Laib Awan

Final-year Computer Science student with hands-on experience in Software Engineering, Full-Stack Web Development, and Artificial Intelligence. Proficient in building scalable web applications using Django, Django REST Framework, React.js, and PostgreSQL, along with developing AI-powered solutions using Python, Scikit-learn, TensorFlow, and NLP techniques. Experienced in designing RESTful APIs, implementing authentication and role-based access control, developing modern frontend interfaces, and integrating AI models into production workflows.

Strong understanding of software engineering principles, clean architecture, database design, and problem-solving, with a passion for building reliable, production-ready applications.

Software Engineer Intern

Contributed to the development of Jira Lite, a project management platform built with Django, Django REST Framework, PostgreSQL, and React.js.

• Designed and developed secure RESTful APIs for authentication, user management, project management, role management, dashboard analytics, and access control.
• Implemented JWT authentication, Role-Based Access Control (RBAC), and permission-based authorization to secure application resources. Designed normalized relational database models with Foreign Key relationships and optimized Django ORM queries for efficient data retrieval and performance.
• Implemented database transactions (transaction .atomic), input validation, centralized exception handling, and standardized API response structures to ensure data consistency and reliability.
• Developed dashboard APIs with aggregated statistics, project insights, and role-based data access while handling edge cases and business logic. Integrated backend APIs with the React.js frontend and collaborated using Git/GitHub, participating in code reviews, debugging, API testing with Postman, and following clean code and software engineering best practices.

AI Intern - Assort tech

• Developed document classification models using Python and Scikit-learn to categorize invoices, resumes, and utility bills. Built a semantic search system using Sentence Transformers and FAISS.
• Implemented PDF text extraction and data preprocessing pipelines. Evaluated model performance and improved classification accuracy through feature engineering. Collaborated with the development team to integrate AI models into backend APIs.

Full Stack Generative AI (Trainee) - Nexskill

• Developed a Python-based web scraping solution using Beautiful Soup and Requests to extract structured web data. Implemented pagination and detail-page scraping for product information collection and CSV export.
• Performed data cleaning, EDA, and feature engineering on real estate datasets for predictive analysis. Built and evaluated machine learning regression models with hyperparameter tuning using RMSE, MAE, and R² metrics.
• Developed stock price forecasting models using RNN, LSTM, and GRU architectures in TensorFlow/Keras. Applied time-series preprocessing, sliding-window sequence generation, and Early Stopping for model optimization. Utilized Python, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, Beautiful Soup, and Requests in project implementation.

Bachelor - Computer Science - University of Management and Technology