🎓 Computer Engineering Student at NUST | 💻 Machine Learning Engineer | 📊 Data Science Enthusiast

Motivated and research-oriented Computer Engineering student at NUST with hands-on experience in:

• Machine Learning & AI (TensorFlow, PyTorch, Scikit-learn)
• Data Science & Visualization (Pandas, NumPy, Seaborn, Matplotlib, Power BI)
• Software Development & Frameworks (C++, Java, Flask, FastAPI, Streamlit, Gradio)
• Database Engineering (MSSQL, MySQL)
• Version Control & Collaboration (Git, GitHub)

I’m passionate about solving real-world problems through ML, AI, and data-driven insights, and have authored publications in Deep Learning and Computer Vision.

• Programming Languages: Python (Flask), C++, Java, SQL, DAX
• Data Science & ML: TensorFlow, PyTorch, Scikit-learn
• Business Intelligence Tools: Power BI
• Databases: MSSQL, MySQL
• Data Analysis & Visualization: Pandas, NumPy, Seaborn, Matplotlib
• Frameworks & Deployment: FastAPI, Streamlit, Gradio
• Version Control: Git

🔹 Machine Learning Engineer Intern — Ebryx Pvt. Ltd. (June 2025 – Present)

• Built ML pipelines: preprocessing, training, evaluation, and hyperparameter tuning.
• Implemented classical algorithms (Logistic Regression, kNN, Naive Bayes, Decision Trees, KMeans).
• Explored NLP & LLM-based solutions for cybersecurity threat intelligence.

🔹 Freelance Machine Learning Engineer

• Designed and deployed ML models for regression, classification & visualization.
• Wrote research papers on AI topics.
• Delivered custom AI solutions to clients.

🔹 Machine Learning Intern — Codic Solutions (July 2024 – Aug 2024)

• Built real-time Shoplifting Detection System using CNNs on surveillance streams.
• Improved detection accuracy by 30% with hyperparameter tuning & augmentation.
• Integrated ML pipeline into existing security infrastructure.

• Motor Imagery EEG Classification Using Fine-Tuned EfficientNetB0
  2023 3rd International Conference on Artificial Intelligence (ICAI)
  [IEEE Link]

• Multiscale Self-Attention for UAV-based Infrared Thermal Image Detection
  Engineering Applications of Artificial Intelligence, 2025
  [Elsevier Link]

• Raspberry Pi + OpenCV, achieved 25+ FPS without deep learning.
• Improved accuracy under varying lighting by 35% with adaptive thresholding.

• Decision Tree model with 91% accuracy.
• Predicted cancer risk using patient lifestyle/medical data.

• Classified speech, music, and noise using spectrograms.
• High accuracy achieved on audio datasets.

• CNN-based real-time video surveillance solution.
• Enhanced theft prevention by 30%.

• EfficientNet-B0 model for mammogram analysis.
• Optimized for early-stage diagnosis accuracy.

• Airport Management System (Java) – Console-based system for flights & check-ins.
• CPU Scheduling with GUI (C++ & Qt) – Visual simulator for scheduling algorithms.
• Search Engine (C++/Hash Maps) – Fast search with GUI-based interface.

• Python for Everybody Specialization – University of Michigan
• Data Visualization with Python – IBM
• Data Analysis Professional Certificate – IBM
• Databases and SQL for Data Science with Python – IBM

⭐️ From Hashir-Ashraf-Awan