.png&w=256&q=75)
🤝 Top Collaborators
.png&w=640&q=75)
.png&w=640&q=75)
🤓 Latest Submissions
Federated Learning Security Design Document
This project implements a secure federated learning system for healthcare institutions, allowing hospitals to collaboratively train machine learning models without sharing raw patient data. Each hospital trains a local model and securely sends the model updates to a central server, where authentication, cryptographic hashing, and HMAC signatures verify integrity and authenticity. The system protects against malicious updates, model poisoning, and fake hospital attacks, while maintaining an audit trail for compliance. Federated Averaging aggregates only verified updates, ensuring both high AI accuracy and strong cybersecurity. This hybrid AI-security framework demonstrates a practical, privacy-preserving approach to collaborative healthcare analytics.
7 Feb 2026
HireScan
The Resume Shortlister is an AI-powered system designed to automate and streamline the initial stages of the hiring process. Instead of manually going through large volumes of resumes, recruiters can rely on the system to parse documents, extract key information, and evaluate candidate profiles with high accuracy. By analyzing elements such as skills, experience, education, certifications, achievements, and job-specific keywords, the system builds a comprehensive understanding of each applicant’s qualifications. The core functionality involves converting unstructured resume content—PDFs, DOCX files, or plain text—into structured data suitable for analysis. Once the information is extracted, the system intelligently matches it with the requirements provided in the job description. Factors like required skills, relevant experience, industry background, and preferred qualifications are all considered during this matching process. Based on these evaluations, the system generates relevance scores that reflect how closely each candidate aligns with the role. Using these scores, the Resume Shortlister ranks and shortlists top applicants, allowing hiring teams to quickly identify the most promising candidates without spending hours on manual screening. This automated ranking not only accelerates the hiring process but also ensures fairness and consistency. Unlike human evaluation, which may vary from person to person or be influenced by fatigue, the system applies the same criteria to every resume, making the selection process more reliable.
19 Nov 2025
