Mirza Milan Farabi@mmfarabi
is under improvement
8
Events attended
2
Submissions made
Bangladesh
4 years of experience
About me
I am a dedicated IT professional with over 4 years of experience in web development and IT support, specializing in creating user-friendly web solutions and maintaining efficient IT infrastructure. Currently, I serve as the Manager of Web Development at Loyal Communication, where I lead a team to optimize code quality, enhance user experience, and manage IT systems to deliver high-quality web solutions. I am also a freelance AI/ML app developer and an active competitor in various tech competitions. My expertise spans Python, Java, Machine Learning, Artificial Intelligence, Flask Web Development, AutoML, Data Science, Prompt Engineering, Feature Engineering, Software Development and more. I hold a Bachelor of Science in Computer Science and Engineering and a Diploma in Software Engineering. My academic background is complemented by professional certifications, including the Oracle Certified Professional, Java SE 6 Programmer and training in CCNA (Routing & Switching). In my current role, I am responsible for web server management, web design and development, website security, project management, IT support, and customer service. My dynamic skill set and ability to multitask in fast-paced environments make me an asset in delivering robust digital solutions and reliable IT services.
is under improvement
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🤓 Submissions
Hawaii Health Risk Assessment System
The Hawaii Health Risk Assessment System is an AI-powered healthcare solution designed to assess individual health risks, focusing on cardiovascular, metabolic, and infectious diseases while ensuring health equity across diverse populations. By using a generative AI model, this system generates detailed risk reports based on user-provided information, facilitates appointment scheduling, and offers data-driven insights for public health administrators. The project aligns with the innovation criteria of Population Health, Public Health and Patient Safety, and Clinical Research, aiming to reduce healthcare disparities and promote preventative care. Flowchart of the System: User Input: Users provide their personal and health-related information via a form. Form Submission: Data entered by the user is submitted to the backend. Generative AI Model Processing · The system processes the submitted data using a generative AI model. · Outputs a Health Risk Assessment Report. Health Risk Report Evaluation Two outcomes: · No Risk Detected: Display health tips and lifestyle recommendations to the user. · Risk Detected: Navigate to the Health Risk Status Panel. Health Risk Status Panel: · Displays the risk detected. · Includes a Book Appointment button. Book Appointment Workflow: User clicks Book Appointment, opening the Appointment Booking Panel. Features: · Dropdown to select hospital. · Calendar to choose date and time. · Health risk status is auto-filled and displayed. Data Storage: User responses and health reports are saved in: · SQLite Database: For structured storage and analysis. · .json File: For backup and interoperability. Admin Dashboard: Connects to the SQLite database and JSON files. Provides: · City/state health trend visualizations. · Patient-level insights. · Data for clinical research and public health policy-making. This project aims to bring fair healthcare to everyone, connect remote communities with providers, and guide better health decisions.
EcoSphereAI
EcoSphereAI is a cutting-edge platform designed to revolutionize connectivity systems by making them more efficient, sustainable, and adaptable to future demands. At its core, EcoSphereAI leverages advanced AI, machine learning, and big data analytics to address pressing challenges such as network congestion, energy inefficiency, and environmental impact. The platform offers a comprehensive suite of features, including energy optimization, predictive maintenance for network nodes, disaster risk assessment, traffic load forecasting, and sustainability reporting. By minimizing energy consumption, reducing carbon footprints, and improving network reliability, EcoSphereAI caters to network providers, users, and the environment alike. With a focus on scalability, the platform is future-ready for IoT and emerging technologies, enabling seamless integration and adaptability. EcoSphereAI represents a visionary step toward sustainable, green technology-driven networks, fostering a more connected and eco-friendly future.
