About
Engineer, student, and systems-minded builder working where robotics, software, and interface design overlap.
The work is less about isolated apps and more about technical systems that have to be understood, used, and maintained by real people under real constraints.
JJ / EXIBIST works across robotics software, machine learning, simulation architecture, and product-style technical interfaces. The through-line is architecture: how codebases are organized, how tools are shaped for operators or teammates, and how a system holds up once it has to do more than demo well.
In robotics, that means thinking about subsystem boundaries, state flow, dashboards, diagnostics, and collaboration inside a shared team repo. In ML and research work, it means building the pipeline around the model instead of pretending the model is the whole product. In simulation and tooling, it means caring about determinism, contracts, replayability, and the surfaces other engineers will actually touch.
Design is part of that engineering practice, not decoration layered on later. A good technical UI reduces mistakes, speeds up understanding, and makes a system more useful the moment it leaves the author’s laptop.
Working style
Architectural thinking over isolated script-writing.
Comfortable moving between code, tooling, interface, and workflow.
Strong bias toward reusable systems and clearer project structure.
Interested in difficult surfaces: robotics, simulation, vision, and ML.
Robotics software
Robot code, operator workflow, subsystem architecture, and match-pressure reliability.
AI / ML
Small language models, behavioral modeling, face recognition, and practical training pipelines.
Computer vision
Tracking, OCR-assisted workflows, camera systems, and video-to-field analysis for robotics review.
Simulation
Deterministic runtime design, replayability, autonomous validation, and real-code compatibility.
Tooling / infrastructure
Planning tools, strategy backends, templates, and the shared engineering surfaces around the code.
Interface design
Technical UIs that stay readable under pressure instead of treating design as an afterthought.
Systems before features
I care about boundaries, data flow, and operator workflow before I care about adding one more feature checkbox.
Build for real constraints
Robotics, simulation, and ML work only get interesting once timing, reliability, and debugging pressure enter the room.
Design is part of the engineering
Readable interfaces, good defaults, and visual clarity matter when a system has to be used quickly and correctly.
Credibility comes from implementation
I prefer concrete architecture, working artifacts, and clear technical tradeoffs over vague claims about innovation.