llama.cpp), Reinforcement Learning
Middleware & Control ROS 2, ISAAC SIM, Gazebo, MAVSDK, PX4 Autopilot
Firmware & Hardware Embedded C/C++, STM32, CUDA, NVIDIA Jetson, FPGA

πŸš€ Mission Log

NVIDIA Project | Deep Tech & System Architecture

Focus: High-performance computing for next-gen autonomous hardware.

  • NVIDIA Tegra Thor Development: Owned the software stack for an entire system module for NVIDIA's Tegra Thor SoC.
  • End-to-End System Ownership: Managed the module lifecycle from Emulation $\to$ FPGA Prototyping $\to$ Pre-Silicon Verification.
  • Impact: Enabled critical validation steps for cutting-edge automotive AI hardware.

Hilti | Robotics & AI Engineer

Focus: Real-world perception and interaction.

  • Developing robust perception systems for autonomous construction robots using ROS 2 and Edge AI.
  • Bridging the gap between theoretical AI models and constrained embedded hardware.

πŸ”¬ Research Interests

My goal is to advance the field of Edge AI for autonomous systems, specifically focusing on:

  • Constrained Optimization: Running VLM/LLMs on resource-limited embedded targets.
  • Neuro-symbolic AI: Combining data-driven learning with robust control theory.
  • Real-time Perception: Low-latency sensor fusion for high-speed UAVs.

Pinned Loading

  1. Intelligent-Sorting-System Intelligent-Sorting-System Public

    Team_Project:

    Python 1

  2. px4_mavsdk_ble_scan px4_mavsdk_ble_scan Public

    Autonomous BLE scanning project using PX4 and MAVSD

    Python

  3. Reinforcement-Learning-Agents Reinforcement-Learning-Agents Public

    Reinforcement learning project with a simple Q Learning and a Deep Q learning.

    Python