[1] Huaipan Jiang, Jian Wang, Weilin Cong, Yihe Huang, Morteza Ramezani, Anup Sarma, Nikolay V Dokholyan, Mehrdad Mahdavi, and Mahmut T. Kandemir. Predicting Protein–Ligand Docking Structure with Graph Neural Network. Journal of Chemical Information and Modeling 2022
[2] Anup Sarma, Sonali Singh, Huaipan Jiang, Rui Zhang, Mahmut Kandemir, and Chita Das. Structured
in space, randomized in time: Leveraging dropout in rnns for efficient training. Advances in Neural
Information Processing Systems, 34, 2021
[3] Huaipan Jiang, Haibo Zhang, Xulong Tang, Vineetha Govindaraj, Jack Sampson, Mahmut Taylan Kandemir, and Danfeng Zhang. Fluid: a framework for approximate concurrency via controlled dependency relaxation. In Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation (PLDI), pages 252–267, 202
[4] Huaipan Jiang, Anup Sarma, Mengran Fan, Jihyun Ryoo, Meenakshi Arunachalam, Sharada Naveen,and Mahmut T Kandemir. Morphable convolutional neural network for biomedical image segmentation.In2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), pages 1522–1525. IEEE,2021
[5] Mengran Fan, Jian Wang, Huaipan Jiang, Yilin Feng, Mehrdad Mahdavi, Kamesh Madduri,Mahmut T. Kandemir, and Nikolay V. Dokholyan. Gpu-accelerated flexible molecular docking.The Journal of Physical Chemistry B, 125(4):1049–1060, 2021. PMID
[6] Huaipan Jiang, Mengran Fan, Jian Wang, Anup Sarma, Shruti Mohanty, Nikolay V Dokholyan, MehrdadMahdavi, and Mahmut T Kandemir. Guiding conventional protein–ligand docking software withconvolutional neural networks.Journal of Chemical Information and Modeling, 2020.
[7] Jihyun Ryoo, Mengran Fan, Xulong Tang, Huaipan Jiang, Meena Arunachalam, Sharada Naveen, andMahmut T Kandemir. Architecture-centric bottleneck analysis for deep neural network applications. In2019 IEEE 26th International Conference on High Performance Computing, Data, and Analytics (HiPC),pages 205–214. IEEE, 2019.
[8] Anup Sarma, Huaipan Jiang, Ashutosh Pattnaik, Jagadish Kotra, Mahmut Taylan Kandemir, andChita R Das. Cash: compiler assisted hardware design for improving dram energy efficiency in cnninference. InProceedings of the International Symposium on Memory Systems, pages 396–407. ACM, 2019.
[9] Huaipan Jiang, Anup Sarma, Jihyun Ryoo, Jagadish B Kotra, Meena Arunachalam, Chita R Das, and
Mahmut T Kandemir. A learning-guided hierarchical approach for biomedical image segmentation. In 2018 31st IEEE International System-on-Chip Conference (SOCC), pages 227-232, Sep. 2018.
[10] Sumitha George, Minli Julie Liao, Huaipan Jiang, Jagadish B Kotra, Mahmut Kandemir, Jack Sampson,
and Vijaykrishnan Narayanan. Mdacache: Caching for multi-dimensional-access memories. In 51st Annual
IEEE/ACM International Symposium on Microarchitecture, MICRO 2018, pages 841–854. IEEE Computer
Society, 2018.
[11] Xulong Tang, Ashutosh Pattnaik, Huaipan Jiang, Onur Kayiran, Adwait Jog, Sreepathi Pai, Mohamed
Ibrahim, Mahmut T Kandemir, and Chita R Das. Controlled kernel launch for dynamic parallelism in gpus.
In High Performance Computer Architecture (HPCA), 2017 IEEE International Symposium on, pages
649–660. IEEE, 2017.
[12] Biaofei Xu, Yuqing Zhu, Donghyun Kim, Deying Li, Huaipan Jiang, and Alade O Tokuta. Strengthening
barrier-coverage of static sensor network with mobile sensor nodes. Wireless Networks, 22(1):1–10, 2016.
[13] Haoyu Cheng, Huaipan Jiang, Jiaoyun Yang, Yun Xu, and Yi Shang. Bitmapper: an efficient all-mapper
based on bit-vector computing. BMC bioinformatics, 16(1):192, 2015.
[14] Biaofei Xu, Donghyun Kim, Deying Li, Joonglyul Lee, Huaipan Jiang, and Alade O Tokuta. Fortifying
barrier-coverage of wireless sensor network with mobile sensor nodes. In International Conference on
Wireless Algorithms, Systems, and Applications, pages 368–377. Springer, 2014.