Haleema Malik

Selected for the AWS AI & ML Scholars Practitioner Program, gaining hands-on training in Artificial Intelligence, Machine Learning, and Generative AI concepts through industry-focused learning modules. Developed practical skills in data analysis, machine learning workflows, model evaluation, AI, and Generative AI applications.

Covered topics related to modern communication networks, including network architecture, data transmission, routing and switching, wireless communication, network protocols, and fundamentals of mobile and cellular networks. Attended technical sessions, worked through practical examples, and discussed real-world networking scenarios.

Learned to write basic quantum circuits with single qubits and simple gates using Qiskit, while shadowing senior team members. Conducted experiments using quantum simulators, analyzed results, reviewed research papers, and contributed to a quantum walk search project that won 1st Prize at ICEQST.

Built and maintained data preprocessing pipelines, handling cleaning, normalization, and augmentation to ensure high-quality inputs for model training. Collaborated with senior engineers to run training experiments, track performance metrics, and document outcomes.

Gathered datasets on Channel State Information (CSI) for Human Activity Recognition (HAR) using transmitters and Wi-Fi signals. Preprocessed collected data into amplitude signals and converted them into heatmaps for training Convolutional Neural Networks (CNNs).

Grade: First Class Honours

Graduated with a BSc (Hons) in Software Engineering, achieving First Class Honours. Completed key courses including programming, data structures, algorithms, and software engineering principles.

Selected for a highly competitive, year-long AWS learning scholarship program, gaining hands-on experience and expert-led training in AI and Machine Learning.

Completed CS50 Introduction to Programming with Python, learning core programming concepts and applying Python for problem-solving and data analysis.

Completed courses on tokenization to vector quantization and LangChain for LLM application development, enhancing understanding of NLP and LLM applications.