Hi, I'm Jonathan Dambros

AI & Machine Learning Specialist · Ph.D. in Chemical Engineering

Porto Alegre, Brazil

I build production-grade Python systems and agentic workflows, apply research in monitoring, diagnostics, and optimization of process industries, and lead teams to deliver dependable AI products and evaluations.

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Portrait of Jonathan Dambros

Selected Work

awesome‑industrial‑datasets

Curated collection of real-world industrial datasets across multiple sectors. (200+ stars on GitHub)

  • Open-source with JSON metadata and community contributions
  • Widely used by researchers and practitioners
View repository

PlantPilot

Conversational AI copilot for process plants using RAG over process documentation with Gradio UI.

  • Rapid Q&A over comprehensive plant documentation
  • Prototype successfully used for demos and internal testing
Open Space

Research & Publications

Control-loop performance monitoring, diagnostics, and industrial applications with real-world impact.

  • Peer-reviewed papers and conference presentations
  • Focus on control-loop process monitoring, fault detection, and optimization
View on Google Scholar

DigitalTwin (private)

Python library for plant monitoring (CPM, Kalman) with reproducible workflows and data auditability.

  • Successfully used in Petrobras collaborations
  • Flow-based execution with comprehensive data auditability
Private — details on request

Kalman Filter (private)

FilterPy-style package for advanced state estimation and filtering.

  • Multiple Kalman filter variants implemented
  • Plant simulation using multiple Python libraries
Private — details on request

Turing (LLM Evaluation)

Evaluation frameworks and datasets to stress-test model reliability and performance.

  • Lead team of 30+ reviewers
  • Structured grading, rubric design, and calibration processes
Private — details on request

Skills

AI Specialist

Building intelligent agentic systems, developing machine learning solutions, and creating data-driven applications with Python.

  • Python · 10+ yrs
  • Machine Learning · 8+ yrs
  • Agents (tool use, retrieval, orchestration) · 1+ yrs
  • RAG & Evaluation Frameworks · 1+ yrs
  • Dash/Gradio UIs · 5+ yrs

Researcher

Conducting applied research with industry partnerships, focusing on control-loop process monitoring (CPM) and advanced diagnostics.

  • Process Control & CPM · 9+ yrs
  • Optimization · 8+ yrs
  • Industrial ML · 7+ yrs
  • Academic Writing/Publishing · 8+ yrs
  • State Estimation (Kalman/LQR) · 7+ yrs

Manager

Leading teams focused on reliable AI delivery, evaluation frameworks, and quality assurance.

  • Team Leadership & Mentoring · 2+ yrs
  • Stakeholder Communication · 2+ yrs

Strengths & Setup

Work Ethic & Craft

How I approach work and quality.

  • Hard worker
  • Communicative and open to feedback
  • Attention to detail
  • Creative problem‑solver
  • Proactive and ownership-driven

Focused Remote Setup

Quiet, dedicated workstation for deep work.

  • Mac mini M4 Pro • 48GB RAM
  • ~600 Mbps fiber internet
  • Isolated workspace
  • Dual monitors

Hobbies

I enjoy sports, great music, and technology.

  • CrossFit practitioner
  • Guitar player
  • Technology enthusiast
  • Open-source projects

Employment History

Engineering Manager — LLM Evaluation

Turing

Remote

2023 – present
  • Lead trainers who evaluate and grade LLM responses using calibrated rubrics and quality standards.
  • Design evaluation methods and reviewer workflows to ensure reliability and consistency.
  • Manage multiple internal projects and cross-functional initiatives.

Postdoctoral Researcher

UFRGS — GIMSCOP

Porto Alegre, RS, Brazil

2019 – present
  • Industrial monitoring, diagnostics, and optimization with real-world deployments and production systems.
  • Developed Python libraries (DigitalTwin, Kalman) through strategic Petrobras collaborations.
  • Published research papers and delivered talks on control-loop process monitoring (CPM) and diagnostics.

Team Lead (Self‑employed)

Latos

Porto Alegre, RS, Brazil · On‑site

2020 – 2023
  • Built comprehensive data-based solutions for manufacturing and process industries.
  • Developed Heron, a web platform to streamline data science workflows for manufacturing operations.
  • Integrated multiple data sources and stored results in InfluxDB for visualization in Grafana, Power BI, and Tableau.
  • Built with Python (Django) and deployed on AWS EC2 with scalable architecture.

Education

Postdoctoral Researcher — Chemical Engineering

UFRGS — GIMSCOP

Porto Alegre, RS, Brazil

Jun 2019 – present

Focus on real AI applications in process industries, collaborating closely with an oil & gas company.

Ph.D. — Chemical Engineering

UFRGS

Porto Alegre, Brazil

Oct 2016 – Jun 2019

Visiting Researcher

University of Kaiserslautern

Kaiserslautern, Germany

Apr 2018 – Oct 2018

M.Sc. — Chemical Engineering

UFRGS

Rio Grande, Brazil

Mar 2015 – Oct 2016

B.Sc. — Chemical Engineering

FURG

Porto Alegre, Brazil

Mar 2010 – Dec 2014

Awards & Honors

Top Graduate (2014)

Recognized for the highest performance among Chemical Engineering graduates.

International Challenge Winner (2019)

Winner of the Gerdau-sponsored challenge proposing a computer-vision solution for scrap quality inspection. Details

Best Industry 4.0 Application (2021

National prize for the Best Industry 4.0 application in manufacturing.