Full-Stack Engineer • Research Engineer • Robotics, Control, Power Systems, and Scientific Tooling

I build production software and research-grade technical systems at the intersection of web engineering, scientific computing, distributed control, robotics, and real-time power-system estimation.

I am a Full-Stack Engineer and research-oriented builder with a strong interest in systems that combine:

• Modern web engineering and product architecture
• Scientific computing and reproducible research workflows
• Distributed control, graph-structured systems, and multi-agent coordination
• Robotics and industrial automation
• Power systems, PMUs, dynamic frequency estimation, and low-inertia grids
• Machine learning for engineering and scientific discovery

My long-term direction is to develop a rigorous portfolio in control, robotics, and intelligent systems, while continuing to build serious production software and technically ambitious research tools.

• Distributed and graph-structured control
• Multi-agent systems and cooperative robotics
• Dynamic frequency and RoCoF estimation for low-inertia power grids
• FPGA-oriented real-time estimation architectures
• Benchmarking frameworks for scientific and engineering methods
• Research automation, bibliometrics, and knowledge synthesis

• Benchmark platforms for frequency-estimation methods under realistic grid disturbances
• Scientific tooling for reproducible experimentation, evaluation, and reporting
• Full-stack products with strong backend, workflow automation, and AI-assisted analysis
• Research infrastructure that is robust enough to become publishable, extensible, and reusable by others

A benchmarking framework for frequency and RoCoF estimators in modern power systems, especially under low-inertia and converter-dominated conditions.

Core ideas:

• Research-grade evaluation pipelines
• Dynamic and stress-test scenarios beyond easy steady-state cases
• Latency vs. robustness trade-off analysis
• Honest comparison of classical, Kalman-based, PLL/FLL, and data-driven estimators

Why it matters: Most estimator comparisons are too narrow, too idealized, or too hard to reproduce. I am interested in building a benchmark that becomes a reliable technical reference rather than another one-off experiment.

A research direction focused on hardware-oriented implementations of dynamic estimators, especially Kalman-style approaches and real-time signal-processing pipelines for power applications.

Core ideas:

• Architectures that are actually hardware-native instead of pseudo-CPU designs on FPGA
• Parallel and scalable estimator structures
• Real-time operation under practical sampling, latency, and robustness constraints
• A path from simulation-grade methods to deployable estimation cores

Research and experimentation around distributed LQR, graph-structured control, spectral perspectives, and locality-aware coordination.

Topics of interest:

• Local vs. centralized control trade-offs
• Space-time sparsity of feedback gains
• Cooperative coordination using only nearby information
• Control laws informed by graph topology and propagation patterns
• Scalable methods for large interconnected systems

Applied work and academic development in industrial robotics, collaborative robotics, sensing, control, and automation workflows.

Typical interests:

• Robot-cell design and safety reasoning
• Collaborative workspaces and practical industrial constraints
• Distributed or multi-agent coordination strategies
• Architectures that bridge control theory and implementable systems

A project for systematic literature review support, bibliometric synthesis, and research automation.

Goal: To reduce the friction between searching the literature, organizing evidence, generating structured outputs, and producing research-ready summaries.

Why it matters: Good research is not only about ideas. It also depends on disciplined pipelines for finding, filtering, structuring, and revisiting the state of the art.

I also build full-stack applications for real users and real workflows.

Representative directions include:

• LegalTech platforms with guided flows, payments, CRM automation, document handling, and scheduling
• Operational dashboards for industrial or business processes
• AI-assisted products that combine search, document workflows, automation, and structured decision support
• Production systems where architecture, reliability, maintainability, and UX matter as much as shipping features

Universidad Internacional de Valencia (VIU)

Focus areas include robotics, industrial automation, sensing, control, manufacturing environments, and applied engineering systems.

Universidad Isabel I & Structuralia

Focused on machine learning, data workflows, analytics, and applied AI engineering.

Universidad de los Andes

Background in embedded systems, electronics, communications, computer systems, and control-related engineering.

Strong foundation across electrical engineering, power systems, control, electronics, automation, and computational problem-solving.

• TypeScript, JavaScript
• React, Next.js, Angular
• Node.js, NestJS, Express
• REST APIs, workflow automation, backend integrations
• PostgreSQL, MySQL, MongoDB
• Docker, Linux, CI/CD
• Cloud services and production deployment workflows

• Python
• MATLAB
• R
• PyTorch
• OpenCV
• Numerical simulation, data analysis, benchmarking, and reporting pipelines

• Control systems
• Robotics
• Multi-agent systems
• Power systems and PMUs
• Scientific software
• AI for engineering workflows

I am especially drawn to work that is:

• Rigorous enough to stand up to academic scrutiny
• Useful enough to solve a real engineering problem
• Reproducible enough that someone else can build on it
• Well-architected enough to survive beyond a demo

I care a lot about the gap between interesting ideas and serious implementations. That gap is where I like to work.

• Research collaborations in control, robotics, power systems, and scientific computing
• Technically demanding full-stack or platform engineering work
• Projects involving benchmarking, experimentation, and reproducible engineering pipelines
• Conversations around future graduate research, especially in distributed control and intelligent systems

• Email: mayorgajl@proton.me
• Portfolio: jlmayorgaco.github.io
• GitHub: github.com/jlmayorgaco

If my work overlaps with your interests, feel free to reach out.