
Software Engineering Intern with less than a year in web development and machine learning with proje
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Computer Science undergraduate specializing in web development and machine learning, with hands-on experience building scalable applications and AI-driven solutions. Proven ability to deliver full-cycle software projects, including a BIM-based design platform and fraud detection system. Strong problem-solving skills with experience in hackathons and collaborative development environments.
Informatics Institute of Technology (IIT)
BSc (Hons) · Software Engineering
August 1, 2024 – June 30, 2028
ArchiSri Smart House Design System
January 1, 2026 – Present
Architected a technical blueprint for a web-based BIM platform, implementing a multi-layered system for real-time architectural design and high-fidelity residential visualisation. Engineered complex algorithmic logic for wall network topology and automated 3D extrusion, ensuring precise geometric accuracy and advanced metadata management. Integrated Industry Foundation Classes (IFC) standards to maintain global interoperability, delivering a scalable solution for cross-platform technical integration.
Criminal Catcher System
January 1, 2026 – Present
Building a machine learning system to predict crime likelihood and identify potential suspects using structured datasets. Performing data preprocessing, feature engineering, and exploratory data analysis (EDA) on crime datasets. Training and evaluating classification models to improve prediction accuracy. Developing a modular backend using Python with libraries such as Scikit-learn, Pandas, and NumPy. Designing future integration for real-time monitoring and automated alert systems. Focused on creating a scalable and practical solution for smart policing applications.
Credit Card Fraud Detection System
January 1, 2026 – June 1, 2026
Developed a supervised machine learning model to identify and mitigate fraudulent transactions, enhancing financial security protocols through predictive analytics. Implemented advanced feature engineering and data preprocessing techniques, achieving a 70% detection accuracy on historical datasets. Optimised model performance through systematic data cleaning and statistical validation, delivering a functional prototype for anomaly detection.
View ProjectCultural Fit Analysis
The candidate's diverse project portfolio, including machine learning, web development, and BIM, indicates a broad interest in software engineering domains. Their active participation in hackathons and sports, coupled with leadership roles, suggests a proactive, collaborative, and competitive spirit. This aligns well with a dynamic, innovation-driven culture. The target role of 'Software Engineering Intern' is appropriate for their current experience level and academic status. The breadth of skills and project types suggests adaptability and a willingness to learn across different technical areas, which is a positive indicator for cultural fit.
Soft Skills & Operational Fit
The candidate's extensive involvement in sports and event organization, including leadership roles, suggests strong teamwork, leadership, and organizational skills. Their hackathon participation also indicates an ability to collaborate effectively under pressure and solve problems creatively. These attributes are valuable for an intern role, demonstrating a proactive attitude and potential for growth within a team-oriented environment. However, without specific psychometric test results, a deeper assessment of stress handling and work attitude is not possible.