Conferences
[C56] H. Errahmouni Barkam, S.Yun, P. R.Genssler, Z. Zou, C.Liu,
H.Amrouch, and Mohsen Imani, “HDGIM: Hyperdimensional Genome Sequence Matching on Unreliable highly scaled FeFET”, DATE, 2023.[pdf]
[C55] Y. Ni, D. Abraham, M. Issa, Y. Kim, P. Mercati,and M. Imani. “Efficient Off-Policy Reinforcement Learning via Brain-Inspired Computing.”, Proceedings of the Great Lakes Symposium on VLSI (GLSVLSI), 2023.[pdf]
[C54] Y. Ni, H. Chen, P. Poduval, P Mercati, and M. Imani. “Incorporating Efficient Uncertainty Estimation into Hyperdimensional Computing.”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2023.[pdf]
[C53] Y. Ni, D. Abraham, M. Issa, Y. Kim, P. Mercati,and M. Imani. “Value-based Reinforcement Learning using Efficient Hyperdimensional Computing.”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2023.[pdf]
[C52] M.Issa, S. Shahhosseini, Y. Ni, T. Hu, D. Abraham, A. Rahmani, N. Dutt, M. Imani, “Hyperdimensional Hybrid Learning on End-Edge-Cloud Networks”, ICCD 2022. [pdf]
[C51] Z.Zou, H. Chen, P. Poduval, Y. Kim, M. Imani, E. Sadredini, R. Cammarota, and M. Imani. “BioHD: an efficient genome sequence search platform using HyperDimensional memorization.” In Proceedings of the 49th Annual International Symposium on Computer Architecture (ISCA), 2022. [pdf]
[C50] Y. Ni, N. Lesica, F.G. Zeng and M. Imani, “Neurally-Inspired Hyperdimensional Classification for Efficient and Robust Biosignal Processing.”, IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2022. [pdf]
[C49] H. Chen, M. A. Issa, Y. Ni and M. Imani,”Distributed Reconfigurable Accelerator for Hyperdimensional Reinforcement Learning.”, IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2022.
[C48] S. Zhang, M. Imani, X. Jiao, “ScaleHD: Robust Brain-Inspired Hyperdimensional Computing via Adapative Scaling.”, IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2022.
[C47] C. Liu, H. Chen, M. Imani, K. Ni, A. Kazemi, A. F. Laguna, M. Niemier, X. S. Hu, L. Zhao, C. Zhuo and X. Yin, “COSIME: FeFET based Associative Memory for In-Memory Cosine Similarity Search.”, IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2022.
[C46] Y. Ni, M. Issa, D. Abraham, M. Imani, X. Yin, and M. Imani. “HDPG: Hyperdimensional Policy-based Reinforcement Learning for Continuous Control.”, IEEE/ACM Design Automation Conference (DAC), 2022.[pdf]
[C45] M. Imani, A. Zakeri, H. Chen, T. Kim, H. Lee, Y. Kim, E. Sadredini, F. Imani. “Neural Computation for Robust and Homographic Face Detection.”, IEEE/ACM Design Automation Conference (DAC), 2022.[pdf]
[C44] P. Poduval, Y. Ni, Y. Kim, K. Ni, R. Kuma, R. Cammarota, M. Imani. “Adaptive neural recovery for highly robust brain-inspired representation.”, IEEE/ACM Design Automation Conference (DAC), 2022.[pdf]
[C43] J. Cai, M. Imani, K. Ni, G. Zhang, X. Zhuo, X. Yin. “Energy Efficient Data Search Design and Optimization Based on a Compact Ferroelectric FET Content Addressable Memory.”, IEEE/ACM Design Automation Conference (DAC), 2022.[pdf]
[C42] A. Jalilvand, S. Naderi, S. N. Estiri, H. Najafi, M. Imani “A Fast and Low-Cost Comparison-Free Sorting Engine with Unary Computing.”, IEEE/ACM Design Automation Conference (DAC), 2022.[pdf]
[C41] Y. Ni, Y. Kim, T. Rosing, M. Imani, “Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2022 (Best paper award).[PDF]
[C40] Y. Ni, Y. Kim, T. Rosing, M. Imani, “Online Performance and Power Prediction for Edge TPU via Comprehensive Characterization ”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2022 .[PDF]
[C39] P Poduval, M Issa, F Imani, C Zhuo, X Yin, H Najafi, M Imani, “Robust In-Memory Computing with Hyperdimensional Stochastic Representation”, IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH), 2021. (invited paper)[PDF]
[C38] Z. Zhao, J. Gomez, H. Ye, M. Imani, X. Yin, S. Deng, B. Melanson, J. Zhang, X. Gong, A. Abusleme, S. Datta, K. Ni, “Computational Associative Memory Based on Monolithically Integrated Metal-Oxide Thin Film Transistors for Update-Frequent Search Applications”, IEEE International Electron Devices Meeting (IEDM), 2021. * fabricated chip using NVM technology.[PDF]
[C37] H. Chen, M. Imani, “Density-Aware Parallel Hyperdimensional Genome Sequence Matching”, IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2022.[PDF]
[C36] S Shahhosseini, Y Ni, EK Naeini, M Imani, AM Rahmani, N Dutt, Flexible and Personalized Learning for Wearable Health Applications using HyperDimensional Computing, Proceedings of the Great Lakes Symposium on VLSI (GLSVLSI), 2022.[PDF]
[C35] Z. Zou, H. Alimohamadi, M. Imani, “Brain-Inspired Neural Adaptation for Dynamic and Scalable Hyperdimensional Learning”, GOMACTech Conference, 2022.
[C34] A. Cano, R. Cammorato, M. Imani, “Data and Model Privacy in Hyperdimensional Learning Systems”, GOMACTech Conference, 2022 .(Collaboration with Intel)
[C33] M. Imani, H. Najafi, “Hyperdimensional Stochastic Representation for Robust Computation with Noisy Emerging Technologies” GOMACTech Conference, 2022.
[C32] Z. Zou, Y. Kim, F. Imani, H. Alimohamadi, R. Cammarota,M. Imani, “Edge-based Hyperdimensional Learning System with Brain-Like Neural Adaptation”, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2021 (Collaboration with Intel) (Open Source @ GitLab)[PDF]
[C31] P. Podual, Y. Ni, Y. Kim, K. Ni, R. Kuma, R. Cammarota, M. Imani, “Hyperdimensional Self-Learning Systems Robust to Technology Noise and Bit-Flip Attacks”, IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2021 (Collaboration with Intel).
[C30] Y. Kim, M. Imani, M. Zuo, S. Gupta, T. Rosing, “Massively Parallel Big Data Classification on a Programmable Processing In-Memory Architecture”, IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2021 [PDF].
[C29] A. Kazemi, M. M. Sharifi, Z. Zou, M. Niemier, X. S. Hu, M. Imani, “MIMHD: Accurate and Efficient Hyperdimensional Inference using Multi-Bit In-Memory Computing”, IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2021 [PDF].
[C28] M. Imani, et. al., “Revisiting HyperDimensional Learning for FPGA and Low-Power Architectures”, EEE International Symposium on High-Performance Computer Architecture (HPCA), 2021 [PDF].
[C27] A. H. Cano, R. Cammarota, M. Imani, “PRID: Model Inversion Privacy Attacks in Hyperdimensional Learning Systems”, IEEE/ACM Design Automation Conference (DAC), 2021. (collaboration with Intel)(Open Source @ GitLab) [PDF]
[C26] P. Poduval, Z. Zhou, H. Najafi, H. Homayoun, M. Imani, “StocHD: Stochastic Hyperdimensional System for Efficient and Robust Learning fromraw data”, IEEE/ACM Design Automation Conference (DAC), 2021 [PDF].
[C25] A. H. Cano, M. Zhou, C. Zhou, X. Yin, M. Imani, “RegHD: Robust and Efficient Regression in Hyper-Dimensional Learning System”, IEEE/ACM Design Automation Conference (DAC), 2021 [PDF].
[C24] P. Poduval, M. Zhou, X. Yin, E. Sadredini, M. Imani, “Cognitive Correlative Encoding for Genome Sequence Matching in Hyperdimensional System”, IEEE/ACM Design Automation Conference (DAC), 2021 [PDF].
[C23] Y. Kim, J. Kim, M. Imani, “CascadeHD: Efficient Many-Class Learning Framework Using Hyperdimensional Computing”, IEEE/ACM Design Automation Conference (DAC), 2021 [PDF].
[C22] Z. Zou, Y. Kim, M. H. Najafi, M. Imani, “ManiHD: Efficient Hyper-Dimensional Learning Using Manifold Trainable Encoder”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021 [PDF].
[C21] S. Asadi, M. H. Najafi, M. Imani, “ A Low-Cost FSM-based Bit-Stream Generator for Low-Discrepancy Stochastic Computing”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021 [PDF].
[C20] A. H. Cano, Y. Kim, M. Imani, “ A Framework for Efficient and Binary Clustering in High-Dimensional Space”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021 (Open Source @ GitLab).[PDF]
[C19] A. H. Cano, N. Matsumoto, E. Ping, M. Imani, “OnlineHD: Robust, Efficient, and Single-Pass Online Learning Using Hyperdimensional System”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021 (Open Source @ GitLab).[PDF]
[C18] R. Garcia, F. Asgarinejad, B. Khaleghi, T. Rosing, M. Imani, “TruLook: A Framework for Configurable GPU Approximation”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021.[PDF]
[C17] S. Salamat, J. Kang, Y. Kim, M. Imani, “FPGA Acceleration of Protein Back-translation and Alignment”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021.[PDF]
[C16] M. Zhou, M. Li, M. Imani, T. Rosing, “ HyGraph: Accelerating Graph Processing with Hybrid Memory-centric Computing”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021.[PDF]
[C15] J. Morris, K. Ergun, B. Khaleghi, M. Imani, B. Aksanli, T. Rosing “HyDREA: Towards More Robust and Efficient Machine Learning Systems with Hyperdimensional Computing”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021.[PDF]
[C14] Y. Qian, Z. Fan, H. Wang, C. Li, M. Imani, K. Ni, G. L. Zhang, B. Li, U. Schlichtmann, C. Zhuo, X. Yin “Energy-Aware Designs of Ferroelectric Ternary Content Addressable Memory”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2021.[PDF]
[C13] H. Amrouch, X.S. Hu, M. Imani, A.F. Laguna, M. Niemier, S. Thomann, X. Yin, C. Zhuo, “Cross-layer Design for Computing-in-Memory: From Devices, Circuits, to Architectures and Applications”, IEEE Asia and South Pacific Design Automation Conference (ASP-DAC), 2021 (Invited paper).[PDF]
[C12] M. Zhou, M. Imani, Y. Kim, S. Gupta, T. Rosing, “DP-Sim: A Full-stack Simulation Infrastructure for Digital Processing In-Memory Architectures”, IEEE Asia and South Pacific Design Automation Conference (ASP-DAC), 2021.[PDF]
[C11] Y. Guo, M. Imani, J. Kang, S. Salamat, J. Morris, B. Aksanli, Y. Kim, T. Rosing, “HyperRec: Efficient Recommender Systems with Hyperdimensional Computing”, IEEE Asia and South Pacific Design Automation Conference (ASP-DAC), 2021.[PDF]
[C10] M. Imani, S. Pampana, S. Gupta, M. Zhou, Y. Kim, T. Rosing, “DUAL: Acceleration of Clustering Algorithms using Digital-based Processing In-Memory”, IEEE/ACM International Symposium on Microarchitecture (MICRO), 2020.[PDF]
[C9] C. Li, F. Müller, T. Ali, R. Olivo, M. Imani, S. Deng, C. Zhuo, T. Kämpfe, X. Yin, and K. Ni, Thomas Kämpfe, Xunzhao Yin, and Kai Ni, “Scalable Design of Multi-Bit Ferroelectric Content Addressable Memory for Data-Centric Computing”, IEEE International Electron Devices Meeting (IEDM), 2020. (Top device conference) * fabricated chip using NVM technology.[PDF]
[C8] C. Chen, S. Yang, W. Qian, M. Imani, X. Yin, C. Zhou, “Optimally Approximated and Unbiased Floating-Point Multiplier with Runtime Configurability”, IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2020 (Best paper candidate).[PDF]
[C7] S. Gupta, J. Morris, M. Imani, R. Ramkumar, J. Yu, A. Tiwari, B. Aksanli, T. Rosing “THRIFTY: Training with Hyperdimensional Computing across Flash Hierarchy”, IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2020.[PDF]
[C6] S. Gupta, M. Imani, H. Zhao, F. Wu, J. Zhao, T. Rosing “Implementing Binary Neural Networks in Memory with Approximate Accumulation”, IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2019. [PDF].
[C5] M. Imani, M. Samragh, Y. Kim, S. Gupta, F. Koushanfar, T. Rosing “Deep Learning Acceleration with Neuron-to-Memory Transformation”, IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2020 (Acceptance rate 19%) [PDF].
[C4] B. Khaleghi, M. Imani, T. Rosing “Prive-HD: Privacy-Preserved Hyperdimensional Computing”, IEEE/ACM Design Automation Conference (DAC), 2020.[PDF]
[C3] H. Nejatollahi, S. Gupta, M. Imani, R. Cammarota*, T. Rosing, N. Dutt “CryptoPIM: In-Memory Acceleration for RLWE Lattice-based Cryptography”, IEEE/ACM Design Automation Conference (DAC), 2020. (* collaboration with Intel) (Best paper candidate)[PDF]
[C2] S. Gupta, M. Imani,J. Sim, A. Huang, F. Wu, H. Najafi, T. Rosing, “SCRIMP: A General Stochastic Computing Architecture using ReRAM in-Memory Processing”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2020 [PDF].
[C1] Y. Kim, M. Imani, N. Moshiri*, T. Rosing, “GenieHD: Efficient DNA Pattern Matching Accelerator Using Hyperdimensional Computing”, IEEE/ACM Design Automation and Test in Europe Conference (DATE), 2020. (* collaboration with groups in Bioinformatics) (Best paper candidate)[PDF]
Journals
[J11] P. Poduval, H. Alimohamadi, A. Zakeri, H. Najafi, F. Imani, T. Givargis, M. Imani, “GrapHD: Graph-based Hyperdimensional Memorization for Brain-Like Cognitive Learning,” Frontiers in Neuroscience, 2022.[PDF]
[J10] Z. Zou, H. Alimohamadi, Y. Kim, H. Najafi, N. Srinivasa, M. Imani, “EventHD: Robust and Efficient Hyperdimensional Learning with Neuromorphic Sensor,” Frontiers in Neuroscience, 2022 (Collaboration with Intel).[PDF]
[J9] M. Alam, H. Najafi, N. Taherinejad, M. Imani, R. Gottumukkala, “Stochastic Computing in Beyond Von-Neumann Era: Processing Bit-Streams in Memristive Memory,” IEEE Transactions on Circuits and Systems II, 2022.[PDF]
[J8] Z. Zou, H. Alimohamadi, A. Zakeri, F. Imani, Y. Kim, H. Najafi, M. Imani, “Memory-inspired spiking hyperdimensional network for robust online learning”, Nature Scientific reports, 2022.[PDF]
[J7] M. Imani, M. Imani, S.F. Ghoreishi, “Bayesian Optimization for Expensive Smooth-Varying Functions”, IEEE Intelligent Systems, 2022.[PDF]
[J6] X. Yin, F. Müller, Q. Huang, C. Li, M. Imani, Z. Yang, J. Cai, M. Lederer, R. Olivo, “An Ultra-Compact Single FeFET Binary and Multi-Bit Associative Search Engine”, arXiv preprint arXiv:2203.0794, 2022.[PDF]
[J5] S. Gupta, M. Imani, J. Sim, A. Huang, F. Wu, J. Kang, Y. Kim, T. Rosing, “COSMO: Computing with Stochastic Numbers in Memory”, ACM Journal on Emerging Technologies in Computing Systems (JETC), 2022.[PDF]
[J4] S. Gupta, B. Khaleghi, S. Salamat, J. Morris, R. Ramkumar, J. Yu, A. Tiwari, J. Kang, M. Imani, B. Aksanli, T. Rosing “Store-n-Learn: Classification and Clustering with Hyperdimensional Computing across Flash Hierarchy”, ACM Transactions on Embedded Computing Systems (TECS), 2022.[PDF]
[J3] C. Chen, W. Qian, M. Imani, X. Yin, C. Zhuo, “PAM: A Piecewise-Linearly-Approximated Floating-Point Multiplier with Unbiasedness and Configurability,” IEEE Transactions on Computer, 2021.[PDF]
[J2] J. Morris, R. Fernando, Y. Hao, M. Imani, B. Aksanli, T. Rosing, “Locality-based Encoder and Model Quantization for Efficient Hyper-Dimensional Computing”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2020.[PDF]
[J1] S. Salamat, M. Imani, T. Rosing, “HD-Core: Exploiting Computational Reuse for FPGA-based Acceleration of Hyperdimensional Computing”, IEEE Transactions on Computers (TC), 2020.[PDF]