Sylvia Barick
@Sylvia15
Sylvia Barick
@Sylvia15
AI/ML-focused B.Tech student | Full-stack & Web3 developer | Hackathon enthusiast | Building real-world, impact-driven projects
AI/ML-focused B.Tech student | Full-stack & Web3 developer | Hackathon enthusiast | Building real-world, impact-driven projects
Kolkata, India
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Top Projects
Top Projects
This system addresses major challenges in remote technical interviews, particularly impersonation, cheating, and lack of real-time monitoring. With rising remote hiring, ensuring that the right candidate is attending the interview has become increasingly difficult. Traditional video interviews are vulnerable to fraud, such as sending a proxy or using hidden support. The solution uses real-time face and voice verification to continuously confirm the candidate’s identity throughout the session. It integrates liveness detection, voiceprint matching, and cross-session consistency checks to prevent impersonation. The system also detects anomalies such as multiple faces, prolonged absence, or voice mismatches, and alerts recruiters instantly. It adapts to real-world conditions with low-light facial recognition, noise suppression, and robust handling of partial occlusions like glasses or masks. Importantly, it stores data securely, using encrypted biometric templates and maintaining compliance with GDPR/CCPA regulations. Recruiters get a dashboard with live status, dynamic risk scores, session replays, and downloadable reports—ensuring transparency and integrity. Overall, this system provides a trusted, secure, and scalable solution for conducting high-stakes remote assessments, allowing companies to make confident hiring decisions based on verified candidate participation.