ohara124c41 / sfnd-radar-target_generation-n-detection

Calibrate, threshold, and filter radar data to detect obstacles in real radar data. Analyze radar signatures to detect and track objects. Calculate velocity and orientation by correcting for radial velocity distortions, noise, and occlusions.

Hi! My name is Christopher. I am a roboticist and cybernetician focused on creating cognitive space robotics. I am currently a Doctorate of Engineering in Aeronautics and Astronautics candidate at the University of Tokyo, Artificial Intelligence Lab. Furthermore, I am working on system/software architecture and autonomous agent path planning for Upper Class E Traffic Management (ETM) spacecraft at NASA Ames (Code: ARC AFT). Previously, I worked with several space groups including the European Space Agency, the Austrian Space Forum, EPFL, and the Space Generation Advisory Council to bring high-tech solutions to complex problems. I specialize in systems engineering and systems architecting domain for artificial intelligence, machine learning, and control systems for space robotics. Thank you for your interest!

I have developed MBSE architecture frameworks for ESA, Volvo, and Siemens. For CERN, I have developed extensive APIs for handling petabytes of data. Most of my projects focus on future-oriented technologies. For example, the CERN SHiP experiment in 2026, ESA's Deep Space (Copernicus and beyond) in 2030-2040, Space Suits for 2024+, and NASA ETM for 2030+. My most intensive contributions have been by combining Generative Engineering and Concurrent Engineering for space system applications development for Phase 0/A missions at Siemens. Finally, I am concurrently designing automatic deconfliction algorithms for aircraft in Upper-Class E Airspace.

Gist:

🌎 International & Multidisciplinary

🚀 Space Mission Planning & Architectures

🤖 Cognitive Robotics & Artificial Agents

🕹️ Human-Robot Interaction & Human Factors (Game Design)

---

---

Now Playing on Spotify 🎧

---