Muhammad Haseeb

AI Solutions Developer & E-commerce Integration Specialist at ExactFlow Solutions Specialized in developing intelligent chatbot solutions and dynamic dashboards for e-commerce businesses, leveraging customer data analytics to drive business insights and automation. Expert in building scalable integrations with major e-commerce platforms including Amazon, BackMarket, and Shopify through webhook implementations. Core Expertise:

Chatbot Development & Training: Design and deploy conversational AI systems tailored to e-commerce customer service and engagement Dashboard Solutions: Create comprehensive data visualization dashboards that transform raw customer data into actionable business intelligence E-commerce Integrations: Seamless webhook-based integrations across multiple platforms (Amazon, BackMarket, Shopify) for real-time data synchronization Customer Data Analytics: Transform e-commerce datasets into meaningful insights for improved customer experience and business optimization

Technical Focus:

Real-time data processing and webhook management AI/ML model training for conversational interfaces Customer behavior analysis and pattern recognition Cross-platform e-commerce data harmonization

Passionate about bridging the gap between complex e-commerce data and user-friendly AI-powered solutions that enhance customer experience while providing businesses with powerful analytical tools for growth and optimization.

Led the development of an OCR system for medical records, enabling precise text extraction for efficient processing and record management. • Created a plagiarism detection tool to compare medical records, ensuring originality and compliance in healthcare documentation. • Developed an AI-generated text detection system leveraging Large Language Models (LLMs) to identify synthetic text in medical records. • Designed a virtual assistant Alivia chatbot, Alivia GPT application that allows users to create custom AI assistants with file-based contextual responses, enhancing user experience and automation. • Developed a product for Apple Vision Pro, enabling an immersive visualization of fraud, waste, and abuse analytics in the healthcare sector. • Implemented AI-driven X-ray analysis to detect duplicate medical images, improving diagnostic accuracy and reducing redundant records. • Created an AI-based cardiac stenosis detection system that analyzes heart X-rays to assist in early diagnosis and treatment planning. • Specialized in healthcare fraud detection, actively working on multiple projects aimed at mitigating fraud, waste, and abuse in medical billing and insurance claims.

Machine Learning Research Scientist & Data Analyst

ML Model Development: Designed and trained advanced machine learning models for predictive analytics across various domains Research Publications: Authored and published research papers contributing to the academic and industrial machine learning community Feature Engineering: Specialized in extracting and optimizing meaningful features from complex datasets to improve model performance Hyperspectral Image Analysis: Developed sophisticated algorithms for processing and analyzing hyperspectral imaging data for various applications Medical AI Research: Led a groundbreaking lung cancer detection project utilizing deep learning architectures to achieve early-stage cancer identification through medical imaging

Key Achievements:

Successfully implemented end-to-end ML pipelines from data preprocessing to model deployment Advanced expertise in computer vision applications, particularly in medical imaging and hyperspectral analysis Proven track record in translating complex research concepts into practical, deployable solutions