Scholar
Lei Jiang
Google Scholar ID: -1sXorAAAAAJ
Indiana University Bloomington
Citations & Impact
Citations
2,798
H-index
28
i10-index
59
Publications
20
Co-authors
11
list available
Contact
No contact links provided.
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- LLMCarbon: Modeling the End-to-End Carbon Footprint, ICLR, 2024.
- TITAN: A Fast and Distributed Large-Scale Trapped-Ion NISQ, DAC, 2024.
- QTrojan: A Circuit Backdoor Against Quantum Neural, ICASSP, 2023.
- PRIMER: A Privacy-Preserving Transformer on Encrypted Data, DAC, 2023.
- MATCHA: A Fast and Energy-Efficient Accelerator for, DAC, 2022.
- SMART: A Heterogeneous Scratchpad Memory Architecture, MICRO, 2021.
- HEMET: A HE-Friendly Privacy-Preserving Mobile Neural, ICML, 2021.
- SAFENet: A Secure, Accurate and Fast Neural Network Inference, ICLR, 2021.
- EXMA: A Genomics Accelerator for Exact-Matching, HPCA, 2021.
- Glyph: Fast and Accurately Training Deep Neural, NeurIPS, 2020.
- AutoPrivacy: Automated Layer-wise Parameter Selection, NeurIPS, 2020.
- Falcon: Fast Spectral Inference on Encrypted Data, NeurIPS, 2020.
- Helix: Algorithm/Architecture Co-design, PACT, 2020.
- AutoQ: Automated Kernel-Wise Neural Network, ICLR, 2020.
- Mitigating Voltage Drop in Resistive Memories, HPCA, 2020.
- SHE: A Fast and Accurate Deep Neural Network, NeurIPS, 2019.
- FindeR: Accelerating FM-Index-based Exact, PACT, 2019.
- Balancing Performance and Lifetime of MLC PCM, HPCA, 2017.
- SD-PCM: Constructing Reliable Super Dense PCM, ASPLOS, 2015.
- A Low Power and Reliable Charge Pump Design, ISCA, 2014.
- FPB: Fine-grained Power Budgeting to Improve Write, MICRO, 2012.
- Improving Write Operations in MLC Phase Change Memory, HPCA, 2012.
Research Experience
- Leading the Uncharted@IU research group within the Department of Intelligent Systems Engineering; focuses on hardware accelerator design, privacy-preserving machine learning, and sustainable machine learning.
Background
- Research interests include hardware accelerator design, privacy-preserving machine learning, and sustainable machine learning. Particularly focused on designing novel cryptographic primitives, algorithms, and hardware for machine learning.
Miscellany
- The page also mentions team composition, such as Captain Dr. Lei Jiang, and other roles like Mate, Bosun, etc., indicating the division of labor within the team.
