I am a Computer Science Ph.D. candidate at the University of Missouri. I obtained my B.S. and M.S. in Electrical Engineering at University of Xiamen, China. I was a software intern at Xiamen Weixintai Technology Co.,Ltd. During college, I was a member of the RCS Robot Team of Xiamen University, where I met many talent people and established my future direction.

My current research interests include machine learning, deep learning, computational biology. I have developed protein complex distance predition tool CDPred, protein intra-chain distance prediction tool DeepDist, and protein secondary structure prediction tool DNSS2. In addition, I have a strong interest in computer vision and machine vision, and I have some experience in the design and production of robots.

Selected Publications

1. Guo, Z., Liu, J., Skolnick, J. and Cheng, J., 2022. Prediction of inter-chain distance maps of protein complexes with 2D attention-based deep neural networks. Nature Communications, 13(1), pp.1-10.
2. Guo, Z., Wu, T., Liu, J., Hou, J. and Cheng, J., 2021. Improving deep learning-based protein distance prediction in CASP14. Bioinformatics, 37(19), pp.3190-3196.
3. Guo, Z., Wu, T., Hou, J. and Cheng, J., 2021. DeepDist: real-value inter-residue distance prediction with deep residual convolutional network. BMC bioinformatics, 22(1), pp.1-17.
4. Guo, Z., Hou, J. and Cheng, J., 2021. DNSS2: improved ab initio protein secondary structure prediction using advanced deep learning architectures. Proteins: Structure, Function, and Bioinformatics, 89(2), pp.207-217.
5. Guo, Z., Ye, S., Wang, Y. and Lin, C., 2017, July. Resistance welding spot defect detection with convolutional neural networks. In International Conference on Computer Vision Systems (pp. 169-174). Springer, Cham.