Quantum AI (QAI) at the Quantum Computing Lab

Created: Damir Cavar, 2023-06-12

Last change: Damir Cavar, 2026-08-23

The Quantum AI Lab is located at Indiana University at Bloomington. While it is mainly a local group of students and researchers with a strong interest in Quantum Computing and [AI] here in Indiana, it maintains connections with colleagues across the country.

The Quantum AI Lab meetings during the Fall Semester of 2026 are held in Luddy Hall BL IF 0002 every Thursday from 5:30 to 7:00 PM.

Please contact Damir Cavar if you are interested in joining the Quantum AI Lab or the AI & NLP Lab meetings.

See the public calendar with all the meeting times and details: AI & NLP Lab and Quantum AI Lab Event Calendar. More information on the AI & NLP Lab on its website.

Schedule

The topics to discuss, papers to read, or presentations to listen to during Fall of 2026:

Date	Topic
08/27/2026	Classical and Quantum Embeddings - CBIRD Project - Model Training
	Training AI models for molecular structure generation and Quantum Circuit for ground-state optimization
09/03/2026	Classical and Quantum Embeddings - CBIRD Project - Model Training
	Training AI models for molecular structure generation and Quantum Circuit for ground-state optimization
…

Previous Meeting Schedules

Content

Publications, Talks, and Software generated by this lab

News

Damir Cavar (2026) presenting Complex Bidirectional Integration for Representation Dynamics (CBIRD), a hybrid classical-quantum AI model trained on classical computers for inferencing on quantum computers, talk at the Physics Colloquium at Indiana University Bloomington, 4-5 PM, Swain Hall, 2nd of December, 2026.
Cavar, D., Daniel Quigley, Sam Gray Miller (2026) Quantum Computing with AI Embeddings and Training of Hybrid Classical/Quantum AI Models (MLMs and LLMs). Tutorial at the 2026 IEEE 2nd International Conference on Quantum Artificial Intelligence (QAI) in Nottingham, UK.
Cavar, D., Peter Sullivan, Shane Sparks, Sam Gray Miller, Ronit Jha, Ayomide Jeje, Yanin Charoenpomsawat (2026) Training Language Models and Embeddings for Hybrid Classical/Quantum Computing. Poster presented at the Midwest Speech and Language Days at the University of Illinois in Urbana-Champaign.
Cavar, D., Shane Sparks, Soren DeHaan, Ronit Jha, Ayomide Jeje, Yanin Charoenpomsawat, Sam Gray Miller (2026) Hybrid Classical-Quantum Language and World Models for AI - CBIRD, Poster presentation at the Center for Quantum Technologies (CQT) Meeting 2026 at Notre Dame, 1st of April, 2026.
Cavar, D. “From Vectors to Qubits: Rethinking AI Models for the Hybrid Classical–Quantum Era,” invited keynote lecture, September 16-18, 2026 at the 37th Central European Conference on Information and Intelligent Systems (CECIIS 2026), Varaždin, Croatia.
Cavar, D. “Hybrid Classical/Quantum Data Structures And Experiments For New AI Architectures,” March 25, 2026, Research Technologies Speaker Series, Cyberinfrastructure Building, Indiana University.
Quantum AI Conference 2026 (website currently being updated) will be August 14th–16th on the IUI campus in Indianapolis! Stay tuned for updates!
The Complex Bidirectional Inducer for Representation Dynamics (CBIRD) is a Language Model trained to be a fully hybrid classical/quantum model, which can be used on CPU/GPU and QPU systems without encoding loss. It is usable as a state-of-the-art text diffusion model, a BERT-style bidirectional encoder-only model, and more — code and model coming soon.
Old news collection

Events

Join us at the Quantum AI 2026 Conference Preparation this August, 2026!
There was a news article about the Quantum NLP Study Group
Quantum Day 2024, April 14th, 2024, 11 AM - 3 PM, Swain West 007
CQT - Center for Quantum Technologies, NSF Industry/University Cooperative Research Center (IUCRC) Year 2, Phase I, Spring 2024 Industry Advisory Board Meeting, April 3-4, 2024, University of Notre Dame, South Bend, IN

Introduction

The Quantum AI in the AI & NLP Lab is currently a study group focusing on the most recent papers in Quantum AI. Our goal is to familiarize participants with the different tools and environments for QAI and work on interesting questions related to Quantum and AI related computation or cognitive aspects of AI, NLP, and quantum models.

The study group meets independently of the AI & NLP Lab weekly meeting at IU-B. If you want to join this meeting, contact Damir Cavar directly.

See also the recent IU News article for further details.

The Quantum AI/NLP/ML GitHub repo.

At Indiana University:

Most Recent

Cavar, D., James Bryan Graves, Shane Sparks, Koushik Reddy Parukola (2025) Hybrid Classical Quantum Embeddings for NLP and AI using Hamiltonians. IEEE Quantum Week 2025, September 2025, Albuquerque, New Mexico. (poster)
Cavar, D., Billy Dickson, James Bryan Graves, Shane A. Sparks, Koushik Reddy Parukola (2025) The Natural Language Qu Kit - NLQK for Quantum NLP and AI. Unpublished. (poster)
Cavar, D., Koushik Reddy Parukola, James Graves, Shane Sparks (2025) Old Wine in New Bottles: Using Classical Word Embeddings in Gate-Based Quantum NLP Systems. Paper to be presented at the Quantum AI and NLP Conference 2025, Indiana University, August 2025. To appear in proceedings, Fall 2025.
Cavar, D., Koushik Reddy Parukola, Shane Sparks (2025) Old Wine in New Bottles: Using Classical Word Embeddings in Quantum NLP Systems. Paper to be presented at the Midwest Speech and Language Days 2025, University of Notre Dame, April 2025.
Chi Zhang, Akriti Kumari, Damir Cavar (2024) Entangled Meanings: Classification and Ambiguity Resolution in Near–Term QNLP. Paper and Poster presented at the IEEE Quantum Week 2024, Montreal, Canada, September 2024. (paper, poster)
Damir Cavar and Chi Zhang (2024) Semantic Similarities using Classical Embeddings in Quantum NLP. Paper and Poster presented at the IEEE Quantum Week 2024, Montreal, Canada, September 2024. (paper, poster)
AI & NLP-Lab poster (2024) Quantum Natural Language Processing and Machine Learning. Luddy-Crane Summit on March 29, 2024 at Indiana University Bloomington.

Literature

Bibliography

Papers:

Papers we have read include:

Laakkonen, Konstantinos, and Coecke (2024) Quantum Algorithms for Compositional Text Processing.
Zhang et al. (2023) Applications of Quantum Embedding in Computer Vision (focus on Quantum Embeddings)
Schuld et al. (2014) An introduction to quantum machine learning.
Coecke et al. (2010) Mathematical Foundations for a Compositional Distributional Model of Meaning.
Coecke (2019) The Mathematics of Text Structure.
Gogioso (2016) A Corpus-based Toy Model for DisCoCat.
Bradley et al. (2018) Translating and Evolving: Towards a Model of Language Change in DisCoCat.
Kartasaklis et al. (2021) lambeq: An Efficient High-Level Python Library for Quantum NLP.
Widdows et al. (2022) Near-Term Advances in Quantum Natural Language Processing.
Alexander and Widdows (2023) Quantum Text Encoding for Classification Tasks.
Lorenz et al. (2021) QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer.
Meichanetzidis et al. (2020) Grammar-aware sentence classification on quantum computers.
Bob Coecke (2023) Our quest for finding the universality of language
Widdows, Dominic and Stanley Peters (2003) Word Vectors and Quantum Logic Experiments with negation and disjunction.

Books:

John Watrous. Understanding Quantum Information and Computation. arXiv:2507.11536, 2025.
Nielsen, Michael A., and Isaac L. Chuang. Quantum Computation and Quantum Information: 10th Anniversary Edition. Cambridge: Cambridge University Press, 2010.
Luongo, Alessandro (2023) Quantum algorithms for data analysis.
Hughes, Ciaran, et al. (2021) Quantum Computing for the Quantum Curious. Springer. Open Access, free download.
James K. Freericks (2026) Quantum Mechanics Done Right: The Shortest Path from Novice to Researcher. Springer Cham.
Bob Coecke and Stefano Gogioso (2023) Quantum in Pictures: A New Way to Understand the Quantum World, Quantinuum.
Bob Coecke and Aleks Kissinger (2017) Picturing Quantum Processes: A First Course in Quantum Theory and Diagrammatic Reasoning, Cambridge University Press.

Relevant literature from Cognitive Science and Psychology:

Jerome R. Busemeyer and Peter D. Bruza (2012) Quantum Models of Cognition and Decision. Cambridge University Press. (FYI: the second edition is coming out soon and it has a special chapter on Large Language Models!)

Tools and Technologies

Qiskit - Open-Source Quantum Development
Wolfram Quantum Framework - omputation framework for quantum circuits and other finite-dimensional quantum systems, Wolfram Language
lambeq, Python library for experimental Quantum Natural Language Processing (QNLP)
tket, a quantum SDK
- pytket, a quantum computing toolkit and optimizing compiler by Quantinuum
- pytket-extensions, extension modules for pytket

Tutorials

From quantum picturalism to quantum NLP and quantum AI with Bob Coecke
An introduction to Quantum Natural Language Processing, Nov. 2022 by Amin Karamlou, Marcel Pfaffhauser, and James Wootton
- related presentation from the QNLP 2022
PennyLane a software framework for Q ML - by Xanadu
- Xanadu Quantum Codebook

Conferences and Events

The Future of Communications in A Quantum Era at the WestGate Academy, Odon, Indiana, 02/04/2025
Quantum Artificial Intelligence and Natural Language Processing Conference 2025 at Indiana University in August 2025.
Purdue Quantum AI (PQAI), Purdue University, West Lafayette, USA
Quantum Artificial Intelligence & Optimization 2025 workshop at the 17th International Conference on Agents and Artificial Intelligence (ICAART).
Quantum Natural Language Processing (QNLP) 2022, Oxford, UK
Quantum Natural Language Processing (QNLP) 2023, Gothenburg, Sweden
Quantum Physics and Logic (QPL) 2022 (proceedings)
Quantum Physics and Logic (QPL) 2023 (proceedings)
Quantum Physics and Logic (QPL) 2024

Jobs and Internships

QED-C Quantum Jobs Page

Cloud Services for Quantum Computation

Government Links

Other News Sources

Team

Dr. Damir Cavar
Khurrum Ali	MacIntosh Phillips, John
Ronit Jha	Shane A. Sparks
Sam Gray Miller	Dr. Daniel Quigley

Full team and history