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Worldisbinary/README.md

Hi, I'm Aman Arora 👋

B.E. Chemical Engineering + M.Sc. Biological Sciences | BITS Pilani (2022–2027)

About Me

I'm a dual-degree student at BITS Pilani with a strong interest in quantitative methods, machine learning, and computational problem-solving. I bridge engineering fundamentals with data-driven approaches — from healthcare analytics to quantum algorithms to electrochemical systems.

  • 🏆 SOLVE Research Grant (INR 2L) — SIRE, BITS Pilani
  • 🏆 2nd Prize — AIChE Student Regional Conference (Al-air battery)
  • 🎙️ Selected Presenter — 3rd Cell Free Systems Conference, Northwestern University, USA
  • ⚽ Bronze Medal — BITS Open Sports Meet (BOSM) 2024

What I Build

Project Description Stack
quantum-computing-qiskit QAOA, VQE, Grover's search, noise modelling, Ramsey sensing Qiskit, Python, SciPy
medical-image-classifier End-to-end image classification with prediction API Scikit-learn, NumPy
symptom-nlp-classifier Medical symptom text classification using TF-IDF Scikit-learn, Python
ayurnidaan-healthcare-analytics Patient clustering, feature selection, screening model (AUC 0.98) Pandas, Scikit-learn
biosensor-signal-processing Signal extraction and noise reduction for PEDOT:PSS cortisol sensor SciPy, FFT, Python

Experience

Healthcare Analytics Intern — Ayurnidaan, BITS Pilani Incubated Startup (Mar–Jun 2025)

Analysed 500+ patient records, extracted 8+ predictive clinical variables, built analytics dashboards

Operations Intern — Bid Alert, Tender Intelligence (May–Jul 2024)

Built Python-Excel procurement pipeline, reduced manual effort by 70%, secured 2 government contracts

Tech Stack

Python C++ Qiskit NumPy Pandas Scikit-learn MATLAB

Currently Learning

  • Quantum variational algorithms (QAOA, VQE) and quantum sensing
  • Interest rate modelling and derivatives pricing
  • Deep learning fundamentals

Connect

LinkedIn Email

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  1. ayurnidaan-healthcare-analytics ayurnidaan-healthcare-analytics Public

    Healthcare ML pipeline from internship at Ayurnidaan (BITS Pilani incubated startup). EDA, KMeans symptom clustering, feature importance, and screening model with AUC 0.98.

    Python

  2. biosensor-signal-processing biosensor-signal-processing Public

    Digital signal processing for PEDOT:PSS wearable cortisol biosensor. Bandpass + notch filtering, FFT noise analysis, and SNR optimisation from 12dB to 28dB.

    Python

  3. medical-image-classifier medical-image-classifier Public

    End-to-end medical image classification pipeline with feature extraction, model comparison (RF, GBM, SVM), and prediction API. Modular design for swapping in CNN backbones.

    Python

  4. Metal-air-batteries Metal-air-batteries Public

    Optimization and production of metal air battery using agarose gel based techniques

  5. quantum-computing-qiskit quantum-computing-qiskit Public

    QAOA, VQE, Grover's search, quantum noise modelling, and Ramsey interferometry implemented in Qiskit. Covers variational algorithms, T1/T2 decoherence, and quantum sensing SNR analysis.

    Python

  6. symptom-nlp-classifier symptom-nlp-classifier Public

    NLP pipeline for classifying medical symptom descriptions using TF-IDF bigrams and scikit-learn classifiers. Achieves 98% accuracy with a callable prediction API.

    Python