
3
3
1 year of experience
I am a Doctor of Physical Therapy (DPT) student with a clinical interest in rehabilitation, human movement, and patient recovery. My studies focus on anatomy, biomechanics, therapeutic exercises, and evidence-based physiotherapy practice. I do not have prior experience in artificial intelligence, but I am interested in learning how AI can be applied in clinical rehabilitation. I am currently working on an idea to use AI in physiotherapy to assist with exercise guidance, patient monitoring, and improving treatment outcomes. My aim is to combine clinical knowledge with emerging technology to support better and more accessible rehabilitation care.

CareSync AI is an enterprise-grade healthcare intelligence platform designed to transform healthcare operations from reactive management to proactive, AI-driven decision-making. The platform combines autonomous AI agents, predictive analytics, healthcare supply chain intelligence, and real-time web data to continuously monitor hospital resources, detect emerging risks, and prevent operational crises before they occur. Using Bright Data's web infrastructure, CareSync AI analyzes live outbreak trends, supplier disruptions, medicine availability, logistics risks, and market intelligence to generate actionable recommendations for healthcare organizations. The system can predict oxygen shortages, medicine stock depletion, ICU overcrowding, and emergency resource stress while autonomously evaluating suppliers and procurement options. Through its multi-agent architecture, CareSync AI provides hospitals, governments, pharmaceutical networks, and emergency response organizations with a unified operational intelligence platform. By integrating healthcare operations, supply chain monitoring, AI procurement reasoning, and executive risk reporting, CareSync AI enables faster emergency response, reduced operational waste, improved resource allocation, and enhanced patient safety. The platform serves as an AI Operating System for Healthcare Infrastructure, helping organizations build more resilient, efficient, and future-ready healthcare ecosystems.
31 May 2026

Rehaby is an AI-powered rehabilitation intelligence platform designed to bridge the gap between hospital-based physiotherapy and home recovery. Many patients receive proper monitoring and rehabilitation support while admitted in hospitals, but after discharge, rehabilitation often becomes unsupervised. Patients may perform exercises incorrectly, lose motivation, misunderstand instructions, or skip therapy sessions completely. This problem is especially common among elderly, post-surgical, orthopedic, neurological, and cardiovascular rehabilitation patients who may also face difficulties traveling long distances for short clinical follow-ups. Improper rehabilitation can increase recovery time, risk of re-injury, and workload on healthcare professionals. Rehaby addresses this challenge through an intelligent AI-driven rehabilitation ecosystem that enables patients to safely continue physiotherapy exercises from home while remaining connected with clinicians. The platform combines computer vision, real-time posture tracking, and adaptive rehabilitation intelligence to analyze patient movements and provide immediate corrective feedback. Using technologies such as MediaPipe Pose, OpenCV, TensorFlow Lite, and FastAPI, Rehaby performs live joint angle analysis, posture correction, repetition counting, and movement scoring directly through a web-based interface. The patient-side application offers real-time camera posture tracking, skeleton overlays, AI voice guidance, visual corrective feedback, and session summaries to improve exercise accuracy and adherence. On the clinician side, a mobile dashboard allows healthcare professionals to monitor patient progress remotely through analytics, form score trends, session histories, and recovery performance insights. The system also supports Urdu voice interaction and low-bandwidth accessibility to improve usability for diverse patient populations.
19 May 2026

QuantTrader Lite is a fully autonomous AI-powered crypto trading agent designed to solve three core problems in modern trading: information overload, lack of trust in AI decisions, and slow human reaction time. Built for the Lablab.ai Hackathon 2026 (Kraken CLI Track), the system continuously fetches live market data, analyzes it using Groq AI (Llama 3), and executes paper trades via Kraken CLI—all without human intervention. 🧠 How It Works The system follows a 5-step autonomous pipeline: Market Data Ingestion Fetches real-time BTC price and 24h change from CoinGecko API. AI Decision Engine Groq-powered Llama 3 analyzes market trends and generates a BUY / SELL / HOLD signal along with a clear, human-readable explanation. Trade Execution The decision is executed using Kraken CLI in sandbox mode (paper trading). Logging & Transparency Every action is recorded in a structured trade_log.json file for auditability. Live Dashboard A Streamlit interface displays signals, trade history, and charts with auto-refresh every 60 seconds. 💡 What Makes It Different Explainable AI Every decision includes a clear reason—no black-box trading. Fully Autonomous Runs continuously with zero human input. Hackathon-Compliant Direct integration with Kraken CLI ensures full alignment with challenge requirements. Simple but Powerful Built entirely in Python with a lightweight, production-ready architecture. 🛠 Tech Stack Groq API (Llama 3) → AI decision-making Kraken CLI → Trade execution (sandbox) CoinGecko API → Live market data Streamlit → Real-time dashboard Python 3.11+ → Core system 🎯 Impact QuantTrader Lite transforms crypto trading from manual, overwhelming, and opaque into a system that is: ⚡ Fast 🔍 Transparent 🤖 Autonomous It not only trades—but also teaches users why each decision is made, bridging the gap between AI and human trust.
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