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αAbout
Jaehong Oh.
Robotics engineer and AI researcher working at the boundary between the mathematics of perception and the engineering of embodied systems. Currently a Research Intern on the Perception Team at ROBOTIS, and a Mechanical Engineering undergraduate at Soongsil University, Seoul.
Also available in other languages — 한국어 · 日本語 · Deutsch · 中文
What I'm working on
The ultimate target of the work is a single cognitive-reasoning architecture that unifies Soft Cognitive Cohesion (SCC) and Ontology Neural Networks (ONN). The ONN + ORTSF framework paper — the first formal statement of the ONN half — was accepted at Int. J. Topol. in April 2026. SCC is the thread I am currently most active on; its current state is tracked in the SCC status page.
Education
Soongsil University · Seoul
B.S. in Mechanical Engineering — focus on Robotics, AI/ML, and Control Systems. Active member of the Fluid Mechanics Laboratory and the Intelligent Robotics Laboratory.
Research experience
Research Intern · ROBOTIS (Perception Team)
End-to-end autonomous-driving research. Developing and evaluating perception pipelines for autonomous navigation systems.
Research Team Leader · Intelligent Robotics Lab, Soongsil
Led a reinforcement-learning-based Hidden Object Finding project on a robot manipulator — novel algorithms for object discovery in occluded environments, integrating vision, tactile feedback, and predictive reasoning under PyTorch and ROS 2.
Project Team Leader · Fluid Mechanics Lab, Soongsil
Led a Janus-particle synthesis project for bio-pharmaceutical applications. Electrohydrodynamics (EHD) research with 3D-printed Y-shaped microfluidic channels, combined with CFD simulation and experimental validation.
Development Team Leader · Aviation Society Cheonggeumbi
End-to-end development of a 4-axis autonomous flight drone — custom CAD frame (AutoCAD, SolidWorks), PID control, sensor fusion, and a cross-functional mechanical / electrical / software team.
Selected publications
All papers →Accepted · Int. J. Topol. · 2026
Ontology Neural Network and ORTSF: A Framework for Topological Reasoning and Delay-Robust Control
Preprint · arXiv:2508.21272 · 2025
Learning to Assemble the Soma Cube with Legal-Action Masked DQN and Safe ZYZ Regrasp on a Doosan M0609
Preprint · arXiv:2505.03815 · 2025
Towards Cognitive Collaborative Robots: Semantic-Level Integration and Explainable Control for Human-Centric Cooperation
Other selected projects
Industrial Safety Monitoring System · TurtleBot3 + YOLOv5 · 2024
Autonomous patrol robot for real-time detection of helmets, safety vests, and protective eyewear. SLAM-based navigation with dynamic obstacle avoidance (LiDAR + RGB-D); ≥ 95 % detection accuracy; MQTT-based real-time alerting.
Precision Liquid Injection Control System · Fluid Mechanics Lab · 2023
High-precision concentration control for bio-pharmaceutical applications. Load-cell mass measurement with Extended Kalman Filter (0.1 g precision), ROS 2 multi-threaded sensor / control / UI pipeline, modified-Bernoulli feedback for 0.5 % accuracy in target concentration.
RL-based Soma Cube Assembly · Doosan M0609 · 2024
The hardware companion to the published Soma-cube paper — Legal-Action Masking (4,536 → 2,484 actions, 26 % efficiency), ZYZ singularity avoidance (54 % → 96.1 % success), 91 % sim-to-real transfer via Unity domain randomisation.
Technical
- Robotics & control
- ROS 2 · robot manipulation · autonomous systems · SLAM · PID · sensor fusion
- AI & ML
- PyTorch · TensorFlow · reinforcement learning · computer vision · YOLOv5 · deep learning
- Languages
- Python · C++ · MATLAB · Git · Linux
- CAD & mechanical
- AutoCAD · SolidWorks · Autodesk Inventor · 3D printing · CFD
- Tools
- Unity · MQTT · WebSocket · Docker · Intel RealSense · Arduino · Raspberry Pi
Certifications
- CAT (Certified Associate in Technology) Level 1 — Korea Productivity Center, Aug 2024
- Doosan Robotics Bootcamp — Doosan Robotics, 2024
Contact
- jack0682@naver.com
- GitHub
- github.com/jack0682
- arXiv
- arxiv.org / Oh Jaehong
- Location
- Seoul, South Korea