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sahilaf/README.md

>_ 🧠 RESEARCH_FOCUS.exe

Working at the intersection of Machine Learning, AI Systems, and Applied Research — building models and systems that generalize to real-world constraints.

Module Status
🤖 Machine Learning & Deep Learning [ACTIVE]
🧠 Computer Vision & Natural Language Processing [ACTIVE]
🔗 Scalable Training, Fine-Tuning & Optimization [ACTIVE]
📊 Structured Reasoning & Representation Learning [ACTIVE]
⚛️ Quantum Machine Learning & Noise Modeling [ACTIVE]

>_ 📌 IDENTITY_PROFILE.log

$ whoami
  • 🎓 Computer Science Engineering student
  • 🧪 Published researcher in Quantum Machine Learning / Noise Modeling (NISQ systems)
  • 🏗️ Build full-stack AI systems combining LLMs + retrieval + structured reasoning
  • 🧠 Strong foundation in algorithms and competitive programming
  • 📚 Interested in bridging AI research ↔ production systems

>_ 🧰 TECHNICAL_STACK.sh

$ cat /etc/tech-stack.conf

# Programming

Python C++ C Java Go TypeScript JavaScript

# AI / ML

PyTorch TensorFlow Deep Learning Computer Vision NLP Transformers LangChain RAG Systems Vector Databases Model Fine-tuning Feature Engineering

# Research Areas

Quantum ML Noise Modeling Transfer Learning Scientific Computing

# Systems

REST APIs Node.js MongoDB React.js

# Tools

Git Linux Jupyter Google Colab Docker


>_ 📊 ANALYTICS_FEED --live

 


>_ 🔗 COMMS_INTERFACE.init


>_ 🎯 PRIMARY_DIRECTIVE.conf

Building scalable, research-driven AI systems that connect:

[ theoretical machine learning ] ──⟶ [ practical intelligent systems ] ──⟶ [ real-world deployment ]

/* The goal is not to build models, but to build systems that think, retrieve, and reason. */

Status Node Kernel

Pinned Loading

  1. Few-Shot-Cross-Device-Transfer-for-Quantum-Noise-Modeling-on-Real-Hardware Few-Shot-Cross-Device-Transfer-for-Quantum-Noise-Modeling-on-Real-Hardware Public

    A machine learning approach for transferring quantum noise models across different hardware using minimal data, enabling efficient and scalable noise characterization on real quantum devices.

    Jupyter Notebook 2 1

  2. Real-Time-Conversational-AI-Avatar Real-Time-Conversational-AI-Avatar Public

    Talk to AI like it’s human. This project builds a real-time conversational avatar system with synchronized speech and lip movement. By combining Gemini 2.5 Flash, LiveKit, and SyncTalk_2D, it creat…

    Python 1

  3. FactEval FactEval Public

    Find exactly which parts of your LLM output are hallucinated. Claim-level factuality verification with NLI, calibrated confidence, and pipeline diagnostics for RAG systems.

    Python 4

  4. Learnathon-By-Geeky-Solutions/bugsquashers Learnathon-By-Geeky-Solutions/bugsquashers Public

    FairBasket – AI-Driven Grocery Marketplace for Transparent Supply Chains FairBasket is a scalable, open-source e-commerce platform focused on optimizing the grocery supply chain. It integrates AI-d…

    JavaScript 2 3

  5. HealthyEats2.0 HealthyEats2.0 Public

    An open-source AI-powered mobile app designed to combat chronic diseases (e.g., diabetes, heart conditions) by offering personalized, budget-friendly health/nutrition plans. Integrates medical hist…

    TypeScript

  6. Bangla-Voice-Assistant Bangla-Voice-Assistant Public

    This is a Python-based voice assistant that speaks and understands Bangla using LiveKit, Gemini, Whisper and Edge_tts

    Jupyter Notebook 2 1