Quantum Algorithm
Design Automation

at Toronto, Ontario, Canada

IEEE International Conference on Quantum Computing and Engineering

- Workshop Focus -

As bigger quantum processors with hundreds of qubits become increasingly available, the potential for quantum computing to solve problems intractable for classical computers is becoming more tangible. However, designing efficient quantum algorithms is key to achieving quantum advantage. Quantum algorithm design is challenging due to the unique nature of quantum computing. Traditionally, quantum programming has been done using quantum assembly language and qubit-level reasoning. However, as quantum computing continues to evolve, programming is going beyond these limits, requiring new tools and approaches to enable efficient algorithm design. The complexity of quantum algorithms is increasing, and the need for automation in quantum algorithm design, programming, and compilation is becoming more apparent. Quantum algorithm design requires understanding the underlying quantum hardware and the problem being solved. Researchers are actively exploring existing and new approaches to algorithm design that can leverage the unique capabilities of quantum computing to solve problems more efficiently. Automating these processes can help to speed up the development of quantum algorithms, reduce errors, and improve the efficiency of quantum computing. This workshop will explore emerging trends toward the automation of quantum algorithm design, programming, and compilation.

- Objectives -

The Quantum Algorithm Design Automation workshop aims to consolidate the current state and research directions with the following goals:

Understand that QC algorithm design principles and programming will change in the near future
Identify emerging trends and opportunities in automation techniques for quantum algorithm design
Know about these directions, the state-of-the-art (theory, tools, researchers), pros, and cons
Establish roadmaps for future research and development in quantum algorithm design automation

The focus will range across automation techniques based on evolutionary computation, reinforcement learning, variational optimization, geometric machine learning, logic synthesis, diagrammatic reasoning, generative AI, and agentic AI.

The workshop will end with a call to action for establishing collaborations.

- Important dates -

Paper submission deadline: <tbd>
Notification of reviews (3 referees): <tbd>
Camera-ready paper: <tbd>

Call-for-Papers details:

Length of workshop papers is 2-6 pages.
Workshop papers will be included in the QCE26 proceedings in Volume 2.
Submission guideline: https://qce.quantum.ieee.org/2026/call-for-technical-papers/
Submit via EasyChair (Author > New Submission > <tbd>-WKS-PAP)

- Format -

The one-day workshop (4.5 hours) will cover three themes over three sessions (90 minutes each). Each session will be a mix of invited talks and presentations of accepted papers.

The first two themes will cover specific QADA techniques based on (i) soft computing and (ii) information theory. The aim is to provide a research overview of diverse QADA techniques for all the participants. In this series of talks, the speakers will focus on presenting:

What the specific technique is about
How it relates to the goal of the workshop
How much domain knowledge must be embedded for the automation technique (NISQ-focused or scalable to FTQC, etc.)
State of the art, or results from the speaker's research
How it relates to other techniques in the workshop

The third theme is how the UI/UX of quantum computers will evolve in the near future.

Theme 1

Soft-computing based QADA

Focus on heuristic and learning-based QADA approaches that are influenced by soft computing. E.g., evolutionary computation, reinforcement learning, architecture search, variational optimization of parametric circuits.

Theme 2

Quantum information based QADA

Focus on QADA approaches that are influenced by quantum information theory. E.g., information geometry, data symmetry groups, inductive logic synthesis, neuro-symbolic AI, diagrammatic reasoning, process calculi, theorem proving.

Theme 3

UI/UX of Quantum Computers

Focus on how the UI/UX of quantum computers might evolve in the near future. E.g., generative AI, agentic AI, high-level programming, domain-specific libraries, IDE, cloud infrastructures, QML ops, gamification.

The goal of this event is to bring leading researchers in quantum algorithm design automationtogether from across the globe and spark interesting conversations.

Register for the event

The Quantum Algorithm Design Automation (QADA) workshop is part of
the 2026 IEEE International Conference on Quantum Computing and Engineering (QCE26).
You can register on the QCE26 page.

Supporters

We are pleased to announce that we have garnered the support of the following organizations and research groups. They acknowledge that Quantum Algorithm Design Automation is of focal importance in current quantum computing research.

We aim to build a collaborative community around this topic.