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Nick Alonso

I’m a researcher studying machine learning and computational neuroscience. I currently work at Zyphra, a startup in the bay area, and recently graduated from UC, Irvine with a PhD in cognitive science. For more information see my CV, about page, or github.

Email: nalonso2@uci.edu
LinkedIn
CV

News

12/20 New Paper! ‘Mixture-of-PageRanks: Replacing Long-Context with Real-Time, Sparse GraphRAG’
10/22 New technical blog post ‘Reaching 1B Context with RAG‘

Papers

Figliolia, T., Alonso, N., Iyer, R., Anthony, Q., & Millidge, B. (2025). Compressed Convolutional Attention: Efficient Attention in a Compressed Latent Space. arXiv preprint arXiv:2510.04476. (Technical Report)

Alonso, N., & Millidge, B. (2024). Mixture-of-PageRanks: Replacing Long-Context with Real-Time, Sparse GraphRAG. arXiv preprint arXiv:2412.06078. (Under Review)

Alonso, N., Figliolia, T., Ndirango, A., & Millidge, B. (2024). Toward Conversational Agents with Context and Time Sensitive Long-term Memory. arXiv preprint arXiv:2406.00057.

Alonso, N., & Krichmar, J. (2024). A Sparse Quantized Hopfield Network for Online-Continual Memory. Nature Communications.

Alonso, N., Krichmar, J., & Neftci, E. (2024). Understanding and Improving Optimization in Predictive Coding Networks. Proceedings of the AAAI conference on artificial intelligence (Selected for oral presentation)

Alonso, N., Millidge, B., Krichmar, J., & Neftci, E. O. (2022). A Theoretical Framework for Inference Learning. Advances in Neural Information Processing Systems, 35, 37335-37348.

Wang, F., Alonso, N., & Teeter, C. (2022). Combining Spike Time Dependent Plasticity (STDP) and Backpropagation (BP) for Robust and Data Efficient Spiking Neural Networks (SNN) (No. SAND2022-16962). Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Alonso, N., & Neftci, E. (2021). Tightening the Biological Constraints on Gradient-Based Predictive Coding. In International Conference on Neuromorphic Systems 2021 (pp. 1-9).