Pioneering the future of autonomous systems with a passion for spatial intelligence and AI-driven solutions.
I’m a doctoral researcher exploring cutting-edge AI and robotic perception, focused on creating intelligent systems that perceive and navigate the world in all its complexity. My work bridges radar perception, embodied AI, and 3D computer vision and probabilistic machine learning, with applications in autonomous navigation and heavy machinery automation.
🌟 Inspired by Iron Man, I thrive on solving challenges where chaos meets clarity to uncover manifold possibilities.
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🔭 Current Focus:
- Working with automotive imaging radar for robust state estimation using low leve raw data.
- Multi-modal sensor fusion and calibration
- World models that integrate radar, IMU, cameras and LiDAR seamlessly.
- Extending my environment perception and state estimation in challenging scenarios research with uncertainty aware deep learning.
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🌱 Learning Goals:
- Exploring probabilistic, complex value, graph and sequence based neural architectures and their application to autonomous navigation
- Understanding the deeper meaning of ancient wisdom in a modern context.
Languages:
Python · C· C++ · MATLAB · ROS2 · CUDA
AI Frameworks:
PyTorch · TensorFlow · Keras · JAX
Specialties:
Radar Perception · 3D Computer Vision · Transformers · Probabilistic deep learning · Sensor Fusion
Platforms:
Jetson Xavier AGX/Orin · Texas Instruments' Cascade Radar · Docker
- 🤖 Developed automated pipelines for active learning, automated annotation, model compression and edge AI during my work at Clear Image AI as a data scientist.
- 💬 Favorite quote: "Manifold possibilities emerge where the mind dares to explore."
- 🔭 Exploring the intersection of chaos and clarity where potential converges with purpose.
- 📚 Big fan of Neal Stephenson and fascinated by the simulation hypothesis (“The Lattice,” as I like to call it).
✨ Feel free to reach out if you’re interested in AI, robotics,3D computer vision or exploring innovative solutions together!