Turning Quantum Weirdness into Everyday Superpowers

If the universe insists on being strange, let’s at least make it useful.” — me, after my third espresso and fifth qubit reset.

About Me

The world of quantum mechanics is often depicted as a bizarre and counterintuitive place. Particles existing in multiple states simultaneously, spooky action at a distance – it all sounds like science fiction. But here’s the thing: quantum mechanics isn’t some fringe theory. It’s the undeniably successful framework that underpins the behavior of the universe at its most fundamental level.

My passion lies in demystifying this “weirdness” and translating it into powerful, real-world applications. I believe that by embracing concepts like superposition, wave-particle duality, and entanglement, we can unlock a new era of technological innovation. My work focuses on the intersection of quantum computing and artificial intelligence, exploring how quantum algorithms can solve problems currently intractable for even the most powerful classical supercomputers.

This profile is a window into my journey. Here you’ll find projects ranging from quantum machine learning models to simulations of novel quantum materials. Join me as we explore the strangeness that shapes our universe and turn it into a superpower.

Skills

  • Quantum Computing: Quantum Algorithms (Shor’s, Grover’s), Quantum Machine Learning, Quantum Error Correction, Quantum Information Theory, Entanglement & Superposition Principles.
  • AI & Machine Learning: Deep Learning, Neural Networks, Reinforcement Learning, Natural Language Processing (NLP), Computer Vision.
  • Programming & Software: Python, C++, Qiskit, PennyLane, Cirq, TensorFlow, PyTorch, Scikit-learn.
  • Mathematics: Linear Algebra, Probability & Statistics, Complex Analysis, Differential Equations.

“If you think you understand quantum mechanics, you don’t understand quantum mechanics.” - Richard Feynman

“The universe is not only stranger than we imagine, it is stranger than we can imagine.” - J.B.S. Haldane

Let’s Connect

Tech Stack

CategoryTechnologies
Quantum FrameworksQiskit PennyLane Cirq D-Wave Ocean Microsoft QDK
AI/ML LibrariesTensorFlow PyTorch Keras Scikit-learn Hugging Face Transformers NLTK
Programming LanguagesPython C++ MATLAB
Cloud & PlatformsIBM Quantum AWS Braket Google Cloud Azure Quantum Docker
DatabasesSQL MongoDB
ToolsGit Jupyter Linux LaTeX

Education

  • Massachusetts Institute of Technology (MIT)
    • Ph.D. in Quantum Information Science
    • September 2019 - May 2024
    • Thesis: Developing Noise-Resilient Quantum Machine Learning Algorithms for Near-Term Devices.
  • University of Oxford
    • M.Sc. in Physics and Theoretical Physics
    • October 2017 - September 2018
    • Focus on Quantum Field Theory and Condensed Matter Physics.
  • Stanford University
    • B.S. in Computer Science
    • September 2013 - June 2017
    • Specialization in Artificial Intelligence.

Work Experience

Quantum Research Scientist | IBM Quantum (June 2024 - Present)

  • Developing and implementing novel quantum machine learning algorithms on IBM’s fleet of superconducting quantum processors.
  • Collaborating with industry partners to identify and solve high-impact business problems in finance, materials science, and healthcare using quantum computers.
  • Contributing to the open-source Qiskit framework, with a focus on the qiskit-machine-learning module.

Certificates & Degrees

  1. IBM Certified Associate Developer - Quantum Computation using Qiskit v0.2X - IBM
  2. Professional Certificate in Quantum Computing - MIT xPRO
  3. Quantum Machine Learning - University of Toronto on Coursera
  4. The Quantum Internet and Quantum Computers: How Will They Change the World? - DelftX (TU Delft) on edX
  5. Introduction to Quantum Computing - Qiskit Global Summer School 2023
  6. Quantum Computing for Everyone - University of Chicago on Coursera
  7. The Physics of Silicon - Quantum Computing 2 - Purdue University on edX

Projects

  1. Quantum Variational Classifier for Drug Discovery
    • Developed a hybrid quantum-classical model using a Variational Quantum Eigensolver (VQE) to predict molecular binding affinities. Implemented in Qiskit and PyTorch.
    • Keywords: VQE, QML, Drug Discovery, Chemoinformatics.
  2. Noise-Resistant Entanglement Distribution Protocol
    • Simulated a novel entanglement swapping protocol incorporating error-mitigation techniques. Showcased improved fidelity on noisy simulated quantum hardware.
    • Keywords: Quantum Networking, Entanglement, Error Mitigation, Qiskit Aer.
  3. Quantum Natural Language Processing (QNLP) Model
    • An exploratory project implementing a sentence-meaning model on a quantum circuit, based on the DisCoCat framework, to classify text sentiment.
    • Keywords: QNLP, DisCoCat, PennyLane, Natural Language Processing.
  4. Financial Portfolio Optimization using Quantum Annealing
    • Formulated a Quadratic Unconstrained Binary Optimization (QUBO) problem for portfolio optimization and solved it using D-Wave’s quantum annealer.
    • Keywords: Quantum Annealing, QUBO, Finance, D-Wave Ocean.
  5. Educational Quantum Circuit Simulator in Python
    • Built a lightweight quantum circuit simulator from scratch using NumPy to teach the fundamental principles of quantum gates, superposition, and entanglement.
    • Keywords: Education, Simulator, Quantum Gates, NumPy.

Courses

  1. MIT 8.05x: Quantum Mechanics: A First Course - edX
  2. Stanford CS269Q: Quantum Computer Programming - Stanford University
  3. Caltech Ph/CS 219: Quantum Computation - California Institute of Technology
  4. Qiskit Global Summer School: Quantum Simulations - IBM Quantum
  5. Introduction to Modern Physics - University of Rochester on Coursera