🚀I'm CEO & Co-Founder @ OrbitFlow Dynamics | CTO & Co-Founder @ Crater-ion, a Space Systems Engineer specialising in GNC, AOCS and spacecraft autonomy, and AI-driven navigation, with a research background spanning reinforcement learning for autonomous docking, vision-based pose estimation, star tracker development, AI-based optical navigation systems, and STM/SSA systems.
**My work sits at the intersection of two increasingly inseparable domains: rigorous astrodynamics and modern deep learning. I build systems that work not just in simulation, but under the real conditions of space, degraded sensors, off-nominal dynamics, and no possibility of human intervention.
🛰️ Research focus: GNC & AOCS Engineer | AI for Spacecraft Autonomy · Vision Navigation · STM . Star Tracking · On-Orbit Servicing.Proximity Operations. Autonomous Rendezvous & Docking · RL. Meta-learning. Constellation Design
🌐 Read the full OrbitalFlow pitch here
I build machine learning systems for spacecraft systems, perception, navigation, and autonomy — combining deep learning, reinforcement learning, meta-learning, and computer vision for enhancing space operations.
-
🌕 ** Multi-layer intelligence: CTDE, smart search, distributed learning, meta-learning ** — Space Traffic Management, Space Situational Awareness (OrbitFlow Dynamics)
-
🤖 **Deep MARL, Intelligent crater mapping, Safe filtering, centralized autonomy ** — Precision Lunar navigation and Landing (Crater-ion)
-
🌕 Vision-based navigation — crater detection, ellipse regression, star trackers
-
🤖 Reinforcement learning for GNC — spacecraft rendezvous & docking, Mega constellation routing
-
🛰️ Satellite image processing — super-resolution & inpainting for optical navigation
-
🎓 **PhD Student in Aerospace engineering ** University of Carleton , Ottawa ,Canada
-
🎓 Holds MSc in Satellite Technology & Space Engineering from Julius Maximiliana Universität Würzburg (JMU)/University of Carleton
-
🎓 Holds **MSc in Cryptography and AI ** from University of Concordia Montreal ,Canada
| Project | Description |
|---|---|
| 🌕 MoonScanner | Deep learning ellipse-regression model for lunar crater mapping from high-res satellite imagery |
| 🚀 Spacecraft Rendezvous & Docking RL | Soft Actor-Critic agent for collision-free docking, trained with curriculum learning on a 2D air-table simulation |
| 🛰️ SR & Inpainting for Optical Navigation | Transformer-based super-resolution & inpainting for corrupted spaceborne imagery (SPEED+ dataset) |
| 🌐 LEO Constellation Routing RL | PPO/SAC agents for optimal routing in LEO satellite constellations, benchmarked against an A* baseline |
| 🔭 SwinDock | Real-time Swin Transformer + NaViT pipeline for identifying satellite docking surfaces, with a live-inference GUI |
| ⭐ Stellar Transformer V2 | Celestial attitude determination using Swinv2 Transformers and Focal Loss, with automated star-map extraction |
-
[IAA AI4Space 2026] Star-Fusion: Multi-modal Transformer for Discrete Celestial Orientation via Spherical Topology (2026) arxiv.org/abs/2604.26582
$~~~~~~~~~~~$ -
[IAC 2026] Stellar Transformers: Vision Transformers for Autonomous Star Tracking and Attitude Estimation (2026)
$~~~~~~~~~~~$ -
[IAA AI4space ] Real-Time Random Exploring Trees for Collision-Free Spacecraft Path Planning , Rendezvous, and Docking (2026)
-
[IAA AI4space ] Efficient Reinforcement Learning For Collision-Free Spacecraft Rendezvous and Docking (2026)
$~~~~~~~~~~~$ -
[IAA AI4space ] A Corruption-Aware Image Restoration Framework for Spaceborne Optical Navigation Using the SPEED+ Dataset (2026)
$~~~~~~~~~~~$ -
[IAC 2024] Innovative AI-Based Star Tracker for Deep Space Exploration (2024)[IAC 2023] Deep Learning for Vision-Based Spacecraft Navigation (2023)
$~~~~~~~~~~~$ -
[IAC 2022] Space Transportation Systems: Lessons Learned from Deep Space Missions (2022)
$~~~~~~~~~~~$ -
[ICPRAI 2020] Characterizing Pre-Trained Features in Video Captioning (2020)
$~~~~~~~~~~~$
📫 Let's connect — always open to talking about spacecraft autonomy, GNC, or space AI research.