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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
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 |
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.
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.
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.
