I am a passionate Full Stack Developer and Computer Science student at the University of Central Punjab. My primary focus is on building scalable, production-grade web applications with the MERN stack and Next.js. Alongside my expertise in web engineering, I also have hands-on experience in Machine Learning and AI model training, applying supervised and ensemble learning techniques for real-world datasets. Known for my strong problem-solving abilities and logical approach, I aim to engineer robust applications and contribute to innovative projects that create impactful digital experiences.
October 2022 - Present
- Designed, developed, and deployed full-stack web applications using the MERN stack (MongoDB, Express.js, React.js, Node.js) and Next.js for server-side rendering and optimized performance.
- Implemented RESTful APIs, middleware, and authentication flows with JWT and OAuth to ensure secure and scalable backend architectures.
- Built responsive, mobile-first UIs with React.js, Tailwind CSS, and Bootstrap, incorporating component reusability, lazy loading, and SSR for enhanced performance.
- Collaborated with cross-functional teams to design and deliver user-centric features aligned with business requirements.
- Enhanced website performance, usability, and SEO, contributing to measurable growth in customer engagement.
- Worked with tools such as Bootstrap, Elementor Pro, and Oxygen Builder for faster prototyping and efficient development cycles.
- Trained and evaluated a Linear Regression model on the Insurance Dataset for predicting medical costs.
- Built a binary classification neural network to provide personalized diet recommendations for patients with hypertension, diabetes, cardiovascular disease, or none, based on health metrics.
- Applied AdaBoost (Adaptive Boosting) for sentiment analysis on text datasets, improving classification accuracy on polarized opinions.
- Experimented with multiple supervised models (Random Forest, SVM, Logistic Regression) and deep learning frameworks (TensorFlow, Keras, PyTorch) to benchmark performance on structured and unstructured datasets.
- AWS Certified Cloud Practitioner
Demonstrates knowledge of AWS cloud services, foundational cloud concepts, and their application in real-world scenarios.
September 2021 - October 2025
- Front-End: HTML, CSS, Bootstrap, JavaScript (ES6+), React.js, Next.js, Tailwind CSS
- Back-End: Node.js, Express.js, RESTful APIs
- Databases: MongoDB, MySQL
- Machine Learning & AI:
- Regression Models (Linear/Logistic Regression)
- Neural Networks (TensorFlow/Keras, PyTorch)
- Ensemble Methods (AdaBoost, Random Forest, Gradient Boosting)
- NLP (Sentiment Analysis, Text Classification)
- Other Skills:
- Writing and analyzing IEEE research papers and technical articles.
- Experience with Figma for UI/UX prototyping and wireframing.
- WordPress (Elementor Pro, Oxygen Builder), jQuery.
- Python (NLP, ML model training), C++, C.
π Iβm interested in building modern web applications with Next.js, scalable backends, and AI-driven solutions, as well as exploring cloud-native architectures, data-driven systems, and microservices.
π» I have worked on MERN and Next.js projects, state management with Redux/Context API, real-time apps with WebSockets/Socket.IO, and multiple ML model trainings across structured/unstructured data.
π Pronouns: He/Him
π« Email: alizaman6780@gmail.com | l1f21bscs1119@ucp.edu.pk
LinkedIn: Ali Zaman - Full Stack Developer
ποΈ Iβm looking to collaborate on open-source projects, SaaS platforms, and enterprise-grade solutions involving MERN stack, Next.js, Machine Learning, Cloud technologies, and AI integrations.