Badre Alloul

𝐑𝐎𝐋𝐄: Built an MVC QGIS plugin + Python CLI embedding SPCD for parcel‑level flood‑damage mapping; made workflows usable by non‑technical users. 𝐇𝐈𝐆𝐇𝐋𝐈𝐆𝐇𝐓𝐒: - Eliminated 6+ GB pre‑downloads via COG/WMTS streaming + AOI clipping; instant input preview in QGIS - Refactored SPCD into a Python package/CLI with tests/logging/CI; GDAL composition; SLURM batch runs - openEO: encoded S2 L2A pre‑processing as process graphs; parameterized batch jobs; 10+ use cases; COG/NetCDF with lineage - Normalized access to Copernicus/Theia (STAC) and IGN cadastre (WFS/WMTS); consistent CRS/tiling/caching 𝐒𝐓𝐀𝐂𝐊/𝐊𝐄𝐘𝐖𝐎𝐑𝐃𝐒: QGIS, PyQt/PyQGIS, Python, GDAL, Rasterio, Dask, FastAPI, PostGIS, openEO, STAC, COG, WMS/WFS/WMTS, SLURM; Earth Observation, Remote Sensing, GIS, Flood Mapping, Hydrology

𝐑𝐎𝐋𝐄: Built and operated 2D flood modeling/mapping pipelines for underwriting/cat analytics; delivered calibrated models and reproducible risk layers across USA, France, Switzerland, Poland, Australia, Brazil. 𝐇𝐈𝐆𝐇𝐋𝐈𝐆𝐇𝐓𝐒: - ANUGA 2D: implemented shallow‑water modeling with custom infiltration/drainage source–sink modules; calibrated/validated vs gauge hydrographs and mapped extents - Mesh standardization: exported unstructured meshes to CF/UGRID NetCDF with xugrid; conservative remap to structured rasters/data cubes for analytics and delivery - Hydrology: EVT/IDF (GEV/Gumbel, L‑moments); HEC‑HMS/Wflow calibrated to NSE >0.85 with temporal validation - Data pipelines: automated Copernicus/ECMWF/USGS ingestion; containerized jobs with retries/checksums; >10 TB/month at ~99.5% reliability - Bathymetry (IP): DEM‑morphometrics + water‑mask regression; cross‑basin CV; error/uncertainty quantified - Architecture blueprint: global OSS hydro stack (open forcings + Wflow/LISFLOOD) on HPC/SLURM; containerized runs; assimilation hooks - DEM (MNT) — Poland/Oder: ASCII grid tiles → gdal_translate (NODATA) → VRT mosaic → gdalwarp (aligned meter grid, CRS, bilinear) → hydrologic conditioning (pit‑fill, breaching, stream burning); exported COG + CF/UGRID NetCDF aligned to ANUGA; hindcast of past extreme discharges 𝐂𝐋𝐈𝐄𝐍𝐓 𝐃𝐄𝐋𝐈𝐕𝐄𝐑𝐘: Asset‑level hazard→loss assessments for a global industrial insurer; mitigation options; technical briefings to client engineering teams. 𝐒𝐓𝐀𝐂𝐊/𝐊𝐄𝐘𝐖𝐎𝐑𝐃𝐒: ANUGA (2D), HEC‑HMS, Wflow, xugrid, UGRID/NetCDF, PyQGIS, GDAL/PDAL, Python, Dask, PostGIS, SLURM; Flood Mapping, Hydrology, EVT/IDF, DEM conditioning (pit fill, stream burning), Raster/Vector/NetCDF

𝐇𝐈𝐆𝐇𝐋𝐈𝐆𝐇𝐓𝐒: - Hydraulic audit (EPANET): built system models, analyzed flow/pressure time series, identified recovery nodes (PRVs, brine lines) via head–flow envelopes and duty cycles - Turbine selection/control: Pelton/Francis sizing from H–Q curves; pressure regulation schemes, bypass/fail‑safe, inverter/grid‑tie options; surge/hammer checks - Integration: P&IDs, skid layout, tie‑ins, isolation/O&M; minimized outage installation; constraints respected (NPSH, cavitation margins) - RO interactions: assessed effects on TMP/recovery; safeguarded membrane performance and plant availability; operating setpoints defined - Business case: energy yield from P=ρgQHη; CAPEX/OPEX drivers and maintenance; payback sensitivity scenarios 𝐈𝐌𝐏𝐀𝐂𝐓: Reduced pressure‑dissipation losses; improved energy efficiency and operating cost without degrading service or RO performance. 𝐒𝐓𝐀𝐂𝐊/𝐊𝐄𝐘𝐖𝐎𝐑𝐃𝐒: EPANET, hydraulic modeling, PRV replacement, Pelton/Francis, RO desalination, surge analysis, P&ID, energy recovery, GIS/AOI mapping

𝐂𝐎𝐍𝐓𝐄𝐗𝐓: Algeria climate constraints (−15–20% summer rainfall; rising temps) → water efficiency, quality monitoring, and resilience. 𝐌𝐄𝐓𝐇𝐎𝐃𝐒: - Product: Design Thinking, JTBD, Lean Canvas, Problem/Solution & MVP slicing, PRD writing, OKRs/KPIs, TAM/SAM/SOM - Delivery: Agile/Scrum ceremonies, Kanban flow, backlog hygiene, CI/CD basics, Git workflows - Data/ML: CRISP‑DM, metrics governance, baseline vs model deltas, validation strategy - Domain: EO (Sentinel‑2 NDVI), ET₀ (FAO‑56), soil‑moisture/flow IoT (LoRaWAN/MQTT), SCADA/OPC‑UA for plants, water‑quality (pH/EC/NTU) - Architecture: API‑first, event‑driven ETL/ELT, multi‑tenant SaaS, cost model (cloud), GDPR/consent, SLO/SLA 𝐃𝐄𝐋𝐈𝐕𝐄𝐑𝐀𝐁𝐋𝐄𝐒: - Lean Canvas + PRD, architecture/pipeline diagrams, analytics KPIs, cost/feasibility notes - MVP/PoC checklists, demo scripts, pitch decks tailored to incubator criteria 𝐈𝐌𝐏𝐀𝐂𝐓: Teams converged on testable MVPs with measurable KPIs, reproducible demos, and clear go‑to‑market assumptions suitable for incubator submission.

𝐑𝐎𝐋𝐄: Hydrologic design and hydraulic modeling for an earth‑fill dam; GIS automation and quantity support. 𝐇𝐈𝐆𝐇𝐋𝐈𝐆𝐇𝐓𝐒: - Catchment characterization: ArcGIS/ArcPy (delineation, hypsometry, slope, land/soil indices) - Design floods: EV1 (Gumbel) frequency analysis → Q100/Q1000; HEC‑HMS rainfall–runoff with event hyetographs - River hydraulics: HEC‑RAS 2D unsteady runs; sensitivity on Manning’s n and boundary conditions; inundation mapping - GeoRAS toolchain: Python + ArcPy + HEC‑GeoRAS to automate cross‑section extraction, terrain conditioning, DEM→RAS export - Earth‑fill design: USBR standards; preliminary sectioning and stability assumptions; foundation reconnaissance - BoQ & procurement: assisted take‑offs, validated quantities; evaluated sourcing vs logistics/cost constraints - Site works: safety compliance checks; field data collection for foundation stability 𝐈𝐌𝐏𝐀𝐂𝐓: Repeatable GIS→HMS→RAS workflow, faster geometry prep, and defensible design discharges/inundation extents. 𝐒𝐓𝐀𝐂𝐊/𝐊𝐄𝐘𝐖𝐎𝐑𝐃𝐒: ArcGIS/ArcPy, HEC‑GeoRAS, HEC‑HMS, HEC‑RAS 2D, Gumbel (EV1), IDF/hyetographs, DEM processing, USBR earth‑fill dams, BoQ, Hydrology, Hydraulic Modeling

𝐑𝐎𝐋𝐄: 6‑week applied program for MENA student leaders; entrepreneurship, product, and strategy fundamentals. 𝐇𝐈𝐆𝐇𝐋𝐈𝐆𝐇𝐓𝐒: - Product/Market: JTBD, Lean Canvas, MVP→PMF, OKRs; customer discovery and value‑prop design - Business: unit economics (CAC/LTV), TAM/SAM/SOM, basic P&L, GTM planning, pricing - Leadership/Comms: stakeholder mapping, negotiation, storytelling, pitch deck structure