Yifeng He, Jiabo Huang, Yuyang Rong, Yiwen Guo, Ethan Wang, and Hao Chen UniTSyn: A Large-Scale Dataset Capable of Enhancing the Prowess of Large Language Models for Program Testing International Symposium on Software Testing and Analysis (ISSTA), September, 2024. Yunlong Lyu, Yuxuan Xie, Peng Chen, and Hao Chen, Prompt Fuzzing for Fuzz Driver Generation ACM Conference on Computer and Communications Security (CCS), October 2024. Yuyang Rong, Zhanghan Yu, Zhenkai Weng, Stephen Neuendorffer, and Hao Chen, IRFuzzer: Specialized Fuzzing for LLVM Backend Code Generation, IEEE/ACM International Conference on Software Engineering (ICSE), April 2025. David Wagner (UC Berkeley), Hao Chen (UC Davis), Christopher Kruegel (UC Santa Barbara) AI for Cybersecurity Ziyu Wang, Anil Kanduri, Seyed Amir Hossein Aqajari, Salar Jafarlou, Sanaz R. Moosavi, Pasi Liljeberg, Shaista Malik, and Amir M. Rahmani, “ECG Unveiled: Analysis of Client Re-identification Risks in Real-World ECG Datasets,” In Proceedings of the IEEE-EMBS International Conference on Body Sensor Networks – Sensors and Systems for Digital Health (BSN'24), 2024, USA. Ziyu Wang, Elahe Khatibi, Sanaz R. Moosavi, Pasi Liljeberg, Shaista Malik, and Amir M. Rahmani, “TransECG: Leveraging Transformers for Explainable ECG Re-identification Risk Analysis” Submitted to the 40th ACM/SIGAPP Symposium On Applied Computing (SAC), 2025, Italy. Amir Rahmani (UC Irvine), Shaista Malik (UC Irvine) Safeguarding Privacy of Cardiovascular Waveforms through Reinforcement Learning-Guided Generative Models Samuel Pfrommer, Brendon Anderson, and Somayeh Sojoudi, Projected Randomized Smoothing for Certified Adversarial Robustness, Transactions on Machine Learning Research, 2023 (INFORMS Data Mining Best Student Paper Award Runner-Up). Yatong Bai, Brendon G. Anderson, Aerin Kim, and Somayeh Sojoudi, Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing, SIAM Journal on Mathematics of Data Science (SIMODS). Baturalp Yalcin, Haixiang Zhang, Javad Lavaei, and Murat Arcak, Exact Recovery for System Identification with More Corrupt Data than Clean Data, under review. Ying Chen and Javad Lavaei, Measurement manipulation of the matrix sensing problem to improve optimization landscape, under review. Ahmad Al-Tawaha, Elson Cibaku, SangWoo Park, Javad Lavaei, and Ming Jin, Distributed Optimization and Learning: A Paradigm Shift for Power Systems, under review. Eli Brock, Haixiang Zhang, Javad Lavaei, and Somayeh Sojoudi, Distributionally Robust Joint Chance-Constrained Optimal Power Flow using Relative Entropy, under review. Eli Brock, Haixiang Zhang, Julie Mulvaney Kemp, Javad Lavaei, and Somayeh Sojoudi, Distributionally Robust Optimization for Nonconvex QCQPs with Stochastic Constraints, to appear in 62nd IEEE Conference on Decision and Control, 2023.
QUANTUM SCIENCE
Simulation of quantum optical phenomena on a superconducting quantum computer Marina Radulaski (UC Davis), Irfan Siddiqi (UC Berkeley)
Marinelli, Brian, Alex H. Rubin, Victoria A. Norman, Zainab Rizvi, Ravi Naik, David I. Santiago, Christopher Spitzer et al. "Digital Tavis-Cummings Simulation on Superconducting Quantum Hardware with Error Mitigation." In Quantum 2.0, pp. QM2A-3. Optica Publishing Group, 2023. [under the 2nd round of review in Quantum] A. H. Rubin. B. Marinelli, V. A. Norman, Z. Rizvi, A. D. Burch, R. K. Naik, J. M. Kreikebaum, M. N. H. Chow, D. S. Lobser, M. C. Revelle, C. G. Yale, M. Ivory, D. I. Santiago, C. Spitzer, M. Krstic- Marinkovic, S. M. Clark, I. Siddiqi, M. Radulaski, "Digital Quantum Simulation of Cavity Quantum Electrodynamics: Insights from Superconducting and Trapped Ion Quantum Testbeds," arXiv:2404.03861. [in submission] B. Marinelli, A. H. Rubin, V. A. Norman, S. Yang, R. Naik, B. M. Niedzielski, D. K. Kim, R. Das, M. Schwartz, D. I. Santiago, C. Spitzer, I. Siddiqi, M. Radulaski, "Observation of Photon Blockade in a Tavis-Cummings System."
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