01 · Process Safety · Oil & Gas
2025 — Present
Fuzzy BowTie inference system for offshore process safety
Lead technical owner of a risk-assessment system combining fuzzy inference with probability trees, delivered in partnership with a major energy operator and a top research university. Designed the architecture, ran end-to-end data analysis on highly fragmented industrial data, and built a tag-clustering algorithm based on business rules that drastically reduced base complexity. First production milestone delivered with full stakeholder approval.
~90%data complexity reduced
2external partners led
Fuzzy InferenceProbability TreesPythonProcess SafetyStakeholder Mgmt
02 · MLOps · Platform
2025
Accelerated deployment framework & QA library
Architected the team's end-to-end deployment workflow and a modular Python QA library for unit and integration testing across dev/prod environments. Restructured the model catalog (50+ legacy entries) and authored the team-wide development & deployment guidebook. Adopted across the data science team and integrated into the lifecycle of 100+ production models.
13×deploy throughput
96%validation cycle cut
100+production models
MLOpsPythonQA FrameworksAzure DevOpsDocumentation
03 · Computer Vision · Industrial Inspection
2024 — 2025
Corrosion detection on offshore equipment
Led a computer vision PoC for corrosion detection on offshore industrial installations using DeepLab semantic segmentation, with data augmentation and patching techniques for high-resolution 360° imagery. Built and supervised the labeling pipeline with LabelMe and established baselines for production rollout.
~70%F1 / IoU
1,500images labeled
PyTorchDeepLabSemantic SegmentationLabelMeData Augmentation
04 · Predictive Maintenance · Industrial
2024 — 2025
Predictive maintenance & sensor anomaly detection
Built predictive-maintenance models for industrial spindle telemetry across 30+ assets and 4 clients, plus anomaly-detection pipelines for offshore sensor data. Early identification of an asset failure was instrumental in a key client renewing a 1-year contract. Also developed a knowledge-based sensor-comparison model with adaptive normalization to detect faults across redundant and analog sensors at vessel scale.
30+industrial assets
1,000+sensors per vessel
Time-seriesAnomaly DetectionSensor AnalyticsPythonDatabricks
05 · Probabilistic ML · Public Utilities
2022 — 2024
Damage prediction for a metropolitan gas network
Designed a probabilistic ML model to predict damage risk to São Paulo's underground gas distribution network from third-party construction work (20–30 sites/day). Output directly drove field-engineering routing and prioritization. Also delivered a billing-rule optimization model and a People Analytics solution that identified improper reimbursements.
~$55Kmonthly cost savings (USD)
+70%field productivity
~$165Kadditional savings (USD)
Probabilistic ModelingPythonAzure MLDatabricksh2o.ai
06 · Research · Surrogate Modeling
2020 — 2021 · DAAD · Germany
Gaussian Process surrogates for crash simulation
Developed Gaussian Process surrogate models at CARISSMA / Technische Hochschule Ingolstadt (DAAD scholarship) to replace computationally expensive Finite Element crash simulations, while maintaining low Mean Absolute Error against the FE ground truth. Published in VDI on metamodel robustness and predictive power considering human diversity.
24×simulation speedup
72h → 3hruntime reduced
Gaussian ProcessesSurrogate ModelingFE SimulationPythonResearch