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Dur-e-Maknoon Nisar@MaknoonNisar
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4
Events attended
2
Submissions made
Pakistan
4 years of experience
About me
I have over 4 years of hands-on experience developing AI-driven solutions across diverse domains. My expertise includes building machine learning models for computer vision, time series forecasting, and information retrieval. I’ve worked on GIS-based AI applications for disaster management systems and developed medical imaging solutions integrating deep learning techniques with real-world scenarios. I specialize in Python, PyTorch, TensorFlow, and OpenCV, and have applied these technologies to innovative projects, such as AI-driven infrastructure resilience, autonomous driving systems, and smog prediction models. My ability to integrate AI with connectivity solutions, particularly in resource-constrained environments, makes me a strong contributor to AI-centric hackathons.
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🤝 Top Collabolators
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🤓 Latest Submissions
Geospatial Technology and Disaster Management
"Designed and implemented a comprehensive GIS-based platform that integrates tourism and disaster management functionalities. The platform incorporates multiple geospatial layers, including tourism spots, geological features, and natural hazards like earthquakes, floods, GLOF, and landslides. Key features include real-time weather updates via Weather APIs, Meteoblue, and Windy integration; Google Directions API for navigation; and virtual tours with 3D street views. It also includes infrastructure layers (rescue stations, hospitals, bus stations), hazard categorization, multimedia content (images/videos), and advisory PDFs for risk awareness. Enhanced user experience through a sidebar for easy navigation, content validation, and data refinement, fostering informed decision-making for users."
26 Jan 2025
AI Model for Space Education
Overview The AI-powered space education platform is an innovative learning system designed to make space science, astronomy, and astronautics more engaging and accessible. By leveraging advanced AI technologies, this platform provides personalized learning experiences, real-time data analysis, and interactive simulations that immerse users in space exploration. Key Features Personalized Learning – AI-driven algorithms tailor content based on users' interests, skill levels, and learning preferences. Interactive Simulations – Virtual models of planetary systems, spacecraft, and celestial events enhance understanding through hands-on experiences. Real-Time Space Data – Integration with satellite feeds, space agencies' databases, and live astronomy events provides up-to-date insights. AI Tutors & Chatbots – Conversational AI assists learners with queries, explanations, and guided lessons. Augmented & Virtual Reality (AR/VR) – Immersive environments allow users to explore planets, space missions, and cosmic phenomena. Citizen Science & Research Collaboration – Enables users to participate in real-world research projects and contribute to space discoveries. Target Audience Students and educators Astronomy enthusiasts Space research organizations Science communicators and media Impact & Goals This project aims to bridge the gap between theoretical learning and practical exploration, making space education accessible, engaging, and data-driven. By integrating AI, it fosters curiosity and deepens the understanding of space sciences, inspiring the next generation of astronomers, engineers, and space explorers.
9 Feb 2025
