bassemsalah019-debug

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bassemsalah019-debug

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### <img src="https://raw.githubusercontent.com/Tarikul-Islam-Anik/Animated-Fluent-Emojis/master/Emojis/People%20with%20professions/Man%20Technologist%20Medium%20Skin%20Tone.png" width="35" /> About Me

> **"Bridging the gap between raw Earth data and intelligent AI-driven insights."**

I'm **Bassem Salah**, a **Petroleum Engineer & Data Analyst** based in Cairo, Egypt 🇪🇬 — with a rare dual expertise in **Petroleum Geoscience** (BSc, Suez University) and **Data Science & AI/ML** (MCIT — DigiLines Program).

I build end-to-end data pipelines, ML models, and interactive dashboards that turn complex geological and operational data into actionable decisions. My unique edge: I combine **seismic interpretation, reservoir characterization, and well log analysis** with **Python, SQL, and machine learning** — a combination very few practitioners bring to the table.

- 🎓 **BSc Petroleum Engineering** — Suez University, Faculty of Petroleum & Mining Engineering *(2017–2022)*
- 🤖 **AI & Data Analysis Program (9 months)** — DigiLines / MCIT Egypt *(Dec 2025 – Jun 2026)*
- 🏢 **Internship (6 months)** @ Energia Inc — Reservoir Characterization & Seismic Inversion *(Mar–Jul 2022)*
- 🛢️ **Well Site Geology Internship** @ Khalda Petroleum Company *(Jul 2021)*
- 💼 **Freelancer** on Upwork & Mostaql
- 📍 **Based in** Cairo, Egypt | 📞 +20 100 117 9269

---

## 🛠️ Tech Stack & Skills

### 🧠 AI & Machine Learning
![Python](https://img.shields.io/badge/Python-3776AB?style=for-the-badge&logo=python&logoColor=white)
![Scikit-Learn](https://img.shields.io/badge/Scikit--Learn-F7931E?style=for-the-badge&logo=scikitlearn&logoColor=white)
![NumPy](https://img.shields.io/badge/NumPy-013243?style=for-the-badge&logo=numpy&logoColor=white)
![Pandas](https://img.shields.io/badge/Pandas-150458?style=for-the-badge&logo=pandas&logoColor=white)
![Jupyter](https://img.shields.io/badge/Jupyter-F37626?style=for-the-badge&logo=jupyter&logoColor=white)

### 📊 Data Analytics & Visualization
![Power BI](https://img.shields.io/badge/Power_BI-F2C811?style=for-the-badge&logo=powerbi&logoColor=black)
![Tableau](https://img.shields.io/badge/Tableau-E97627?style=for-the-badge&logo=tableau&logoColor=white)
![Matplotlib](https://img.shields.io/badge/Matplotlib-11557C?style=for-the-badge&logo=python&logoColor=white)
![Excel](https://img.shields.io/badge/Excel-217346?style=for-the-badge&logo=microsoft-excel&logoColor=white)

### 🗄️ Databases & Cloud
![SQL](https://img.shields.io/badge/SQL-CC2927?style=for-the-badge&logo=microsoft-sql-server&logoColor=white)
![Azure](https://img.shields.io/badge/Microsoft_Azure-0089D6?style=for-the-badge&logo=microsoft-azure&logoColor=white)
![Git](https://img.shields.io/badge/Git-F05032?style=for-the-badge&logo=git&logoColor=white)

### 🛢️ Petroleum & Geoscience
![Petrel](https://img.shields.io/badge/Schlumberger_Petrel-003DA5?style=for-the-badge&logoColor=white)
![Techlog](https://img.shields.io/badge/Schlumberger_Techlog-E63312?style=for-the-badge&logoColor=white)
![ArcGIS](https://img.shields.io/badge/ArcGIS-2C7AC3?style=for-the-badge&logo=arcgis&logoColor=white)
![Surfer](https://img.shields.io/badge/Surfer_&_Global_Mapper-6D6D6D?style=for-the-badge&logoColor=white)
![PLAXIS](https://img.shields.io/badge/PLAXIS_2D_%26_3D-8B0000?style=for-the-badge&logoColor=white)

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---

## 📜 Certifications

| 🎓 Certification | 🏛️ Issuer | 📅 Year | 🔗 |
|-----------------|-----------|---------|-----|
| 🤖 **AI & Machine Learning** | DigiLines — MCIT Egypt | 2026 | coming soon |
| 📊 **Data Analytics Program** | DigiLines — MCIT Egypt | 2026 | coming soon |
| 🧠 **Azure AI Fundamentals (AI-901)** | Microsoft | 2026 | coming soon |
| ☁️ **Azure Data Fundamentals (DP-900)** | Microsoft | 2026 | coming soon |
| 📈 **Power BI Data Analyst Associate (PL-300)** | Microsoft | 2026 | [View](https://learn.microsoft.com/en-us/users/bassemsalahabdelalim-6117/credentials/5b1854bd43ef5cea?ref=https%3A%2F%2Fwww.linkedin.com%2F) |
| 📈 **Fabric Analytics Engineer Associate (DP-600)** | Microsoft | 2026 | [View](https://learn.microsoft.com/en-us/users/bassemsalahabdelalim-6117/credentials/984622ecda4cdcb5?ref=https%3A%2F%2Fwww.linkedin.com%2F) |
| 🧠 **IBM AI Engineering** | IBM | 2026 | [View](https://www.coursera.org/account/accomplishments/specialization/1EKSFM1BYDUP) |
| 📈 **Google Data Analytics** | Google | 2026 | [View](https://www.coursera.org/account/accomplishments/professional-cert/KFU00VJBZTJX) |
| 🛡️ **OSHA General (HSE)** | OSHA | 2022 | [View](https://app.oshacademy-atp.com/verify/?code=260201-100-352-9bde5) |
| 🛢️ **IWCF Programme Level 1** | IWCF | 2022 | [View](https://iwcflevel1programme.lovable.app) |
| 🏢 **Internship Certificate** | Energia Inc | 2022 | [View](https://www.linkedin.com/feed/update/urn:li:activity:6955635836902080512/) |

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---

## 🚀 Previous projects

### 🏋️ Body Performance ML Analytics
> *Classification · Feature Engineering · Regression · SHAP Explainability · Gradio App*

**A full end-to-end ML pipeline** classifying physical fitness into 4 categories (A/B/C/D) from 13,393 human performance records, with a secondary regression task predicting broad jump distance (cm).

**Pipeline highlights:**
- 🧹 Data cleaning with IQR Winsorization & leakage-free StandardScaler inside Pipeline
- ⚙️ 9 domain-driven engineered features (BMI, fitness_composite, endurance_strength…)
- 🤖 5 classifiers × 6 feature subsets = **30 configurations tested**
- 📉 5 regressors × 6 feature variants = **30 regression configs**
- 🧠 SHAP explainability for full model transparency
- 🚀 Deployed **Gradio prediction app** on HuggingFace Spaces

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**🏆 Key Results**

| Metric | Value |
|--------|-------|
| 🎯 Best Accuracy | **75.29%** |
| 📊 ROC-AUC | **0.9193** |
| 📈 Best R² | **0.7841** |
| 📉 Best RMSE | **18.52 cm** |
| 🔢 Records | **13,393** |
| ⚙️ ML Configs | **30** |

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**🏅 Best Models:**

| Task | Winner | Score | Runner-Up |
|------|--------|-------|-----------|
| Classification | Neural Network (128,64) + tanh | Acc=75.29%, AUC=0.9193 | SVM-RBF (72.0%) |
| Basic Regression | SVR-RBF (C=100, γ=0.01) | R²=0.7817, RMSE=18.62cm | Neural Net (R²=0.7812) |
| Advanced Regression | Linear Reg + All Enhanced (39f) | R²=0.7841, RMSE=18.52cm | Linear + Log+Poly (R²=0.7837) |

**🔬 Top SHAP Features:** `sit-ups counts (0.145)` → `gripForce (0.118)` → `fitness_composite (0.112)` → `body fat% (0.098)`

**🛠 Technologies:**
![Python](https://img.shields.io/badge/-Python-3776AB?style=flat-square&logo=python&logoColor=white)
![Scikit-Learn](https://img.shields.io/badge/-Scikit--Learn-F7931E?style=flat-square&logo=scikit-learn&logoColor=white)
![SHAP](https://img.shields.io/badge/-SHAP-FF6B6B?style=flat-square)
![Gradio](https://img.shields.io/badge/-Gradio-FF7C00?style=flat-square)
![HuggingFace](https://img.shields.io/badge/-HuggingFace-FFD21E?style=flat-square&logo=huggingface&logoColor=black)
![Pandas](https://img.shields.io/badge/-Pandas-150458?style=flat-square&logo=pandas&logoColor=white)

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---

### 🏥 Hospital LOS Data Mining
> *SQL Server · Power BI · Orange Data Mining · Python EDA · Database Design*

**A two-part end-to-end data engineering project** covering a production-grade hospital management database and a full exploratory data mining pipeline on 318,438 real hospital admission records.

**Part 1 — Database Architecture:**
- 🗄️ 22-table SQL Server DB normalised to **3NF**
- 🔑 6 stored procedures with TRY/CATCH error handling
- ⚡ 3 automation triggers (patient safety, audit trail)
- 🔐 RBAC security model with 6 roles + DENY escalation prevention
- 📊 10 SQL analytical views (RANK, DATEDIFF, window functions)
- 📈 21 performance indexes including covering indexes

**Part 2 — EDA & Data Mining:**
- 🔍 20 analytical questions answered across all 18 features
- 🔄 Full Orange Data Mining visual workflow
- 📊 Interactive Power BI 5-page dashboard
- ⚠️ Discovered critical **Excel auto-format bug** ('Nov-20' vs '11-20')

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**🏆 Key Numbers**

| Metric | Value |
|--------|-------|
| 📋 Records | **318,438** |
| 🏗️ DB Tables | **22** |
| 🔗 Foreign Keys | **28** |
| 📊 SQL Views | **10** |
| 🎭 RBAC Roles | **6** |
| ❓ EDA Questions | **20** |
| 📈 LOS Classes | **11** |
| 🏥 Hospitals | **32** |

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**🔑 Key Discovery:** Patient Visitors is the **single strongest predictor** of hospital LOS — mean visitors rises monotonically from 2.6 (short stays) to 7.9 (>100 days), acting as a proxy for illness severity.

**🛠 Technologies:**
![SQL Server](https://img.shields.io/badge/-SQL_Server-CC2927?style=flat-square&logo=microsoft-sql-server&logoColor=white)
![Power BI](https://img.shields.io/badge/-Power_BI-F2C811?style=flat-square&logo=powerbi&logoColor=black)
![Python](https://img.shields.io/badge/-Python-3776AB?style=flat-square&logo=python&logoColor=white)
![Orange DM](https://img.shields.io/badge/-Orange_DM-FF7F0E?style=flat-square)
![Pandas](https://img.shields.io/badge/-Pandas-150458?style=flat-square&logo=pandas&logoColor=white)

</p>

---

### 🛢️ Well Log Petrophysical Analysis
> *LAS File Processing · Archie Equation · OOIP/EUR Estimation · Petroleum Data Science*

**A complete 7-stage petrophysical well log analysis pipeline** built entirely in Python using a real LAS field file — replacing expensive proprietary software (Petrel/Techlog) with a reproducible, open-source workflow. Built on domain expertise from the Energia Inc internship and Suez University graduation project.

**7-Stage Analysis Pipeline:**

| Stage | Task | Method |
|-------|------|--------|
| 1 | LAS File Ingestion | `lasio` library |
| 2 | Log QC & Curve Validation | Null detection, depth alignment |
| 3 | Vshale Calculation | GR log linear method |
| 4 | Porosity Estimation | Density / Neutron / Sonic |
| 5 | Water Saturation | **Archie Equation** Sw = √(a·Rw / φᵐ·Rt) |
| 6 | Net Pay Cutoffs | Vsh < 50%, φ > 10%, Sw < 60% |
| 7 | OOIP & EUR Estimation | Volumetric method + Recovery Factor |

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**🛢️ Workflow Outputs**

| Output | Description |
|--------|-------------|
| 📉 Log Tracks | Multi-curve display |
| 📊 Crossplots | Porosity vs Sw |
| 🟩 Net Pay Flag | Cutoff-based zones |
| 💧 Sw Profile | Archie-derived |
| 🏔️ Vshale | GR-normalized |
| 🛢️ OOIP | Volumetric calc |
| 📈 EUR | Recovery estimate |

**Domain Bridge:**
Backed by real industry experience at Energia Inc — seismic, reservoir characterization & 3D Petrel workflows.

</td>
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</table>

**⚡ Why This Matters:** Combines 6 months of real reservoir characterization experience at Energia Inc + Suez University graduation project in seismic evaluation — all translated into open-source Python workflows.

**🛠 Technologies:**
![Python](https://img.shields.io/badge/-Python-3776AB?style=flat-square&logo=python&logoColor=white)
![lasio](https://img.shields.io/badge/-lasio-6D6D6D?style=flat-square&logo=python&logoColor=white)
![Matplotlib](https://img.shields.io/badge/-Matplotlib-11557C?style=flat-square&logo=python&logoColor=white)
![NumPy](https://img.shields.io/badge/-NumPy-013243?style=flat-square&logo=numpy&logoColor=white)
![Pandas](https://img.shields.io/badge/-Pandas-150458?style=flat-square&logo=pandas&logoColor=white)
![Petrel](https://img.shields.io/badge/-Schlumberger_Petrel-003DA5?style=flat-square&logoColor=white)

</p>

---

## 💼 Experience Timeline

```
2026  ──────────────────────────────────────────────────────────────────
      🤖 AI & Data Analysis Program — DigiLines / MCIT Egypt
         Dec 2025 – Jun 2026 (9 months)
         Python · Pandas · NumPy · Scikit-learn · Power BI · EDA

2024  ──────────────────────────────────────────────────────────────────
      💼 Active Freelancer — Upwork & Mostaql
         Data analytics projects · Dashboard design · Reporting

2022  ──────────────────────────────────────────────────────────────────
      🏢 Internship — Energia Inc (6 months) | Mar–Jul 2022
         Reservoir characterization · Seismic inversion
         3D Petrel workflows · Well planning · Cross-functional teams
         🎓 Graduation Project: 3D seismic analysis, well tops,
            prospective zone prediction

2021  ──────────────────────────────────────────────────────────────────
      🛢️ Online Internship — Khalda Petroleum Company | Jul 2021
         Well site geology

📐 Training — Seismic Interpretation & Reservoir Analysis
         Suez University Geological Engineering Dept | Mar 2021

2020  ──────────────────────────────────────────────────────────────────
      🗺️ Online Training — Geological & Structural Mapping | Nov 2020

2017  ──────────────────────────────────────────────────────────────────
      🎓 BSc  Petroleum Engineering
         Suez University, Faculty of Petroleum & Mining Engineering
         2017–2022
         Graduation Project 1: Seismic Evaluation (TP) Concession,
                              North Sea, Northwest Russia
         Graduation Project 2: Electrical Survey Geotechnical Study
                              Grade: EXCELLENT
```

---

## 🏆 Achievements

| 🏅 Achievement | 📋 Details | 📅 Year |
|----------------|-----------|---------|
| 🥇 **ML Pipeline Champion** | Built 30-config ML system achieving 75.29% accuracy + ROC-AUC 0.9193 on fitness classification | 2026 |
| 🚀 **Deployed AI App** | Published live Gradio prediction app on HuggingFace Spaces for Body Performance Analytics | 2026 |
| 🗄️ **Full DB Architect** | Designed 22-table production-grade SQL Server DB normalized to 3NF with RBAC security | 2026 |
| 🎓 **Excellent Grade** | Awarded Excellent on Electrical Survey Geotechnical graduation project — Suez University | 2022 |
| 🛢️ **Industry Experience** | 6-month internship at Energia Inc — real 3D seismic data, Petrel, reservoir characterization | 2022 |
| 🛢️ **Petroleum + Python** | Reproduced full Petrel/Techlog petrophysical workflow in open-source Python | 2025 |
| 📊 **Data Bug Hunter** | Identified critical Excel auto-format artifact ('Nov-20') in 318K-record hospital dataset | 2026 |
| 💼 **Active Freelancer** | Delivering data analytics projects on Upwork & Mostaql platforms | 2024– |

</div>

---

---
## 🧰 Skills Matrix

| Domain | Skills | Level |
|--------|--------|-------|
| **Machine Learning** | Classification, Regression, Feature Engineering, SHAP, Cross-Validation, Hyperparameter Tuning | ⭐⭐⭐⭐⭐ |
| **Python Data Science** | Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Gradio | ⭐⭐⭐⭐⭐ |
| **Data Visualization** | Power BI, Tableau, Matplotlib, Dashboard Design | ⭐⭐⭐⭐⭐ |
| **SQL & Databases** | SQL Server, Stored Procedures, Triggers, RBAC, Window Functions | ⭐⭐⭐⭐☆ |
| **Petroleum Geoscience** | Seismic Interpretation, Reservoir Characterization, Well Log Analysis, Seismic Attributes | ⭐⭐⭐⭐⭐ |
| **Geoscience Software** | Schlumberger Petrel, Techlog, ArcGIS, Surfer, Global Mapper, PLAXIS 2D&3D | ⭐⭐⭐⭐⭐ |
| **Data Mining** | Orange DM, Association Rules, Clustering, EDA, Pattern Mining | ⭐⭐⭐⭐☆ |
| **Cloud & Office** | Microsoft Azure, MS Office (Word, Excel, PowerPoint) | ⭐⭐⭐⭐☆ |
| **Languages** | Arabic (Native), English (Upper Intermediate — B2) | ⭐⭐⭐⭐⭐ |

</div>

---

## 📁 Repository Structure

```
📦 bassemsalah019-debug/
 ┣ 📜 README.md                              ← You are here
 ┣ 📂 projects/
 ┃ ┣ 📂 body-performance-ml/                ← ML Classification + Regression + Gradio App
 ┃ ┣ 📂 hospital-los-mining/                ← SQL DB + EDA + Power BI + Orange DM
 ┃ ┗ 📂 well-log-petrophysical/             ← LAS Processing + Archie + OOIP/EUR
 ┣ 📂 certificates/                         ← Digital certificates (PDF/PNG)
 ┗ 📂 assets/                               ← Images, charts, project previews
```

---

## <img src="https://raw.githubusercontent.com/Tarikul-Islam-Anik/Animated-Fluent-Emojis/master/Emojis/Objects/Telephone%20Receiver.png" width="35" /> Let's Connect!

<p align="center">
I'm always open to interesting conversations and collaboration opportunities.<br>
Whether you have a question, a project idea, or just want to say hi — feel free to reach out!
</p>

| Channel | Details |
|---------|---------|
| 📧 **Email** | [bassemsalah019@gmail.com](mailto:bassemsalah019@gmail.com) |
| 💼 **LinkedIn** | [linkedin.com/in/bassemsalahpd](https://www.linkedin.com/in/bassemsalahpd) |                                                              
| 🐙 **GitHub** | [github.com/bassemsalah019-debug](https://github.com/bassemsalah019-debug) |
| 📞 **Phone** | +20 100 117 9269 |
| 📍 **Location** | Cairo, Egypt 🇪🇬 |

<br/>

*Open to: Data Analyst · AI/ML Engineer · Petroleum Data Scientist · Freelance Projects*

<br/>

</div>

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