2nd ACM SIGSPATIAL International Workshop on Quantum Computing and Quantum-Inspired Technologies for Spatial Data Systems and Applications
(Q-Spatial 2026)
Co-located with the 34th ACM SIGSPATIAL 2026 in Riverside, California, USA
Tuesday, November 3, 2026
Co-located with
Important Dates
All deadlines are at 11:59 PM (Midnight) Pacific Time. |
Welcome to Q-Spatial 2026The 2nd ACM SIGSPATIAL International Workshop on Quantum Computing and Quantum-Inspired Technologies for Spatial Data Systems and Applications Workshop OverviewQuantum computing and other quantum-driven technologies have been a field of technology investment for decades. With promising potential, significant investments from many governmental and industrial parties are poured into winning the race. The SIGSPATIAL community is building a capacity in that promising technology field. This workshop aims to bring together SIGSPATIAL community members interested in exploring quantum technologies in spatial systems and applications. It will also invite non-SIGSPATIAL members who are experts in the field of quantum technologies to enrich the community and foster learning and collaboration. The workshop will be open to all levels of expertise, allowing participants to contribute or learn. Workshop Mission and GoalsThe high-level philosophy of organizing this workshop is engaging, motivating, encouraging, and helping interested SIGSPATIAL community members to explore spatial problems that could take advantage of quantum computing. This mission breaks down into the following goals:
Workshop Organizers
Program Committee
Workshop ProgramSchedule - Tuesday, November 3, 2026
Keynote TalksKeynote Talk 1 Fundamental Physics and Precision Measurements in SpaceDr. John Callas NASA Jet Propulsion Laboratory, Pasadena, California, USA AbstractEinstein’s General Relativity and the Standard Model of particle physics are the two central pillars of modern physics. Both have been extraordinarily successful, yet they leave several basic questions unresolved. What is the particle nature of dark matter? What drives the accelerated expansion of the universe? Why is the observable universe dominated by matter rather than equal amounts of matter and antimatter? And how can gravity be reconciled with quantum theory? Extensive accelerator, direct-detection, and astronomical searches have placed stringent constraints, but no confirmed dark-sector particle or definitive deviation from known physics has yet been identified. Space-based precision measurement offers a complementary discovery strategy. Instead of producing new particles directly, it tests the principles underlying General Relativity and the Standard Model by searching for extremely small departures from their predicted observables. This presentation describes how quantum-enabled precision measurements in space can test for new physics beyond the reach of traditional high-energy and direct-detection approaches. BiographyDr. John Callas is a physicist at NASA's Jet Propulsion Laboratory in Pasadena, California. He is deputy director of JPL's Quantum Space Innovation Center. Previously, he managed NASA's Mars Exploration Rover Project, the joint NASA-NSF Exoplanet Observational Research program, and NASA's Fundamental Physics Program. He teaches mathematics at Pasadena City College as an adjunct assistant professor. He holds a Ph.D. in Physics from Brown University. Keynote Talk 2 Bridging Quantum Machine Learning and Spatial Systems: Harnessing Quantum Computing for Geographic and Spatial ApplicationsDr. Thilanka Munasinghe Rensselaer Polytechnic Institute (RPI), Troy, New York, USA AbstractQuantum technologies are rapidly advancing, with quantum computing, quantum communication, and quantum optimization set to revolutionize next-generation communication networks and learning systems. As quantum computing evolves from theoretical ideas to hardware prototypes capable of managing hundreds of qubits, recent advancements in industry and academia have enabled promising applications in classification, regression, generative modeling, and reinforcement learning. Quantum Machine Learning (QML) stands as an innovative field at the intersection of Quantum Computing (QC) and Artificial Intelligence (AI). This presentation explores the transition from classical machine learning to quantum-driven spatial systems within the current Noisy Intermediate-Scale Quantum (NISQ) era. We will examine how Variational Quantum Algorithms (VQAs) and Quantum Kernel methods can address high-dimensional environmental data for NISQ devices (e.g., IBM quantum systems) and explore their associated challenges. We will examine data inputs from NASA missions such as the precipitation data from the Global Precipitation Measurement (GPM) mission, Land Surface Temperature (LST), and soil moisture observation data in QML applications, alongside current benchmarking with classical ML models. The talk addresses strategies for managing quantum hardware constraints and implementing QML models for classification and regression tasks related to floods, wildfires, and other domains such as agricultural crop-frosting. Attendees will gain a functional understanding of how to transform classical datasets into quantum states and choose appropriate quantum encoding methods for spatial data analysis. The talk will provide a foundation for understanding how to choose QML models to run on both quantum simulators and real quantum computing hardware for geospatial applications. BiographyDr. Thilanka Munasinghe is a faculty member and Lead Research Specialist at Rensselaer Polytechnic Institute (RPI). He holds a BSc in Aerospace Engineering and an MSc in Mechanical Engineering from West Virginia University, and a PhD in Information Science from the University at Albany, New York. Currently, his research interests focus on developing QML applications that leverage the intersection of Quantum Computing (QC) and Artificial Intelligence (AI), harnessing quantum algorithms. He serves on the organizing committee for international conferences and workshops on Quantum & AI for industry applications and scientific discovery. Accepted Papers
Call for Papers2nd ACM SIGSPATIAL International Workshop on Quantum Computing and Quantum-Inspired Technologies for Spatial Data Systems and Applications (Q-Spatial 2026) Quantum computing and other quantum-driven technologies, such as quantum communication and quantum sensing, have been a focus of investment for decades across diverse scientific and engineering communities, including major professional societies. Recent advances and breakthroughs from academia and industry have direct relevance to spatial applications, such as GPS-free navigation using quantum navigators. Several countries worldwide are investing hundreds of millions of dollars in quantum technologies through public and private partnerships. We strongly believe it is time for the SIGSPATIAL community to build capacity in this promising field of technology. Q-Spatial 2026 brings together members of the research community interested in exploring quantum technologies in spatial systems and applications, whether experts in the field or those seeking to learn about them at different levels of seniority and expertise. The workshop series is designed to benefit all levels of expertise, whether contributing or learning, with sessions tailored to audiences with varying levels of experience in quantum technology. Important DatesAll deadlines are due at Midnight (11:59 PM) Pacific Time.
Topics of InterestWe welcome submissions at the intersection of quantum computing / quantum-inspired technologies and spatial data systems and applications, including (but not limited to):
Submission TypesThe workshop welcomes submissions of different types. All page limits below exclude references and appendices, and submissions should follow the current ACM SIGSPATIAL formatting guidelines. All submissions are peer-reviewed by the program committee. Research PapersCategories: novel research, quantum use cases, quantum experiments, vision papers, and review papers.
Any of the above contribution kinds may be submitted at the length that best fits its maturity: full papers for complete, evaluated work; short papers for focused or preliminary results; and extended abstracts for early-stage ideas, positions, or demonstrations. Educational PapersTutorials, enlightening talks, and lightning talks.
OriginalityA paper submitted to Q-Spatial must present original work not described in any prior publication that is more than 4 double-column ACM-style pages in length. A prior publication is a paper that has been accepted for presentation at a refereed conference or workshop with proceedings; or an article that has been accepted for publication in a refereed journal. If a Q-Spatial submission has overlap with a prior publication, the submission must cite the prior publication, along with all other relevant published work, even if this prior publication is at or below the 4-page length threshold. For 4-page papers to appear at ACM SIGSPATIAL'26 which are not yet published, the authors must enclose a copy of their 4-page paper to their workshop submission to allow reviewers to assess the quality of the material that is not already published. SubmissionAll submissions must be made electronically through EasyChair. Please select the appropriate submission type when submitting. Previous WorkshopsPast editions of the Q-Spatial Workshop:
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