Publications

Journal Articles

  1. N. Kim, E. Andrews, and P. Mishra, “Optimizing Generative Adversarial Networks with Tensor Decompositions for Resource‑Constrained Systems,” IEEE Embedded Systems Letters, Feb. 2026, to be published.
  2. A. Jayasena, E. Andrews, and P. Mishra,”TVLA*: Test Vector Leakage Assessment on Hardware Implementations of Asymmetric Cryptography Algorithms,” IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 31, no. 9, pp. 1269–1279, Sep. 2023, doi: 10.1109/TVLSI.2023.3297027.

Conference Proceedings

  1. E. Andrews and P. Mishra, “Accelerating Machine Learning Applications through Optimized Tensor Decompositions,” in International Symposium of Quality Electronic Design, Apr. 2026, to appear.
  2. E. Andrews, A. Jayasena, and P. Mishra, “Semantic‑Guided Test Generation using Fine‑Tuned LLMs for Validation of Hardware Accelerators,” in International Symposium of Quality Electronic Design, Apr. 2026, to appear.
  3. E. Andrews, D. Bau, and J. Blanchard, “From Droplet to Lilypad: Present and Future of Dual-Modality Environments,” in 2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), Oct. 2021, pp. 1–2. doi: 10.1109/VL/HCC51201.2021.9576355.

Book Chapters

  1. E. Andrews and P. Mishra, “Quantum Artificial Intelligence,” Springer, 2025.
  2. A. Jayasena, E. Andrews, and P. Mishra, “Quantum Testing and Validation,” in Design Automation for Quantum Computing, Springer, 2025.
  3. E. Andrews and P. Mishra, “Functional Verification using Large Language Models,” in LLM for SoC Design and Security, Springer, 2025.
  4. E. Andrews, Z. Pan, and P. Mishra, “Explainable Artificial Intelligence,” in Explainable AI for Cybersecurity, Springer, 2023, pp. 29–51.

Preprints and Other Publications

  1. E. Andrews and P. Mishra, “Quantum Masked Autoencoders for Vision Learning.” arxiv:2511.17372, Nov. 2025.
  2. E. Andrews and P. Mishra, “Memory‑Efficient Machine Learning using Tensor Decompositions.” SRC TECHCON, Sep. 2025.
  3. N. Kim, E. Andrews, and P. Mishra, “Efficient Data Augmentation using Generative Models with Tensor Decompositions.” SRC TECHCON,Sep. 2025.
  4. E. Andrews and P. Mishra, “Explainable Metric Learning for Deflating Data Bias.” SRC TECHCON, Sep. 2024.
  5. Z. Pan, E. Andrews, L. Chang, and P. Mishra, “Privacy-Preserving Debiasing using Data Augmentation and Machine Unlearning.” arXiv, Apr. 19, 2024. doi: 10.48550/arXiv.2404.13194.
  6. E. Andrews, Z. Pan, and P. Mishra, “Towards Accurate Measurement of Pretraining Bias.” SRC TECHCON, Sep. 2023.
  7. K. Rani, E. Andrews, A. Jayasena and P. Mishra, “Defending Elliptic Curve Cryptography against Laser Fault injection Attacks”, GOMACTech Conference, San Diego, California, Mar. 20-23, 2023.