ELENA VANCE

I'm a quantum computing researcher who grew up in London, now living in Cambridge. I realize notable ideas across compilation, neural networks, and hardware co-design — I care just as much about absolute mathematical rigor as I do about practical hardware execution. I'm a detail freak: always refining compilers, always delivering sub-nanosecond speedups.

2024 — Present

Lead Researcher & Lab Director

MIT Quantum Informatics Lab

Directing a team of 8 PhD candidates studying error correction pipelines, compiler optimizations, and neural integrations on superconducting quantum arrays. Responsible for grant acquisition, publication strategy, and lab infrastructure.

Team Leadership Grant Writing Quantum Hardware
2021 — 2024

Postdoctoral Research Fellow

National Science Foundation Lab

Developed compiler algorithms for noise mitigation and mapped hybrid AI algorithms onto topological quantum computer simulations. Published 12 peer-reviewed papers during tenure.

Compiler Algorithms Noise Mitigation Topological QC
2019 — 2021

Research Assistant

Cambridge University — Quantum Group

Assisted lead researchers in benchmarking decoherence rates on superconducting circuit arrays. Co-authored 4 conference papers presented at IEEE QCE and APS March Meeting.

Benchmarking Co-author Conference Papers
2017 — 2021

Ph.D. in Physics & Computing

Cambridge University

Dissertation: "Decoherence Mitigation in High-Friction Superconducting Circuit Arrays." Recipient of the Outstanding Dissertation Award and the Cavendish Laboratory Prize.

2013 — 2017

B.Sc. in Theoretical Physics (First Class Honours)

Imperial College London

Final-year thesis on variational quantum eigensolvers for molecular simulation. Dean's List all four years.

2025

IBM Quantum Developer Certification

IBM • Qiskit Advanced

2024

NSF CAREER Award

National Science Foundation

2023

Google Quantum AI Research Grant

Google Research

2021

Outstanding Dissertation Award

Cambridge University

2020

Best Paper — IEEE QCE

IEEE Quantum Computing & Engineering

2019

TensorFlow Developer Certificate

Google • Deep Learning Specialization

01

Sub-nanosecond Instruction Compilers for Superconducting Qubits

Nature Quantum Engineering • 2026

A novel compilation framework leveraging predictive scheduling to align gate instructions, reducing decoherence rates by 22% on noisy intermediate-scale quantum hardware.

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02

Hybrid QNN-Classical Neural Architectures for Large-scale OCR Parsing

IEEE Transactions on Pattern Analysis • 2025

Combining Quantum Neural Networks with convolutional layers to enhance features in highly distorted handwritten records, yielding 3.4x speedups in pattern classification.

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03

Predictive Error Mitigation in High-Friction Data Workflows

NeurIPS Conference • 2024

Structuring error-correcting predictive layers within deep neural networks to correct laboratory telemetry, lowering dataset noise without losing system fidelity.

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04

QASM-X: Open-source Quantum Assembly Compiler Toolkit

GitHub • Ongoing • 2,400+ Stars

An open-source toolkit for translating high-level quantum circuit descriptions into optimized, hardware-native pulse sequences for IBM and Google quantum processors.

Dr. Elena Vance is open to research partnerships, peer reviews, consulting, and post-graduate mentorship.

OFFICE Bldg 42, Quantum Informatics Wing, MIT
HOURS Tue / Thu, 14:00 — 16:00 EST
CITATION COPIED!