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Schedule Interview NowMy name is Gohar R. and I have over 0 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, AI Agent Development, Python, LangChain, Chatbot, etc.. I hold a degree in Bachelor of Computer Science (BCompSc). Some of the notable projects I've worked on include: AI-Powered Restaurant Reservation & Call-Handling Automation (Relair), Wellness Website Optimization & AI Automation Integration, Intelligent Roof Anomaly Detection Platformm, LLM Fact-Checking and Reliability Framework, Jet Engine Combustion Digital Twin (ML + Simulation), etc.. I am based in Manchester, United Kingdom. I've successfully completed 8 projects while developing at Softaims.
I am a business-driven professional; my technical decisions are consistently guided by the principle of maximizing business value and achieving measurable ROI for the client. I view technical expertise as a tool for creating competitive advantages and solving commercial problems, not just as a technical exercise.
I actively participate in defining key performance indicators (KPIs) and ensuring that the features I build directly contribute to improving those metrics. My commitment to Softaims is to deliver solutions that are not only technically excellent but also strategically impactful.
I maintain a strong focus on the end-goal: delivering a product that solves a genuine market need. I am committed to a development cycle that is fast, focused, and aligned with the ultimate success of the client's business.
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Relair is a platform that serves as a 24/7 virtual host for restaurants answering calls, booking tables, and confirming reservations so no booking is ever missed. I designed and built the backend and
I optimized and enhanced the Anahana wellness platform by integrating advanced AI automation workflows. The project focused on streamlining content delivery, improving site usability, and enabling sca
Utilizing advance artificial intelligence for precise identification of structural and material anomalies, complemented by natural language processing to deliver comprehensive diagnostic reporting for
This project develops a structured fact-checking framework for large language models (LLMs). It combines automated verification pipelines, human feedback loops, and model tuning strategies to ensure o
Research project building a hybrid digital twin of jet engine combustion to predict emissions and optimize fuel burn. Engine telemetry (temperature, pressure, air–fuel ratio, EGT, exhaust species) is
Bachelor of Computer Science (BCompSc) in
2014-01-01-2018-01-01