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Amrita Vishwa Vidhyapeetham
Data Scientist
June 20, 2026 – Present
Cortexa
April 27, 2026 – Present
Local-first DAG-based AI orchestration platform for grounded, self-correcting, client-ready deliverables.
View Projectthreatlens-ai
April 10, 2026 – Present
Real-time phishing detection engine using hybrid ML + structural analysis, designed for secure link-sharing in workspace environments (Slack, Notion, Docs).
View ProjectBISAG-Support-Ticket-Grievance-Routing-Auto-Reply
January 20, 2026 – Present
Goal * Classify incoming grievances/tickets to the correct department/category * Cluster similar grievances * Auto-generate a unified response (LM-based) for repeated issues
View ProjectClarity-Stack
December 28, 2025 – Present
ClarityStack is a local-first knowledge system that converts long AI chats into structured, version-controlled knowledge — while preserving the raw chat history as immutable ground truth. Backend: FastAPI + SQLite. Frontend: Next.js + Android (Jetpack Compose).
View ProjectGraphAMR-Multimodal-Relational-Graph-Learning-for-Antimicrobial-Resistance-Prediction
December 24, 2025 – Present
GraphAMR-Multimodal-Relational-Graph-Learning-for-Antimicrobial-Resistance-Prediction — GitHub repository
View ProjectFaceVault
December 24, 2025 – Present
Designed and built an identity-aware face retrieval platform with safety-gated routing and FAISS-based search — from dataset ingestion to UI
View ProjectDynamic-Credit-Risk-Assessment-using-Multi-Task-DL-and-Bayesian-Optimization-
November 19, 2025 – November 21, 2025
Dynamic-Credit-Risk-Assessment-using-Multi-Task-DL-and-Bayesian-Optimization- — GitHub repository
View ProjectCultural Fit Analysis
The candidate demonstrates a strong drive for personal projects, indicating initiative and a passion for technology. The diversity of projects, ranging from AI orchestration to specific ML applications (phishing, credit risk, face retrieval), suggests adaptability and a broad interest in problem-solving. The alignment with a 'Data Scientist' role is strong given the project focus. However, the lack of team-based or open-source contributions in the provided data makes it difficult to fully assess collaborative cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions suggest an ability to conceptualize and execute complex technical ideas. The focus on 'local-first' systems and 'self-correcting' platforms indicates an inclination towards robust and autonomous solutions. However, without psychometric test results or interview data, it's difficult to assess specific soft skills like teamwork, stress handling, or communication clarity in a professional setting.