Hey! I’m Chirag GSoC'25@Jenkins contributor, an AI enthusiast diving deep into machine learning and deep learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Student
Data Scientist
June 12, 2026 – Present
railmind
June 12, 2026 – Present
Multi-agent control room for Indian Railways autonomous agents negotiate delays, platforms, and crew swaps on a live digital twin. Built for FAR AWAY 2026.
View ProjectHive
May 5, 2026 – Present
Local-first agent OS. Spawn persistent AI agents that collaborate, write code, and use tools autonomously. Multi-model (Claude, Codex, LM Studio). Config-driven with pre-built agent presets.
View ProjectOSS-Skills
April 27, 2026 – Present
15 Claude Code skills that walk you through your first open source contribution. Built by a GSoC mentor.
View Projectdevcard
April 25, 2026 – Present
🪪 DevCard Auto-generate agent-readable developer profiles from GitHub. A standardized schema + CLI that extracts who a developer is, what they build, and how they work from pure GitHub signals. No LLM needed. Agents welcome.
View ProjectFungiClassifier
November 15, 2024 – November 18, 2024
FungiClassifier is a deep learning project focused on the classification and identification of different mushroom species using Convolutional Neural Networks (CNNs). The model is trained to classify mushrooms based on their images, helping in identifying edible and poisonous varieties.
View ProjectNexNet
August 8, 2024 – November 30, 2025
NexNet ⚡ is a simple and easy-to-use neural network library 🧠. It provides all the essential building blocks like layers, activations, and optimizers to help you create and train your own neural networks from scratch 🛠️. Whether you're learning or building projects, NexNet makes it easy to understand and experiment with neural networks 🚀.
View ProjectCultural Fit Analysis
The candidate's portfolio shows a strong inclination towards innovative and cutting-edge AI/ML projects, including multi-agent systems and LLM applications. This aligns well with a culture that values research, development, and pushing technological boundaries. The diversity of projects, from deep learning classification to agent operating systems, indicates a broad interest and adaptability. However, the lack of team-based projects or professional experience makes it challenging to fully assess collaboration and cultural integration.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and experimental approach to problem-solving. The focus on personal projects suggests self-motivation and a drive to learn and build. However, without specific assessment data on communication, logical reasoning, or teamwork, it is difficult to fully assess soft skills and operational fit.