Julio Werner Email & Phone Number

End to end development of Air Quality Monitoring Platform used by a Big Company. • Main System Features: near real-time data, maps, alerts, emission inventories, and forecasts.• Data Stack: Dagster, GCS, Timescale• Backend: Django• Frontend: htmx, tailwind,alpine.js, leaflet• DevOps: Argocd and Terraform

Developed a batch video processor for traffic analysis.Main Features:• Automatically group flow directions, estimation of velocity and traffic intensity.• Trained YOLO model achieving mAP of 57;• Used TensorRT to improve performance;• Monthly Report automatization;

Designed and developed low-cost data logger for wind speed and direction measurements.• Fast prototype and deployment on coastal area (Approx. 1 Month)• Raspberry Pico ADC to capture and transmit data (Code in C)• Raspberry Pi to receive, store, transmit data (Code in Python)

Designed and developed a data-driven tool to assess Brazil's investment needs for universalizing sanitation services. • Understand advanced analysis from a cross-functional team of economists and engineers and transform into a product.• Collect and process data from multiple national providers;

Curitiba, Paraná, Br

Challenge accepted to create the integration team (5) from scratch and remotely.Managed hundreds of integrations.We reduce by 250% the lead time of new integrations by restructuring teams and changing API designs.We developed an integration software that could work offline for some hours, thus avoiding downtimes.The team had high eNPS scores (>80) and we created a collaborative workplace by cultivating transparency and openness.

Curitiba, Paraná, Br

• Designing and developing systems to communicate with clients and to inspect consumer behavior.• Delivered a tool to deploy an android emulator on the cloud.• Developed a real-time system to synchronize data among internal and external repositories. Tech: Go, Node.js, Python, RabbitMq, SQS, Pubsub, MongoDB, Clickhouse

Curitiba, Paraná, Br

A machine learning-based zoning methodology was developed to identify and prioritize areas of concern within reservoirs.Tools Applied:• Machine learning clustering• 3D water quality modeling• Remote sensing analysis• Simple assessment tools (Vollenweider models, residence time)Main Finding:Reservoir geometry and inlets with the largest drainage areas were the most influential factors in determining the zoning.

Curitiba, Parana, Br

Leading team of researchers, planning activities, writing proposals, writing reports, setting hydro-dynamic model, and writing computer program for data analysis. Some of the R&D projects andservices were:• Monitoring the development and movement of aquatic plant in reservoirs through remote sensingand hydrodynamic modeling• Damage Assessment of Fundão Dam Failure• Analysis of the environmental impact of Floating Solar Panels deployed at a Hydroelectric Reservoir• Dam-break flood analysis

Modelagem tridimensional e unidimensional de um trecho da Hidrovia Tocantins Araguaia.

I developed a simpler method to determine the carbon stored by a hydroelectric reservoir and then infer its impact on greenhouse gas emissions. https://link.springer.com/article/10.1007/s13280-016-0874-6Activities- Managing a small research group;- Writing technical reports;- Planning field campaigns;- Purchase specifications;- Presentation of results.

London, Gb

- Development of a statistical model for operational risk;- Automation of repetitive tasks using VBA;- Development of tools to forecast economic indicators.

- Data quality assurance of hydrological and meteorological data;- Calibration and Simulation using the Hydrological Model SWAT;

Doctorate, Water Resources And Environmental Engineering

Research Stay, Environmental Engineering Technology/Environmental Technology

Master'S Degree, Water Resources And Environmental Engineering

Enviromental Engineer, Environmental Engineering Technology/Environmental Technology

Electronics Technician