Student : P Magodi
About the student
I’m a Computer Science graduate pursuing Honours in IT (AI) with expertise in AI, Machine Learning, and Full-Stack Development. I’ve built impactful projects like a fairness-aware admissions platform, ECG autoencoder, and sign language interpreter. Skilled in Python, Java, and React, I’m a collaborative leader passionate about creating ethical, innovative AI solutions for real-world challenges.
About the Project
AI-Powered University Admissions Simulation System: Advancing Equity in Higher Education Our project addresses critical challenges in university admissions by developing an intelligent multi-agent simulation system that revolutionizes how educational institutions balance academic merit with social equity. The system tackles persistent issues of bias and inequality in traditional admission processes through data-driven, transparent decision-making. Technical Innovation: The platform employs a sophisticated multi-agent architecture featuring four specialized agents: Simulation Administrators, Applicants, Admissions Officers, and Registrars. Each agent mirrors real-world university workflows while enabling large-scale simulation testing. The system integrates cutting-edge machine learning algorithms including Hybrid Gradient Boosting, Support Vector Regression, Deep Neural Networks, and Neuro-evolutionary algorithms, all optimized for GPU acceleration to efficiently process thousands of applicant profiles simultaneously. Technology Stack: Built with Python FastAPI backend, React.js frontend, MySQL database management, and CuPy for GPU optimization, the system ensures scalable performance and intuitive user interaction through comprehensive dashboards and real-time monitoring capabilities. Social Impact: Beyond technical achievement, the platform addresses urgent societal needs for educational equity. Universities can simulate various admission scenarios, test algorithmic approaches, and analyze demographic impacts on underrepresented populations including rural students, economically disadvantaged applicants, and diverse ethnic groups. Comprehensive fairness metrics and equity constraints ensure institutions maintain academic standards while promoting inclusive excellence. Real-World Applications: The system enables evidence-based policy development, algorithm auditing, and strategic enrollment management planning. Universities can optimize their admission strategies to improve diversity outcomes while preserving academic quality, ultimately contributing to enhanced social mobility and educational justice. Results: Simulation results demonstrate measurable improvements in demographic representation while maintaining competitive academic standards, providing actionable insights for transforming university admission practices toward greater fairness and transparency.
