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🧠 About Me

class AathithyaArasu:
    def __init__(self):
        self.name         = "Aathithya Arasu S"
        self.location     = "Chennai, India"
        self.degree       = "B.Tech Information Technology (Expected May 2027)"
        self.college      = "St. Joseph's College of Engineering"
        self.cgpa         = 8.20

        self.stack = [
            "PyTorch", "LangChain", "llama.cpp", "Ollama",
            "FastAPI", "Qdrant", "FAISS", "Docker",
            "AWS SageMaker", "OpenCV", "EfficientNetB7"
        ]

        self.currently_learning = [
            "Advanced Agentic RAG Architectures",
            "Graph RAG & Knowledge Graph Retrieval",
            "LLM Fine-tuning on Constrained Hardware",
            "Java DSA for Interview Readiness"
        ]

        self.fun_fact = (
            "Built a production RAG pipeline during internship "
            "that got adopted by the internal team in week one."
        )

    def motto(self) -> str:
        return "Ship systems that work on real hardware, not benchmark rigs."

me = AathithyaArasu()

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⚙️ Tech Stack

Languages

ML / DL / CV

RAG / LLM

Cloud & DevOps

Databases & Retrieval

Tools

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📊 GitHub Stats

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🔥 Streak

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📈 Activity Graph

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🏆 Trophies

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💼 Work Experience

Ozis Technology — Software Engineering Intern  |  Feb 2026 – Mar 2026  |  Madurai, India

Python RAG Graph RAG LangChain Vector Retrieval FastAPI

• Designed and deployed an end-to-end RAG pipeline adopted by the internal team for production document retrieval within the internship window.
• Benchmarked Naive RAG vs. Graph RAG across document sets, evaluating retrieval accuracy, latency, and scalability under real load conditions.
• Delivered structured performance comparisons that directly informed the team's architecture decision for their document Q&A product.

INFINEX Corporation Private Limited — Machine Learning Intern  |  Dec 2025 – Jan 2026  |  Chennai, India

Python NLTK Scikit-learn Topic Modeling Sentiment Analysis LLM

• Built NLP pipelines for sentiment analysis and topic modeling on 10,000+ research documents, improving classification efficiency by 25%.
• Developed "NLP-based Sentiment Analysis and Topic Modeling for Research Integrity" — a full pipeline combining NLTK, Scikit-learn, and LLM-assisted extraction.
• Automated insight extraction from unstructured data, reducing manual analysis effort across large-scale document corpora.

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🚀 Featured Projects

Project	Stack	Highlights
Multimodal RAG System V2	FastAPI · Qdrant · BGE · CLIP ViT-B/32 · BM25 · llama.cpp · Docker	4-stage hybrid retrieval (Vector + BM25 → RRF k=60 → reranker @ 0.15); 4-signal confidence scoring (45/25/15/15%); Qwen2.5-1.5B Q4_K_M running at ~2.5 GB on 4 GB VRAM
Multimodal Document Tampering Detection ⭐ 29	EfficientNetB7 · ELA · Grad-CAM · EasyOCR · MC Dropout · AWS SageMaker	6-signal cross-modal fusion: Grad-CAM (0.25) + Visual-OCR IoU (0.30) + OCR-visual conflict (0.15) + OCR confidence penalty (0.10) + MC Dropout uncertainty (0.10) + spatial density agreement (0.10) → tiered LOW/MEDIUM/HIGH risk; deployed on SageMaker real-time inference API
Confusion Matrix Debugger	Python · Streamlit · LangChain · FAISS · Groq API	LangChain + FAISS RAG backend for contextual error explanations; automated class-imbalance and mislabeling detection reducing manual evaluation overhead

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🏅 Achievements

	Achievement	Details
🥇	Cognizant Technoverse Hackathon 2026 — Finalist	National-level CTS hackathon; Personalised Banking theme; built Mu AI Finance Agent (bank statement ingestion, transaction categorisation, GST compliance, what-if simulation, Ollama Qwen AI chat)
🥈	Makethon 3.0 — Finalist	Feb 2026
🎓	SIH 2026 — Top 50 College Team	Confirmed slot representing St. Joseph's College of Engineering
🏅	Python for Data Science — Silver Medal (Top 5%)	NPTEL / IIT Madras · Jul–Aug 2025
☁️	OCI 2025 Generative AI Professional	Oracle University · Jul 2025
📜	Introduction to NLP	Infosys Springboard · May 2025
📜	AI Fundamentals	IBM SkillsBuild · Feb 2025

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🎓 Education

Degree	Institution	Expected	Score
B.Tech — Information Technology	St. Joseph's College of Engineering, Chennai (Anna University)	May 2027	8.20 / 10 CGPA

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📚 Currently Learning

🧩 Advanced RAG        →  Graph RAG · HyDE · RAPTOR · Agentic RAG loops
🔧 LLM Deployment      →  GGUF quantisation · llama.cpp optimisation · speculative decoding
🤖 Agentic Systems     →  Tool-use · Multi-agent orchestration · ReAct / LATS patterns
☕ Java DSA            →  OOP deep-dive · Collections · Interview-pattern problem sets
🧠 CV Architectures    →  ConvNeXt · SAM · DINO · zero-shot classification

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