| 2024 | IJCNN | Molecular Classification Using Hyperdimensional Graph Classification. | Pere Vergs, Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau |
| 2023 | DAC | An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing. | Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau |
| 2023 | KDD | DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication. | Igor Nunes, Mike Heddes, Pere Vergs, Danny Abraham, Alexander V. Veidenbaum, Alex Nicolau, Tony Givargis |
| 2023 | RTCSA | Accelerating Permute and N-Gram Operations for Hyperdimensional Learning in Embedded Systems. | Pere Vergs, Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau |
| 2022 | DAC | Hyperdimensional hashing: a robust and efficient dynamic hash table. | Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum |
| 2022 | DATE | GraphHD: Efficient graph classification using hyperdimensional computing. | Igor Nunes, Mike Heddes, Tony Givargis, Alexandru Nicolau, Alexander V. Veidenbaum |