The Second IEEE Workshop on
Quantum IntelLigence, Learning and Security (QuILLS 2025)
The Second IEEE Workshop on
Quantum IntelLigence, Learning and Security (QuILLS 2025)
Quantum computing hardware has continued to progress rapidly since last year’s workshop, moving beyond the noisy intermediate-scale quantum (NISQ) era toward early demonstrations of fault tolerance. Late 2024 saw Google unveil its Willow processor, a 105‑qubit superconducting device achieving below-threshold error correction, where logical error rates drop exponentially as more qubits are added, and maintaining logical qubit stability for more durations. These advances, along with mid‑2025 demonstrations of magic-state distillation using neutral-atom arrays, are marking a transition toward practical, scalable fault-tolerant quantum computation (FTQC). Algorithms that rely on such hardware, from Shor’s factoring to large-scale Grover search and quantum machine learning (QML) applications, are becoming increasingly relevant as the first logical circuits are deployed. QML continues to serve as a bridge between the NISQ and FTQC eras, with use cases expanding from molecular design and materials discovery to financial optimization and real-time anomaly detection.
The rapid approach of fault tolerance also brings sharper focus to quantum security and cryptanalysis. With Shor-capable hardware on the horizon, public key cryptography such as RSA and elliptic curve cryptography faces mounting risk, accelerating global moves toward post-quantum cryptography (PQC). Beyond cryptography, the security of quantum devices themselves is a growing concern, as tomography-based attacks, QML model theft, and denial-of-service vulnerabilities become more relevant with powerful FTQC-capable systems.
It remains likely that quantum computers will, for the foreseeable future, be accessed remotely, but recent progress in quantum networking—such as entanglement distribution, teleported logic gates across fiber, and modular architectures—suggests a near future where quantum networks link powerful cloud-based quantum servers with smaller-scale client systems. These networks will enable distributed quantum computation and QML, but also amplify challenges of trust, privacy, and security, including the protection of proprietary algorithms and quantum data for clients and defenses against hardware-level and network-based attacks for providers. Software- and hardware-level countermeasures, from blind quantum computation and entanglement distillation to quantum network coding and restrictions on pulse-level access, are becoming essential. This workshop will build on last year’s foundation to discuss these developments, focusing on how emerging fault-tolerant hardware, novel PQCs, cryptanalysis, and quantum networking will define the secure and scalable quantum ecosystem of 2025 and beyond.
We invite submissions of previously unpublished works broadly in the areas of quantum computing, quantum machine learning, quantum networks, cybersecurity, and their interplay. Topics of interest include but are not limited to the following:
Quantum computation
Blind quantum computation
Distributed quantum computing architectures
Quantum algorithms
Quantum communication complexity
Error correction and mitigation algorithms
NISQ and fault-tolerant applications
QML algorithms
QML applications
Quantum optimization (e.g., QAOA)
QML model security
Quantum data security
Quantum repeaters, switches, routers
Quantum data center architectures
Secure quantum networking
Quantum network coding
Quantum Key Distribution
Post-quantum cryptography
Deadline: September 07, 2025 (updated: September 21, 2025).
Notification of decision: October 02, 2025
Final version due: October 14, 2025
General Chair: Rob Cunningham, University of Pittsburgh
Co-Chair: Junyu Liu, University of Pittsburgh
Co-Chair: Kaushik P. Seshadreesan, University of Pittsburgh
Bruno Ricardi de Abreu, Pittsburgh Supercomputing Center
Kishor Bharti, A*STAR Singapore
Kaifeng Bu, Ohio State University
Tianlong Chen, University of North Carolina, Chapel Hill
Alessandro Cilardo, University of Naples Federico II, Italy
Raquel Coelho, University of Pittsburgh
Chaohan Cui, University of Maryland
Shengwang Du, University of Pittsburgh
Swaroop Ghosh, Pennsylvania State University
Edoardo Giusto, University of Naples Federico II, Italy
Yue Joyce Jiang, University of Pittsburgh
Soummya Kar, Carnegie Mellon University
Eneet Kaur, Cisco
Mohammad Mohammadisiahroudi, University of Maryland, Baltimore County
Jamie Sikora, Virginia Tech
Kate Smith, Northwestern
Xulong Tang, University of Pittsburgh
Tamás Terlaky, Lehigh University
Jun Yang, University of Pittsburgh
Xiu Yang, Lehigh University
Zheshen Zhang, University of Michigan
Youtao Zhang, University of Pittsburgh
Ting Zhu, Ohio State University