Xun Jiao
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
42
Venues
24
Active years
2016–2026
Best venue rank
A*
Where they publish
- ADATE9 papers
- AICCAD4 papers
- A*DAC4 papers
- ADSN3 papers
- AISSRE2 papers
- BASPDAC2 papers
- BACNS1 paper
- CISCAS1 paper
- AWSDM1 paper
- A*ISCA1 paper
- AITC1 paper
- A*ASPLOS1 paper
- CPDCAT1 paper
- A*SIGIR1 paper
- A*CVPR1 paper
- MulticonferenceICASSP1 paper
- BIJCNN1 paper
- ARTSS1 paper
- NationalACSSC1 paper
- Journal PublishedEMSOFT1 paper
- ARTAS1 paper
- CDSD1 paper
- A*ICSE1 paper
- CICCD1 paper
Papers
42 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACNS | Understanding the Robustness of BERT Models Against Hardware Errors: An Experimental Study. | Ruixuan Wang, Dongning Ma, Xun Jiao |
| 2026 | ISCAS | MILEAM: Modeling Input-Aware Logic Errors of Approximate Multipliers using Machine Learning. | Jinghao Wen, Dongning Ma, Xun Jiao |
| 2026 | WSDM | Stealing Black-box Hyperdimensional Computing Models Without Data. | Dongning Ma, Ruixuan Wang, Xun Jiao |
| 2025 | DSN | Large-Scale AI Infra Reliability: Challenges, Strategies, and Llama 3 Training Experience. | Xun Jiao, Abhinav Pandey, Karthik Pattabiraman, Fan Fred Lin |
| 2025 | DSN | Hardware Telemetry at Scale: A Case Study on SSDs Endurance Monitoring in Datacenters. | Olusiji Medaiyese, Fred Lin, Harish Dattatraya Dixit, Richa Mishra, Andrea Baglioni, Leandro Silva, Mike Elkin, Andrei Ilyashenko, Gor Safaryan, Dhankaran Singh Ajravat, Xun Jiao, Vineet Parekh |
| 2025 | ISCA | Meta's Second Generation AI Chip: Model-Chip Co-Design and Productionization Experiences. | Joel Coburn, Chunqiang Tang, Sameer Abu Asal, Neeraj Agrawal, Raviteja Chinta, Harish Dattatraya Dixit, Brian Dodds, Saritha Dwarakapuram, Amin Firoozshahian, Cao Gao, Kaustubh Gondkar, Tyler Graf, Junhan Hu, Jian Huang, Sterling Hughes, Adam Hutchin, Bhasker Jakka, Guoqiang Jerry Chen, Indu Kalyanaraman, Ashwin Kamath, Pankaj Kansal, Erum Kazi, Roman Levenstein, Mahesh Maddury, Alex Mastro, Siji Medaiyese, Pritesh Modi, Jack Montgomery, Nadathur Satish, Amit Nagpal, Ashwin Narasimha, Maxim Naumov, Eleanor Ozer, Jongsoo Park, Poorvaja Ramani, Harikrishna Reddy, David Reiss, Deboleena Roy, Sathish Sekar, Arushi Sharma, Pavan Shetty, Aravind Sukumaran-Rajam, Eran Tal, Mike Tsai, Shreya Varshini, Richard Wareing, Olvia Wu, Xiaolong Xie, Jinghan Yang, Hangchen Yu, Tanmay Zargar, Zitong Zeng, Feixiong Zhang, Ajit Mathews, Xun Jiao, Jiyuan Zhang, Emmanuel Menage, Truls Edvard Stokke, Mohammed Sourouri |
| 2025 | ISSRE | Understanding Recommendation System Robustness Against Silent Data Corruption: An Empirical Study. | Dongning Ma, Xun Jiao, Fan Fred Lin, Daniel Moore, Sriram Sankar |
| 2025 | ITC | CP-Bench: A PyTorch Test Suite to Detect AI Hardware Failure, Performance Degradation, and Silent Data Corruption. | Xun Jiao, Sunny Yang, Suman Gumudavelli, Shreya Varshini, Abhinav Pandey, Abhinav Jauhri, Francesco Caggioni, Gautham Vunnam, Harish Dattatraya Dixit, Jason Liang, Philip Henzler, Sameeksha Gupta, Tyler Graf, Venkat Ramesh, Fan Fred Lin |
| 2024 | ASPLOS | Dr. DNA: Combating Silent Data Corruptions in Deep Learning using Distribution of Neuron Activations. | Dongning Ma, Fan Fred Lin, Alban Desmaison, Joel Coburn, Daniel Moore, Sriram Sankar, Xun Jiao |
| 2024 | DATE | PP-HDC: A Privacy-Preserving Inference Framework for Hyperdimensional Computing. | Ruixuan Wang, Wengying Wen, Kyle Juretus, Xun Jiao |
| 2024 | PDCAT | Research on Task Migration Problem Based on Link Uncertainty in Adversarial Scenarios. | Xiangxiang Xing, Pan Li, Tianyu Zuo, Yuanshuang Jiang, Kai Di, Xin Wang, Xun Jiao, Yichuan Jiang, Dan Chen |
| 2024 | SIGIR | Memory-Efficient Deep Recommender Systems using Approximate Rotary Compositional Embedding. | Dongning Ma, Xun Jiao |
| 2023 | ASPDAC | Beyond von Neumann Era: Brain-Inspired Hyperdimensional Computing to the Rescue. | Hussam Amrouch, Paul R. Genssler, Mohsen Imani, Mariam Issa, Xun Jiao, Wegdan Mohammad, Gloria Sepanta, Ruixuan Wang |
| 2023 | ASPDAC | Robust Hyperdimensional Computing against Cyber Attacks and Hardware Errors: A Survey. | Dongning Ma, Sizhe Zhang, Xun Jiao |
| 2023 | CVPR | PerfHD: Efficient ViT Architecture Performance Ranking using Hyperdimensional Computing. | Dongning Ma, Pengfei Zhao, Xun Jiao |
| 2023 | DATE | Comprehensive Analysis of Hyperdimensional Computing Against Gradient Based Attacks. | Hamza Errahmouni Barkam, SungHeon Evan Jeong, Calvin Yeung, Zhuowen Zou, Xun Jiao, Mohsen Imani |
| 2023 | DATE | Adversarial Attack on Hyperdimensional Computing-based NLP Applications. | Sizhe Zhang, Zhao Wang, Xun Jiao |
| 2023 | ICASSP | Strategies for Enhanced Signal Modulation Classifications Under Unknown Symbol Rates and Noise Conditions. | Ruixuan Wang, Yue Qi, Mojtaba Vaezi, Xun Jiao, Moeness G. Amin |
| 2023 | ICCAD | Invited Paper: Hyperdimensional Computing for Resilient Edge Learning. | Hamza Errahmouni Barkam, SungHeon Evan Jeong, Sanggeon Yun, Calvin Yeung, Zhuowen Zou, Xun Jiao, Narayan Srinivasa, Mohsen Imani |
| 2023 | IJCNN | On Hyperdimensional Computing-based Federated Learning: A Case Study. | Sizhe Zhang, Dongning Ma, Song Bian, Lei Yang, Xun Jiao |
| 2023 | RTSS | Brief Industry Paper: Evaluating Robustness of Deep Learning-Based Recommendation Systems Against Hardware Errors: A Case Study. | Xun Jiao, Fan Fred Lin, Matt Xiao, Alban Desmaison, Daniel Moore, Sriram Sankar |
| 2022 | ACSSC | Handcrafted and Neural Network Based Features for Outlier Modulation Detection. | Yue Qi, Ruixuan Wang, Mojtaba Vaezi, Jonathan Francis, Xun Jiao |
| 2022 | DAC | ODHD: one-class brain-inspired hyperdimensional computing for outlier detection. | Ruixuan Wang, Xun Jiao, X. Sharon Hu |
| 2022 | DATE | PoisonHD: Poison Attack on Brain-Inspired Hyperdimensional Computing. | Ruixuan Wang, Xun Jiao |
| 2022 | DATE | Energy-Efficient Brain-Inspired Hyperdimensional Computing Using Voltage Scaling. | Sizhe Zhang, Ruixuan Wang, Dongning Ma, Jeff Jun Zhang, Xunzhao Yin, Xun Jiao |
| 2022 | ICCAD | ScaleHD: Robust Brain-Inspired Hyperdimensional Computing via Adapative Scaling. | Sizhe Zhang, Mohsen Imani, Xun Jiao |
| 2021 | DAC | HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing. | Dongning Ma, Jianmin Guo, Yu Jiang, Xun Jiao |
| 2021 | DATE | Workload-Aware Approximate Computing Configuration. | Dongning Ma, Rahul Thapa, Xingjian Wang, Xun Jiao, Cong Hao |
| 2021 | EMSOFT | Towards scalable, secure, and smart mission-critical IoT systems: review and vision. | Xiaolong Guo, Song Han, X. Sharon Hu, Xun Jiao, Yier Jin, Fanxin Kong, Michael Lemmon |
| 2021 | RTAS | Brief Industry Paper: HDAD: Hyperdimensional Computing-based Anomaly Detection for Automotive Sensor Attacks. | Ruixuan Wang, Fanxin Kong, Hasshi Sudler, Xun Jiao |
| 2020 | DAC | TEVoT: Timing Error Modeling of Functional Units under Dynamic Voltage and Temperature Variations. | Xun Jiao, Dongning Ma, Wanli Chang, Yu Jiang |
| 2020 | DAC | ICS Protocol Fuzzing: Coverage Guided Packet Crack and Generation. | Zhengxiong Luo, Feilong Zuo, Yuheng Shen, Xun Jiao, Wanli Chang, Yu Jiang |
| 2020 | DSD | AxBy: Approximate Computation Bypass for Data-Intensive Applications. | Dongning Ma, Xun Jiao |
| 2020 | DSN | A Machine Learning-Based Error Model of Voltage-Scaled Circuits. | Dongning Ma, Xun Jiao |
| 2020 | ICCAD | Fixed-Priority Scheduling and Controller Co-Design for Time-Sensitive Networks. | Xiaotian Dai, Shuai Zhao, Yu Jiang, Xun Jiao, Xiaobo Sharon Hu, Wanli Chang |
| 2019 | ISSRE | Engineering a Better Fuzzer with Synergically Integrated Optimizations. | Jie Liang, Yuanliang Chen, Mingzhe Wang, Yu Jiang, Zijiang Yang, Chengnian Sun, Xun Jiao, Jiaguang Sun |
| 2018 | DATE | Energy-efficient neural networks using approximate computation reuse. | Xun Jiao, Vahideh Akhlaghi, Yu Jiang, Rajesh K. Gupta |
| 2018 | ICSE | SAFL: increasing and accelerating testing coverage with symbolic execution and guided fuzzing. | Mingzhe Wang, Jie Liang, Yuanliang Chen, Yu Jiang, Xun Jiao, Han Liu, Xibin Zhao, Jiaguang Sun |
| 2017 | DATE | Combining structural and timing errors in overclocked inexact speculative adders. | Xun Jiao, Vincent Camus, Mattia Cacciotti, Yu Jiang, Christian C. Enz, Rajesh K. Gupta |
| 2017 | DATE | SLoT: A supervised learning model to predict dynamic timing errors of functional units. | Xun Jiao, Yu Jiang, Abbas Rahimi, Rajesh K. Gupta |
| 2017 | ICCAD | An assessment of vulnerability of hardware neural networks to dynamic voltage and temperature variations. | Xun Jiao, Mulong Luo, Jeng-Hau Lin, Rajesh K. Gupta |
| 2016 | ICCD | WILD: A workload-based learning model to predict dynamic delay of functional units. | Xun Jiao, Yu Jiang, Abbas Rahimi, Rajesh K. Gupta |