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Graduate student at School of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi - 110016, India.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Agentic_AI_Reading_List-
May 30, 2026 – Present
Notes & PDFs from Google's 5-Day Agentic AI Course: agent architecture, MCP, context engineering, memory, agent quality, and production deployment.
View ProjectGNN_FreeSolve
June 3, 2025 – September 5, 2025
This repository contains the code for our paper "Graph Neural Networks for Predicting Hydration Free Energies with Physics-based Descriptors."
View ProjectLocality-Sensitive-Hashing
March 2, 2025 – March 2, 2025
Locality-Sensitive-Hashing — GitHub repository
View ProjectSurvey-on-Graph-Transformers
June 28, 2024 – July 6, 2024
Survey-on-Graph-Transformers — GitHub repository
View ProjectF2PGNN-AAAI2024
January 16, 2024 – January 16, 2024
This repository contains the code for our AAAI 24 paper titled No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation
View ProjectF2PGNN-AAAI24
December 12, 2023 – December 12, 2023
This repository contains the code for our AAAI 24 paper titled No prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation
View ProjectF2PGNN-AAAI24
July 26, 2023 – July 31, 2024
Official repo of the paper "No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation" accepted in AAAI 2024
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards academic research and advanced machine learning topics, particularly in Graph Neural Networks and Federated Learning. This aligns well with roles requiring deep technical expertise and a research-oriented mindset. The diversity of projects, including C++ and web development (HTML, CSS, JavaScript), suggests a broad technical curiosity, though the core focus remains on AI/ML research. The candidate's experience level is listed as 0, which contradicts the advanced nature of their research projects, suggesting a potential misclassification or that their experience is primarily academic/research-based rather than industry-based.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a focus on research and technical contributions.