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1.3.0

Muhammad_Suleman

Muhammad Suleman@Muhammad_Suleman

2

Events attended

1

Submissions made

Looking for experience!

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🤝 Top Collaborators

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Muhammad Saleem

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Sumera Rounaq

I am deeply passionate about Artificial Intelligence, with a strong focus on Computer Vision, Deep Learning, and Generative AI. As a researcher and educator, I actively contribute to cutting-edge AI projects involving medical image analysis, GANs, and predictive modeling. I love collaborating on innovative ideas and believe in using AI to solve real-world challenges. I bring skills in Python, TensorFlow, Keras, and PyTorch, and I enjoy both solo and team-based development. Currently exploring impactful AI applications through research, hackathons, and global collaboration.

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Humaira Rajar

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Rehan Ahmed

🤓 Latest Submissions

    Resource Allocation Optimizer

    Resource Allocation Optimizer

    he Resource Allocation Optimizer is an innovative AI-driven solution designed to address the challenges of bandwidth allocation in public sector networks, particularly in underserved regions. Public sector connectivity networks often face issues like resource scarcity, suboptimal prioritization, and inefficiencies in service delivery for critical sectors such as healthcare, education, and emergency services. This system leverages the power of Groq's Llama API to analyze incoming service requests and assign numerical priority scores based on urgency, bandwidth requirements, and the nature of the service. These prioritized requests are then processed by a dynamic resource allocation algorithm that distributes available bandwidth in real-time, ensuring that high-priority services receive the resources they need without delays.Key features of the project include: Simulated Environment: A network simulation generates realistic service requests for bandwidth from sectors like healthcare, education, and emergency services. AI-Powered Decision Making: The Groq Llama model analyzes requests and assigns priorities, enabling fast and accurate resource allocation. Dynamic Resource Allocation: The allocation algorithm ensures bandwidth is distributed efficiently, balancing critical needs and overall network availability. Interactive Dashboard: Built using Streamlit, the dashboard visualizes service logs, priorities, and bandwidth usage with real-time updates and dynamic charts, offering transparency and user engagement. This project has immense value in enhancing the efficiency of public sector networks by automating resource management, improving service outcomes, and reducing operational overhead. It is designed with scalability in mind, allowing integration with real-world networks and enabling further customization for specific scenarios.

    Hackathon link

    26 Jan 2025

👌 Attended Hackathons

    AI for connectivity hackathon

    AI for connectivity hackathon

    🔍Create AI-driven solutions using open-source technologies to optimize public sector network management—planning, procurement, and maintenance—for scalable, sustainable school connectivity in underserved regions. 📅 Join us January 24-26: Participate online or in person in Geneva to develop innovative solutions with peers globally. 👨‍🏫 Work alongside industry mentors for insights and guidance on your projects. 🏆 Compete for a chance to join the Lablab NEXT incubator program! 🧑🏻‍💻 Sign up before the Kick-Off Stream to secure your spot!

    AIstronauts: Space Agents on a mission

    AIstronauts: Space Agents on a mission

    🕒 2 days to innovate and build groundbreaking applications using the latest generative AI tools 🌟 Expert mentors will guide you every step of the way. 🤝 Work alone or form a team to build something extraordinary. 🏆 Win an opportunity to participate in the Lablab NEXT acceleration program. 🧑🏻‍💻 Sign up before the Kick-Off Stream to secure your spot!

📝 Certificates

    AI for connectivity hackathon

    AI for connectivity hackathon | Certificate

    View Certificate