Muhammad Awais

Built and deployed a WhatsApp Business chatbot for a UK-based HVAC company using n8n and the Meta Cloud API, handling webhook verification, message templates, and opt-in compliance. Developing an AI-powered SaaS platform for a Hong Kong client assessing company eligibility for R&D Tax, Patent Box, and Intangible Assets incentives.

Developed and deployed machine learning models for real-world AI applications, improving prediction accuracy and system performance. Built and optimized data pipelines, model training workflows, and inference systems using Python and modern ML frameworks.

Conducted research in core machine learning, spanning computer vision, deep learning, and generative AI, under a merit-based scholarship. Co-authored Angular Networks (NeurIPS 2026), a low-bit learning framework that quantizes both weights and activations without straight-through estimators.

Developed a chatbot for PERA as part of a government collaboration. Served as technical counsellor and conducted candidate interviews as part of PERA's official hiring process.

Served two terms as TA; delivered lectures and led lab sessions on ML fundamentals and practical implementation. Mentored students on assignments and projects with an emphasis on model development and evaluation.

Delivered websites end to end, from design through deployment, using PHP and Laravel.

Built machine learning solutions in Python across classification and prediction tasks.

Grade: 3.30 / 4.00

Pursuing an MS in Data Science with a thesis on Binary Neural Networks, supported by a merit-based research scholarship.

Grade: 3.72 / 4.00

Completed a BS in Computer Science with a final year project on autonomous field data collection using drones, supported by a merit-based fee-waiver scholarship.