The NSF SpectrumX Data & Algorithm Competition (SpX-DAC) aims to inspire students to turn raw spectrum data into intelligent detection and decision-making tools that can shape the future of spectrum sharing.
In this competition, students will detect the existence of active user transmissions of 5G-like signals in the lower 7Ghz band, utilizing measurement data collected during NSF SpectrumX’s July 2025 VLA experiment. This data, taken from three transmit locations and 5 receive locations (both stationary and mobile), will be in the Digital RF format with labeled segments.
This competition allows students to work on real spectrum field data, advance 6G sensing and coexistence, boost their research profile, and gain visibility within the SpectrumX Center.
Students will compete in teams, with a maximum of three students per team, with one student acting as team leader and point of contact.
The registration for the SpX-DAC is currently closed.
Eligibility Requirements
Full-time undergraduate and graduate students from all US-based institutions. Each team may have up to three students, who may be enrolled in the same or different US institution(s). No faculty or other advisors are allowed.
Competition Flow
- Team registration – December 15, 2025
- Background materials on data format will be provided
- Data release – December 19, 2025
- Teams will receive a labeled dataset with known incumbent user activity
- Algorithm submission and evaluation – February 27, 2026
- Teams will submit their implemented algorithms, including low-level design documents
- Algorithms will be tested against several unreleased datasets to assess their performance
- Submissions will be scored based on the specified evaluation metrics
- Results and recognition – Spring 2026 SpectrumX Center Meeting (June 1-2 2026)
Evaluation Metrics
Groups will be evaluated based on four criteria. The first two criteria are objective and will be scored accordingly. The last two will be scored by an evaluation committee.
- Detection accuracy
- Implementation efficiency
- Algorithmic novelty
- Visualization quality
Prizes
Prizes will be awarded for Winner, Runner-Up and Honorable mention for two categories: Overall Performance and Innovation.
2026 Reviewers
We’d like to extend a special thank you to the reviewers of this year’s SpX-DAC:
- Ali Abedi, Assistant Professor, University of Wisconsin – Madison
- Karyn Doke, Assistant Professor, Hamilton College
- Clark Mattoon, Ph.D. student, University at Albany
- Omkar Mujumdar, Ph.D. student, University of Notre Dame
- Andrew Okoro, Ph.D. student, University at Albany
- Cong Shen, Associate Professor, University of Virginia
- Vaasu Taneja, Ph.D. student, University at Albany
- Sarah Tanveer, Ph.D. student, University of Wisconsin – Madison
- Mariya Zheleva, Associate Professor, University at Albany
Contact
If you have any questions on the SpX-DAC, please contact prof. Cong Shen at cong@virginia.edu.
About SpectrumX
SpectrumX, the U.S. National Science Foundation (NSF) Spectrum Innovation Center, is the world’s largest academic hub where all radio spectrum stakeholders can innovate, collaborate, and contribute to maximizing social welfare of this precious resource. SpectrumX aims to provide national-level coordination of world-class interdisciplinary researchers, policy experts, and educators from academia working to solve spectrum coexistence and workforce challenges in collaboration with industry and government.
