Name: Pham Minh Quang
Location: Hanoi, Vietnam 🇻🇳
University: UET - VNU Hanoi
Major: Aerospace Engineering
Specialization:
  - Information Technology
  - Avionics Systems
GPA: 3.2/4.0
Status: Final Year Student

🔬 Final Thesis: Advanced Soil Salinity Mapping
🛰️ Technology: CYGNSS Satellite Data + ML
📍 Region: Mekong Delta, Vietnam
📄 Publication: Journal of Science (VNU)
🌐 Open Source: Core Engineering on GeoLibre & RustGIS

research_areas = {
    "AI_ML": [
        "Deep Learning",
        "Ensemble Methods",
        "Optimization Algorithms"
    ],
    "Remote_Sensing": [
        "CYGNSS Satellite Data",
        "Landsat & Sentinel",
        "Multi-source Integration"
    ],
    "High_Perf_GIS": [
        "Pure-Rust Geospatial Engines",
        "Apache Arrow / GeoArrow",
        "WebAssembly (SIMD128)",
        "Zero-Copy Vector Tiling",
        "DAG Workflow Orchestration"
    ],
    "Tools": [
        "Rust, Python, TypeScript",
        "ArcGIS, QGIS, GEE",
        "PyTorch, DuckDB, egui",
        "GeoPandas, MapLibre GL"
    ]
}

🇬🇧 English: IELTS 7.5
🇻🇳 Vietnamese: Native

• Zero-Copy Binary Layout (GeoArrowBatch): Eliminated JS heap GC bottlenecks by storing coordinates in flat continuous arrays (Float64Array) and ring offsets (Int32Array).
• High-Throughput Vector Tiling: Boosted worker tiling speeds by 1.9x to 7.3x using direct transferable binary buffers over structured clone.
• SQL Workspace Integration: Added atomic spatial layer creation and direct WKB decoding from DuckDB-WASM query results.
• Tech Stack: TypeScript, Apache Arrow, GeoArrow, DuckDB-WASM, MapLibre GL.

• Hardware SIMD128 Acceleration: Implemented multi-threaded adaptive WebAssembly worker pools utilizing 128-bit vector instructions for raster operations.
• Dynamic Worker Pool Scaling: Scaled background execution across available CPU cores via navigator.hardwareConcurrency with adaptive load balancing.
• Zero-Copy Buffer Transfer: Shared memory buffers and zero-copy transferable ArrayBuffers eliminating worker communication overhead.
• Tech Stack: TypeScript, WebAssembly (WASI/SIMD128), Web Workers, Whitebox Tools.

• Cycle-Safe Iteration Topology: Engineered forward-pipelined loop execution (iterate-features, iterate-rasters, collect-results) strictly verifiable by Kahn's DAG topological ordering without cycles.
• Conditional Branching & Dynamic Routing: Implemented conditional-switch and conditional-merge routing with skipped signal propagation ({ kind: "skipped" }).
• Interactive Visual Canvas & Inspectors: Designed custom multi-port control flow cards, port-level wiring, and property inspectors with live Dark/Light theme support.
• Tech Stack: React, TypeScript, DAG Topological Sorting, Kahn's Algorithm, Turf.js.

⚡ Zonal Statistics Engine & Selection Clipping (#718)

• Scanline Zonal Extraction: Architected pure-Rust cell extraction engine (zonal_statistics, Accumulator) computing multi-band count, sum, mean, min, max, and stddev via Welford's algorithm without runtime allocations.
• Geospatial Safety & Hole Invariant: Engineered scanline polygon masking (polygon_mask), enforcing atomic hole validation so defective geometry never silently enlarges sampled raster area.
• Reactive Workflow UI: Implemented reactive egui state handling in analysispane.rs reflecting selection counts (sel_count > 0), with full crate::i18n::fmt localization.
• Tech Stack: Rust, egui, Scanline Rasterization, Welford Accumulator, i18n.

🌐 Vietnam VN-2000 Coordinate System & Presets (#684)

• National CRS Engine Support: Integrated Vietnam National Coordinate Reference System (VN-2000 / QĐ 973/2001/QĐ-TTg) natively into rustgis-map and projection pipelines.
• Transverse Mercator 3° & 6° Zones: Implemented TM-3 and UTM Zone 48N/49N presets (EPSG:3405, EPSG:3406) with 7-parameter Helmert datum transformations (+towgs84).
• Provincial Central Meridian Presets: Added automated meridian resolution for provinces across Vietnam (hanoi, cantho, tphcm, haiphong, hue, danang).
• Tech Stack: Rust, Map Projections, Transverse Mercator, Helmert Datum Transforms.

📈 Ordinary Kriging Interpolation & Variograms (#660)

• BLUE Continuous Surface Reconstruction: Implemented Ordinary Kriging geoprocessing tool (kriging) computing Best Linear Unbiased Estimator surfaces from scattered point measurements.
• Theoretical Semivariogram Models: Built Spherical, Exponential, and Gaussian autocorrelation models with automated nugget, sill, and range parameter optimization.
• Zero-Allocation Local Solver: Solves local $(k+1) x (k+1)$ Kriging systems ($k \le 32$) with Gaussian elimination and partial pivoting for sub-second execution.
• Dual Raster Outputs: Generates both Prediction surfaces ({name}.tif) and Estimation Variance / Uncertainty maps ({name}_variance.tif).
• Tech Stack: Rust, Spatial Statistics, Variogram Modeling, Linear Algebra.

🔗 Spatial Join Geoprocessing Engine (#657)

• Topological Predicate Engine: Implemented spatialJoin tool and gp.spatialJoin engine command supporting Intersects, Contains, and Within relationships.
• Flexible Join Semantics: Supported Join one-to-one (with match count aggregation) and Join one-to-many, plus left outer joins (keepAll) and inner joins.
• Automated Field Resolution: Engineered configurable field prefixes and collision-resistant attribute deduplication when combining target and join schemas.
• Tech Stack: Rust, Vector Topology, Spatial Indexing, Schema Merging.

📋 Project Overview

A comprehensive framework integrating CYGNSS satellite data with multi-source remote sensing datasets to create high-resolution soil salinity maps for the Mekong Delta region using advanced machine learning algorithms.

🎯 Key Achievements

• ✅ 98% Accuracy with ensemble ML models
• ✅ Processed CYGNSS observations
• ✅ Integrated 15+ environmental variables
• ✅ Validated with field stations
• ✅ Published in Journal of Science (VNU)
• ✅ Generated risk maps

⚙️ Technical Stack

ML: Random Forest, XGBoost, LightGBM, CatBoost
Data: CYGNSS L1/L3,...
Tools: Python, PyTorch, GDAL, Rasterio
GIS: ArcGIS Pro, QGIS, Google Earth Engine

📊 Research Metrics

🔬 Innovation

• CYGNSS-based salinity mapping in Vietnam
• Multi-source data fusion approach
• Real-time prediction capability
• Scalable framework

Objective: Geospatial flood risk assessment using ensemble ML

Highlights:

• 📊 AUC > 0.95
• 🗺️ High-resolution hazard maps
• 🎯 Multi-criteria analysis
• ⚡ Real-time prediction

Tech: Python, RF, XGBoost, QGIS, GEE

Objective: Landslide risk assessment using ML

Highlights:

• 🤖 5+ ML algorithms compared
• 📈 F1-score > 0.8
• 🗺️ Actionable hazard maps
• 📊 Feature importance analysis

Tech: Python, CatBoost, ArcGIS

Objective: Enhanced flood prediction with optimization

Highlights:

• 🔄 ML + GA/PSO/ACO
• 📈 15% accuracy boost
• ⚡ Optimized hyperparameters
• 🎯 Robust predictions

Tech: Python, Genetic Algorithms, PSO

Year: 2023

Year: 2023

• Learned core ML algorithms: Linear Regression, KNN, SVM, Decision Trees
• Data preprocessing & model evaluation
• Hands-on projects using Python & Scikit-learn

Year: 2023

• AI fundamentals & problem-solving techniques
• Basics of Reinforcement Learning
• Implemented AI models through real-world simulations

Achievement: Excellent Academic Performance
Institution: UET - VNU Hanoi

Title: Advanced Soil Salinity Mapping using CYGNSS
Journal: Journal of Science: Earth and Environmental Sciences, VNU
Impact: Environmental monitoring & sustainable agriculture

Achievement: Academic Excellence
Recognition: Consistent high performance

🎯 Responsibilities & Contributions:

• 🌍 Lead Researcher on CYGNSS satellite data processing for soil salinity mapping
• 📊 Collaborated with 5+ researchers on environmental monitoring projects
• 💡 Contributed to 2+ research publications in peer-reviewed journals
• 🛠️ Created interactive visualization dashboards for research insights

🔬 Technical Achievements:

• Processed CYGNSS satellite observations
• Integrated 15+ environmental variables from multiple sources
• Achieved high prediction accuracy with ensemble models
• Validated results with ground truth stations
• Developed scalable framework for real-time predictions

📊 Impact Metrics

Data_Processed:
  CYGNSS
  Auxiliary Data: "Enviromental", "Meteorological",...

Models_Developed:
  Ensemble_ML: "5 algorithms"
  Accuracy: "high"
  Validation: "ground truth stations"

Publications:
  Journal_Papers: 1
  Conference: "In preparation"
  
Time_Saved:
  Automation: "50% reduction"
  Pipeline: "Fully automated"

Collaboration:
  Researchers: "5+ members"

🎯 Responsibilities & Engineering Contributions:

• ⚡ Engineered Zero-Copy GeoArrow Vector Pipeline (#3191): Flattened coordinate arrays into continuous memory (Float64Array) with binary tiling protocol, speeding up worker transfer by 1.9x to 7.3x.
• 🚀 Enabled Multi-Threaded SIMD128 WASI Geoprocessing (#3203): Integrated adaptive worker pool and SIMD128 hardware vector instructions for in-browser Whitebox geospatial tools.
• 🔄 Architected Cycle-Safe Model Builder Control Flow (#3215): Implemented forward-pipelined iteration (iterate-features, iterate-rasters, collect-results) and dynamic branching (conditional-switch, conditional-merge) with Kahn's topological DAG validation.

📊 Engineering Metrics

Performance_Gains:
  Tiling_Speed: "1.9x - 7.3x boost"
  Heap_Memory: "Zero GC freezes on 50k+ geoms"
  Concurrency: "Multi-worker SIMD128 pool"

Core_PRs:
  - "#3191: Zero-Copy GeoArrow Pipeline"
  - "#3203: Multi-Threaded SIMD128 WASM"
  - "#3215: Model Builder Control Flow"

Test_Coverage:
  Unit_Tests: "540+ passing tests"
  Quality: "Strict ratchet typecheck & lint"

🎯 Responsibilities & Engineering Contributions:

• ⚡ Engineered Pure-Rust Zonal Statistics Tool (gp.zonalStats) (#718): Built high-throughput scanline raster masking, multi-band accumulator, and reactive egui workflow UI with localized formatting.
• 🌐 Architected Vietnam VN-2000 Coordinate System (#684): Integrated native VN-2000 TM-3/UTM projection presets, 7-parameter Helmert transforms, and provincial central meridian aliases.
• 📈 Built Ordinary Kriging Interpolation Tool (#660): Implemented BLUE spatial surface estimation, Spherical/Exponential/Gaussian variogram models, and dual Prediction & Variance raster outputs.
• 🔗 Engineered Spatial Join Engine (gp.spatialJoin) (#657): Developed spatial predicate engine (Intersects, Contains, Within) with one-to-one/one-to-many joins and collision-safe schema merging.

📊 Engineering Metrics

Performance_Gains:
  Memory_Safety: "Pure Rust, zero unwrap/panic"
  Kriging_Solver: "Zero-allocation local (k+1) solve"
  Scanline_Mask: "Zero GC, scanline polygon fill"

Core_PRs:
  - "#718: Zonal Statistics & Clipping"
  - "#684: Vietnam VN-2000 Coordinate System"
  - "#660: Ordinary Kriging & Variograms"
  - "#657: Spatial Join Engine & Predicates"

Test_Coverage:
  Unit_Tests: "150+ geoprocessing tests & suites"
  Quality: "100% Green CI on Linux/wasm32"