Senior AI/ML Engineer | GenAI & Agentic AI Builder | 8+ Years Exp in Software Development | M.Tech Graduate | Research & Quantum Computing Enthusiast
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Disaster-Management-System-Climate
June 8, 2026 – Present
A self-contained, agent-based AI framework for multi-hazard natural disaster prediction using FastAPI microservices and local SLMs (Small Language Models).
View ProjectAgentic-Honey-Pot-for-Scam-Detection-Intelligence-Extraction
January 25, 2026 – Present
Agentic-Honey-Pot-for-Scam-Detection-Intelligence-Extraction — GitHub repository
View ProjectAI-Generated-Voice-Detection
January 25, 2026 – Present
AI systems can now generate very realistic human-like voices. Because of this, it is difficult to identify whether a voice recording was spoken by a real human or generated by an AI system. In this problem, students must build an API-based solution that detects whether a given voice sample is AI-generated or Human, across five supported languages.
View Projectrag-youtube-video
November 5, 2025 – November 5, 2025
rag-youtube-video — GitHub repository
View Projecthealth-llm-diana
October 27, 2025 – October 27, 2025
health-llm-diana — GitHub repository
View ProjectReinforcement-Learning-RL-Algorithms.
February 22, 2025 – March 22, 2025
Reinforcement Learning (RL) is a machine learning approach where an agent learns by interacting with an environment to maximize cumulative rewards. It uses states, actions, rewards, and policies to improve decision-making. Key algorithms include Q-learning, DQN, PPO, and A3C.
View ProjectDomain-Specific-FAQ-Chatbot
December 14, 2024 – December 14, 2024
Domain-Specific-FAQ-Chatbot
View ProjectMaze-Solving-AI
December 13, 2024 – December 13, 2024
This project involves designing and implementing a maze-solving AI capable of finding the shortest path using algorithms like A* (A-Star), Dijkstra's Algorithm, or Breadth-First Search (BFS). The AI will navigate a given maze to identify the optimal path from a start point to an endpoint, considering obstacles and potential dead ends.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on personal AI/ML projects, demonstrating strong initiative and a passion for the field. However, the lack of team-based projects or professional experience makes it difficult to assess cultural fit in a collaborative work environment. The projects align well with a Data Scientist role, indicating a strong interest in the domain.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong technical focus, but collaboration, problem-solving approach, and communication style cannot be evaluated without interview data or specific assessment results.