Summary
Muhammad Tahir is a machine learning engineer and computer scientist with eight years of experience building applied AI solutions across finance, computer vision, and embedded systems. He has developed production-focused models and pipelines—from a supervised K-NN for stock movement prediction and LSTM/autoencoder experiments to a 90%‑accurate real-time emotion recognition CNN integrated with edge devices like Neural Compute Stick and Raspberry Pi. His background spans R&D at startups and product work at companies like Afiniti, where he translated performance-critical modules between languages and shipped SwiftUI interfaces, showing a comfort with both low-level optimization and user-facing features. Currently based in Chester, UK, he blends academic rigor (Advanced Computer Science masters) with practical deployment experience in trading and vision systems. An unexpected thread through his work is a knack for translating research prototypes into integrated pipelines (Backtrader, OpenCV) that drive measurable engagement and utility.
8 years of coding experience
3 years of employment as a software developer
Matriculation, Computer Science, A+, Matriculation, Computer Science, A+ at The Trust School
Intermediate, General Sciences, A, Intermediate, General Sciences, A at Government College University (GCU), Lahore
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at National University of Computer and Emerging Sciences
Master's degree, Advanced Computer Science, Master's degree, Advanced Computer Science at University of Chester