Publications

     Conference:

1. Z. Ghodsi*, M. Javaheripi*, N. Sheybani*, X. Zhang*, K. Huang, and F. Koushanfar. "zPROBE: Zero peek robustness checks for federated learning." IEEE/CVF International Conference on Computer Vision (CVPR), 2023. (* equal contribution) 

[paper]

2. R. Zhang, M. Javaheripi, Z. Ghodsi, A. Bleiweiss, and F. Koushanfar. "AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs". ACM/IEEE Design Automation Conference (DAC), 2023.

3. J. W. Chang, M. Javaheripi, and F. Koushanfar. "VideoFlip: Adversarial Bit Flips for Reducing Video Service Quality". ACM/IEEE Design Automation Conference (DAC), 2023.

4. K. Babel*, M. Javaheripi*, Y. Ji, M. Kelkar, F. Koushanfar, and A. Juels. "Lanturn: Measuring economic security of smart contracts through adaptive learning". ACM SIGSAC Conference on Computer and Communications Security (CCS), 2023. (* equal contribution) 

[paper]

5. M. Javaheripi, Gustavo de Rosa, Subhabrata Mukherjee, Shital Shah, Tomasz Religa, Caio Mendes, Sebastien Bubeck, Farinaz Koushanfar, Debadeepta Dey. "LiteTransformerSearch: Training-free On-device Search for Efficient Autoregressive Language Models", Neural Information Processing Systems (NeurIPS), 2022. 

[paper, code]

6. J. Chang, M. Javaheripi, S. Hidano, F. Koushanfar. "RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression". The Network and Distributed System Security (NDSS) Symposium, 2022. 

[paper]

7. S. Hussain*, M. Javaheripi*, M. Samragh*, F. Koushanfar. "COINN: Crypto/ML Codesign for Oblivious Inference via Neural Networks".  ACM Conference on Computer and Communications Security (CCS), 2021. (* equal contribution) 

[paper, code]

8. M. Javaheripi, F. Koushanfar. “HASHTAG: Hash Signatures for Online Detection of Fault-Injection Attacks on Deep Neural Networks.” IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2021. 

[paper]

9. M. Javaheripi, M. Samragh, T. Javidi, and F. Koushanfar. "GeneCAI: Genetic Evolution for Acquiring Compact AI". Genetic and Evolutionary Computation Conference (GECCO), 2020. 

[paper, code]

10. M. Javaheripi, M. Samragh, G. Fields, T. Javidi, F. Koushanfar. "CLEANN: Accelerated Trojan Shield for Embedded Neural Networks". IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2020. 

[paper]

11. S. Hussain, M. Javaheripi, P. Neekhara, R. Kastner, and F. Koushanfar. "FastWave: Accelerating Autoregressive Convolutional Neural Networks on FPGA". IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2019. 

[paper]

12. M. S. Riazi, M. Javaheripi, S. U. Hussain, and F. Koushanfar. "MPCircuits: Optimized Circuit Generation for Secure Multi-Party Computation". IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2019. 

[paper]

13. M. Imani, M. Bosch, M. Javaheripi, B. Rouhani, X. Wu, F. Koushanfar, and T. Rosing. "SemiHD: Semi-Supervised Learning Using Hyperdimensional Computing". IEEE/ACM International Conference On Computer Aided Design (ICCAD), 2019. 

[paper]

14. B. Rouhani, M.Samragh, M. Javaheripi, T. Javidi, and F. Koushanfar. "DeepFense: Online Accelerated Defense Against Adversarial Deep Learning". International Conference on Computer-Aided Design (ICCAD), 2018. 

[paper]

15. B. Rouhani, M.Samragh, M. Javaheripi, T. Javidi, and F. Koushanfar. "Assured Deep Learning: Practical Defense Against Adversarial Attacks." 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2018.

[paper]

Journal:

1. M. Javaheripi, J. W. Chang, and F. Koushanfar. "AccHashtag: Accelerated Hashing for Detecting Fault-Injection Attacks on Embedded Neural Networks." ACM Journal on Emerging Technologies in Computing Systems (JETC), 2022.

2. M. Javaheripi, B. Rouhani, F. Koushanfar. “SWANN: Small-World Architecture for Fast Convergence of Neural Networks.” IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), 2021.

[paper]

3. M. Javaheripi, M. Samragh and F. Koushanfar. “AutoRank: Automated Rank Selection for Effective Neural Network Customization.” IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), 2021.

[paper]

4. M. Javaheripi, M. Samragh, B. D. Rouhani, T. Javidi, F. Koushanfar. "CuRTAIL: ChaRacterizing and Thwarting AdversarIal deep Learning". IEEE Transactions on Dependable and Secure Computing (TDSC), 2020.

[paper]

5. M. Javaheripi, M. Samragh, T. Javidi, and F. Koushanfar. "AdaNS: Adaptive Non-uniform Sampling for Automated Design of Compact DNNs." IEEE Journal of Selected Topics in Signal Processing, 2020.

[paper, code]

6. M. Samragh*, M. Javaheripi*, and F. Koushanfar. "EncoDeep: Realizing Bit-Flexible Encoding for Deep Neural Networks." ACM Transactions on Embedded Computing Systems (TECS), 2020. (* equal contribution)

[paper]

Workshop:

1. H. Pouransari, M. Javaheripi, V. Sharma, and O. Tuzel. "Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution". IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2021. 

[paper]

2. G. Fields, M. Samragh, M. Javaheripi, F. Koushanfar, T. Javidi. “Trojan Signatures in DNN Weights.” IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021. 

[paper]

3. M. Javaheripi, M. Samragh, T. Javidi, and F. Koushanfar. "ASCAI: Adaptive Sampling for acquiring Compact AI". 6th ICML Workshop on Automated Machine Learning (AutoML), 2019. 

[paper]

Magazine:

1. M. Javaheripi, M. Samragh, and F. Koushanfar. "Peeking Into the Black Box: A Tutorial on Automated Design Optimization and Parameter Search". IEEE Solid-State Circuits Magazine, 11(4), pp.23-28, 2019.

[paper]

Preprints:

1. Textbooks Are All You Need [paper]