Huan Zhang

Huan Zhang 

Huan Zhang

Ph.D. Candidate
Department of Electrical and Computer Engineering
University of California, Davis
Davis, CA, 95616

Email:ecezhang AT ucdavis DOT edu

Resume (pdf)


My current research interests include machine learning, optimization and parallel computing. Some recent works include exploring the robustness issues and adversarial examples in deep neural networks from an optimization perspective, accelerating gradient boosted decision tree (GBDT) training on GPUs, and designing large-scale asynchronous parallel stochastic gradient descent and coordinate descent optimizers in multi-core and distributed settings especially for deep learning training.

During 2012-2015, I also worked on a few topics in computer architecture and computer networks.

My advisors are Cho-Jui Hsieh and Venkatesh Akella.


Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach , Tsui-Wei Weng*, Huan Zhang*, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel (* Equal contribution). International Conference on Learning Representations (ICLR), 2018. (pdf) (code)

Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning, Hongge Chen*, Huan Zhang*, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh (* Equal contribution). arXiv:1712.02051, 2017 (pdf) (code).

Towards Robust Neural Networks via Random Self-ensemble, Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh. arXiv:1712.00673, 2017 (pdf).

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples, Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi and Cho-Jui Hsieh. In AAAI Conference on Artificial Intelligence (AAAI), 2018. (pdf) (code)

ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models, Pin-Yu Chen*, Huan Zhang*, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh. (* Equal contribution) ACM Conference on Computer and Communications Security (CCS) Workshop on Artificial Intelligence and Security (AISec), 2017. (pdf) (code)

GPU-acceleration for Large-scale Tree Boosting, Huan Zhang, Si Si, Cho-Jui Hsieh. SysML Conference, 2018. (pdf) (code)

Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent, Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, and Ji Liu. To appear in Advances in Neural Information Processing Systems (NIPS), 2017. (Oral paper) (pdf)

Gradient Boosted Decision Trees for High Dimensional Sparse Output, Si Si, Huan Zhang, Sathiya Keerthi, Dhruv Mahajan, Inderjit Dhillon, Cho-Jui Hsieh. In International Conference on Machine Learning (ICML) 34, 2017. (pdf)

HogWild++: A New Mechanism for Decentralized Asynchronous Stochastic Gradient Descent, Huan Zhang, Cho-Jui Hsieh and Venkatesh Akella. In IEEE International Conference on Data Mining (ICDM), 2016. (pdf) (code)

Fixing the Convergence Problems in Parallel Asynchronous Dual Coordinate Descent, Huan Zhang, Cho-Jui Hsieh. In IEEE International Conference on Data Mining (ICDM), 2016. (pdf) (code)

Sublinear Time Orthogonal Tensor Decomposition, Zhao Song, David P. Woodruff and Huan Zhang. In Advances in Neural Information Processing Systems (NIPS), 2016. (pdf) (code)

A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order, Xiangru Lian, Huan Zhang, Cho-Jui Hsieh, Yijun Huang, Ji Liu. In Advances in Neural Information Processing Systems (NIPS), 2016. (pdf)

Field demonstration of 100-Gb/s real-time coherent optical OFDM detection, by Noriaki Kaneda, Timo Pfau, Huan Zhang et. al., in Journal of Lightwave Technology, Vol. 33, No. 7, April 1 2015.

Burst Mode Processing: An Architectural Framework for Improving Performance in Future Chip Microprocessors, by Huan Zhang, Rajeevan Amirtharajah, Christopher Nitta, Matthew Farrens and Venkatesh Akella, in Workshop on Workshop on Managing Overprovisioned Systems, Co-located with ASPLOS-19, April 2014.

HySIM: Towards a Scalable, Accurate and Fast Simulator for Manycore Processors by Kramer Straube, Huan Zhang, Christopher Nitta, Matthew Farrenss and Venkatesh Akella, in 3rd Workshop on the Intersections of Computer Architecture and Reconfigurable Logic, Co-located with MICRO-46, December 2013.

Spectral and Spatial 2D Fragmentation-Aware Routing and Spectrum Assignment Algorithms in Elastic Optical Networks, by Yawei Yin, Huan Zhang, Mingyang Zhang, Ming Xia, Zuqing Zhu, S. Dahlfort and S.J.B Yoo, in IEEE/OSA Journal of Optical Communications and Networking, Vol. 5, No. 10, October 2013.


“Blind Guide Device Based on the Smart Phone”, China Patent ZL.2010 2 0516516.9. Yang Yang, Huan Zhang, Ding Zhao, Li Chen et al. Issued on July, 20, 2011. (pdf)

Some Fun Undergraduate Projects

I did some interesting projects during my undergraduate years. They have become non-relevant to my current research but I am still keeping links and descriptions here because I do occasionally get emails asking some details. And, they are fun!

Click here for a list of my previous projects.


Email:ecezhang AT ucdavis DOT edu

2306 Academic Surge
University of California, Davis
One Shields Avenue
Davis, CA, 95616