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Preprint

Euntae Choi, Kyungmi Lee, Kiyoung Choi, "Autoencoder-Based Incremental Class Learning without Retraining on Old Data." Preprint, 2019.
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Preprint

Kyungmi Lee, Anantha Chandrakasan, "Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods." Preprint, 2020.
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Published in IEEE Open Journal of Circuits and Systems, 2021

Kyungmi Lee, Anantha Chandrakasan, "Understanding the Energy vs. Adversarial Robustness Trade-Off in Deep Neural Networks", IEEE Open Journal of Circuits and Systems, 2021.
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Published in In the proceedings of IEEE Workshop on Signal Processing Systems (SiPS), 2021

Bob Owens Best Student Paper Award

Kyungmi Lee, Anantha Chandrakasan, "Understanding the Energy vs. Adversarial Robustness Trade-Off in Deep Neural Networks." In the proceedings of IEEE Workshop on Signal Processing Systems (SiPS), 2021.
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Published in In the proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022

Kyungmi Lee, Anantha Chandrakasan, "SparseBFA: Attacking Sparse Deep Neural Networks with the Worst-Case Bit Flips on Coordinates", In the proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.
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Published in JAMA Otolaryngology–Head & Neck Surgery, 2022

Gabrielle Cahill, Annette Wang, Kyungmi Lee, Masaharu Sakagami, D. Welling, Konstantina Stankovic, "Association of Stapedotomy Volume and Patient Sex With Better Outcome", JAMA Otolaryngology–Head & Neck Surgery, 2022.
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Published in In the proceedings of IEEE 49th European Solid State Circuits Conference (ESSCIRC), 2023

Student Research Preview (ISSCC'23) Best Poster

Saurav Maji, Kyungmi Lee, Cheng Gongye, Yunsi Fei, Anantha Chandrakasan, "An Energy-Efficient Neural Network Accelerator with Improved Protections Against Fault-Attacks", In the proceedings of IEEE 49th European Solid State Circuits Conference (ESSCIRC), 2023.
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Published in In the proceedings of IEEE/ACM International Symposium on Microarchitecture, 2023

Kyungmi Lee, Mengjia Yan, Joel Emer, Anantha Chandrakasan, "SecureLoop: Design Space Exploration of Secure DNN Accelerators", In the proceedings of IEEE/ACM International Symposium on Microarchitecture, 2023.
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Published in IEEE Journal of Solid-State Circuits, 2024

Saurav Maji, Kyungmi Lee, Cheng Gongye, Yunsi Fei, Anantha Chandrakasan, "An Energy-Efficient Neural Network Accelerator With Improved Resilience Against Fault Attacks", IEEE Journal of Solid-State Circuits, 2024.
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Published in IEEE Computer Architecture Letters, 2024

Saurav Maji, Kyungmi Lee, Anantha Chandrakasan, "SparseLeakyNets: Classification Prediction Attack Over Sparsity-Aware Embedded Neural Networks Using Timing Side-Channel Information", IEEE Computer Architecture Letters, 2024.
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Published in IEEE Circuits and Systems Magazine, 2025

Kyungmi Lee, Maitreyi Ashok, Saurav Maji, Rashmi Agrawal, Ajay Joshi, Mengjia Yan, Joel Emer, Anantha Chandrakasan, "Secure Machine Learning Hardware: Challenges and Progress", IEEE Circuits and Systems Magazine, 2025.
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In Preparation

Kyungmi Lee, Gaurab Das, Donghyeon Han, Anantha Chandrakasan, "Securing DNN Acceleration from DRAM Vulnerabilities with Low-overhead Authenticated Encryption." In Preparation, 2025.

Published in In the proceedings of International Workshop on Hardware and Architectural Support for Security and Privacy, 2025

Jan Strzeszynski, Jianming Tong, Kyungmi Lee, Nathan Xiong, Angshuman Parashar, Joel Emer, Tushar Krishna, Mengjia Yan, "SquareLoop: Explore Optimal Authentication Block Strategy for ML", In the proceedings of International Workshop on Hardware and Architectural Support for Security and Privacy, 2025.
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Accepted to IEEE International Symposium on Performance Analysis of Systems and Software

Kyungmi Lee, Zhiye Song, Eun Kyung Lee, Xin Zhang, Tamar Eilam, Anantha Chandrakasan, "EnergAIzer: Fast and Accurate GPU Power Estimation Framework for AI Workloads", 2026.

Published in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2026

Kyungmi Lee, Gaurab Das, Donghyeon Han, Anantha Chandrakasan, "Securing DNN Acceleration From Off-Chip Memory Vulnerabilities With Low-Overhead Authenticated Encryption", IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2026.
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