Publications

Conference/Workshop Papers

  1. Xiaotang Wang, Yongchao Liu, Yun Zhu, Haizhou Shi, Chuntao Hong: Graph triple attention networks: a decoupled perspective. 2025 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2025), 2024, accepted.
  2. Ting Li, Chunqi Wu, Yang Liu, Zhao Li, Chuan Zhou, Chenhao Qiu, Hongyang Chen, Yongchao Liu, Peng Du and Chuntao Hong: Unsupervised pre-trained social networks for e-commerce community detection. 2024 IEEE International Conference on High Performance Computing and Communications (HPCC 2024), 2024.
  3. Boci Peng, Yongchao Liu, Xiaohe Bo, Sheng Tian, Baokun Wang, Chuntao Hong, Yan Zhang: "Subgraph retrieval enhanced by graph-text alignment for commonsense question answering." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2024 (ECML PKDD 2024), 2024.
  4. Sheng Tian, Xintan Zeng, Yifei Hu, Baokun Wang, Yongchao Liu, Yue Jin, Changhua Meng, Chuntao Hong, Tianyi Zhang, Weiqiang Wang: "GraphRPM: risk pattern mining on industrial large attributed graphs." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2024 (ECML PKDD 2024), 2024.
  5. Pengyu Qiu, Yongchao Liu, Xintan Zeng: "DiVerFed: distribution-aware vertical federated learning for missing information". The 17th International Conference on Knowledge Science, Engineering and Management (KSEM 2024), 2024 (Best Student Paper Award).
  6. Yue Jin, Sheng Tian, Yongchao Liu, Chuntao Hong: "GraphGen: a distributed graph sample generation framework on industry-scale graphs". The European Conference on Computer Systems (EuroSys 2024), 2024 (poster track).
  7. Pengyu Qiu, Yuwen Pu, Yongchao Liu, Wenyan Liu, Yun Yue, Xiaowei Zhu, Lichun Li, Jinbao Li, Shouling Ji: "Integer is Enough: when vertical federated learning meets rounding". 38th AAAI Conference on Artificial Intelligence (AAAI 2024), 38(13), 14704-14712, 2024.
  8. Yun Yue, Zhiling Ye, Jiadi Jiang, Yongchao Liu, Ke Zhang: "AGD: an auto-switchable optimizer using stepwise gradient difference for preconditioning matrix". 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023
  9. Yice Luo, Guannan Wang, Yongchao Liu, Jiaxin Yue, Weihong Cheng and Binjie Fei: "FAF: a risk detection framework on industry-scale graphs". 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023), 2023, pp. 4717–4723.
  10. Yue Jin, Chengying Huan, Heng Zhang, Yongchao Liu, Shuaiwen Leon Song, Rui Zhao, Yao Zhang, Changhua He, Wenguang Chen: "G-Sparse: compiler-driven acceleration for generalized sparse computation for graph neural networks on modern GPUs". 32nd International Conference on Parallel Architectures and Compilation Techniques (PACT 2023), 2023, pp. 137-149.
  11. Yun Yue, Jiadi Jiang, Zhiling Ye, Gao Ning, Yongchao Liu, Ke Zhang: "Sharpness-aware minimization revisited: weighted sharpness as a regularization term". 2023 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023, pp. 3185–3194 (research track)
  12. Yue Jin, Yongchao Liu: "GPC: compiler-based optimization for sparse computations in graph neural networks". The European Conference on Computer Systems (EuroSys 2023), 2023 (poster track).
  13. Yuchen Zhou, Yanan Cao, Yongchao Liu, Yanmin Shang, Peng Zhang, Zheng Lin, Yun Yue, Baokun Wang, Xing Fu and Weiqiang Wang: "Multi-aspect heterogeneous graph augmentation". The 2023 ACM Web Conference (WWW 2023), 2023, pp. 39-48.
  14. Chengying Huan, Shuaiwen Leon Song, Santosh Pandey, Hang Liu, Yongchao Liu, Baptiste Lepers, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu: "TEA: a general-purpose temporal graph random walk engine". The European Conference on Computer Systems (EuroSys 2023), 2023, pp. 182-198.
  15. Chengying Huan, Shuaiwen Leon Song, Yongchao Liu, Heng Zhang, Hang Liu, Charles He, Kang Chen, Jinlei Jiang, Yongwei Wu: "T-GCN: a sampling based streaming graph neural network system with hybrid architecture". 31st International Conference on Parallel Architectures and Compilation Techniques (PACT 2022), 2022, pp. 69–82.
  16. Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, Shuaiwen Leon Song: "Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator system". International Conference on Supercomputing 2022 (ICS 2022), 2022, 11:14.
  17. Chengying Huan, Hang Liu, Mengxing Liu, Yongchao Liu, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu, Shuaiwen Leon Song: "TeGraph: a novel general-purpose temporal graph computing engine". 38th International Conference on Data Engineering (ICDE 2022), 2022, pp. 578-592.
  18. Yang Gao, Peng Zhang, Zhao Li, Chuan Zhou, Hong Yang, Yongchao Liu, and Yue Hu: "Heterogeneous graph neural architecture search". IEEE International Conference on Data Mining (ICDM 2021), 2021, pp. 1066-1071
  19. Yun Yue, Yongchao Liu, Suo Tong, Minghao Li, Zhen Zhang, Chunyang Wen, Huanjun Bao, Lihong Gu, Jinjie Gu and Yixiang Mu: "Adaptive optimizers with sparse group lasso for neural networks in CTR prediction". The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2021), 2021, pp. 314–329 .
  20. Houyi Li, Zhihong Chen, Chenliang Li, Rong Xiao, Hongbo Deng, Peng Zhang, Yongchao Liu and Haihong Tang: "Path-based deep network for candidate item matching in recommenders". 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), 2021, pp. 1493–1502.
  21. Yue Jin, Yongchao Liu, Yong Chen, Rui Zhao, Yao Zhang: "Model-based cost estimation and its application in deep learning operation optimizations". GPU Technology Conference 2020 (GTC 2020), 2020, China (talk given by Yue Jin).
  22. Yongchao Liu, Yue Jin, Yong Chen, Teng Teng, Hang Ou, Rui Zhao, Yao Zhang: "Woodpecker-DL: an efficient compiler for accelerating deep learning on heterogeneous computing architectures". GPU Technology Conference 2019 (GTC 2019), 2019, China (talk given by Yong Chen).
  23. Shuozhi Xu, Thomas G. Payne, Hao Chen, Yongchao Liu, Liming Xiong, Youping Chen, David L. McDowell: "PyCAC: the concurrent atomistic-continuum simulation environment”. 2018 TMS Annual Meeting & Exhibition (TMS 2018)
  24. Yuandong Chan, Kai Xu, Haidong Lan, Weiguo Liu, Yongchao Liu and Bertil Schmidt: ”PUNAS: a parallel ungapped-alignment-featured seed verification for next-generation sequencing read alignment”. 31st IEEE International Parallel and Distributed Processing Symposium (IPDPS 2017), 2017, pp. 52-61.
  25. Haidong Lan, Weiguo Liu, Yongchao Liu and Bertil Schmidt: ”SWhybrid: a hybrid parallel framework for large-scale protein sequence database search”. 31st IEEE International Parallel and Distributed Processing Symposium (IPDPS 2017), 2017, pp. 42-51.
  26. Tony Pan, Patrick Flick, Chirag Jain, Yongchao Liu and Srinivas Aluru: "Kmerind: A flexible parallel library for k-mer indexing of biological sequences on distributed memory systems". 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2016), 2016, pp. 422-433
  27. Yongchao Liu, Tony Pan, and Srinivas Aluru: "Parallel pairwise correlation computation on Intel Xeon Phi clusters". 28th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2016), 2016, pp. 141-149
  28. Yongchao Liu, Martin Loewer, Srinivas Aluru, Bertil Schmidt: "SNVSniffer: an integrated caller for germline and somatic SNVs based on Bayesian models". 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2015), 2015, pp. 83-90.
  29. Sharma V. Thankachan, Sriram P. Chockalingam, Yongchao Liu, Ambujam Krishnan, Srinivas Aluru: "A greedy alignment-free distance estimator for phylogenetic inference (extended abstract)". 5th IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS 2015), 2015, pp. 1-1.
  30. Yongchao Liu and Bertil Schmidt: "LightSpMV: faster CSR-based sparse matrix-vector multiplication on CUDA-enabled GPUs". 26th IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP 2015), 2015, pp. 82-89 (Best Paper Award)
  31. Yongchao Liu, Jorge González-Domínguez, Bertil Schmidt: "Faster compressed sparse row (CSR)-based sparse matrix-vector multiplication using CUDA". GPU Technology Conference 2015 (GTC 2015), San Jose, USA, 2015
  32. Tuan Tu Tran, Simon Schindel, Yongchao Liu and Bertil Schmidt: "Bit-Parallel approximate pattern matching on the Xeon Phi coprocessor". 26th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2014), 2014, pp. 81-88
  33. Yongchao Liu, Tuan-Tu Tran, Felix Lauenroth and Bertil Schmidt: "SWAPHI-LS: Smith-Waterman algorithm on Xeon Phi coprocessors for long DNA sequences". 2014 IEEE International Conference on Cluster Computing (Cluster 2014), 2014, pp. 257-265 (Best Paper Award Recommendation)
  34. Yongchao Liu and Bertil Schmidt: "SWAPHI: Smith-Waterman protein database search on Xeon Phi coprocessors". 25th IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP 2014), 2014, pp. 184-185 [full version at arXiv]
  35. Yongchao Liu and Bertil Schmidt: "CUSHAW Software Package: harnessing CUDA-enabled GPUs for next generation sequencing read alignment". GPU Technology Conference 2014 (GTC 2014), San Jose, USA, 2014
  36. Yongchao Liu and Bertil Schmidt: "Faster GPU-accelerated Smith-Waterman algorithm with alignment backtracking for short DNA sequences". 10th International Conference on Parallel Processing and Applied Mathematics (PPAM 2013), appear in Lecture Notes in Computer Science 8385, pp. 247-257
  37. Yongchao Liu and Bertil Schmidt: "Long read alignment based on maximal exact match seeds". 11th European Conference on Computational Biology (ECCB 2012), Basel, Switzerland (also published in the Bioinformatics journal)
  38. Yongchao Liu and Bertil Schmidt: Evaluation of GPU-based seed generation for computational genomics using Burrows-Wheeler transform". 26th IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW 2012), 684-690
  39. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "A fast CUDA compatible short read aligner to large genomes". GPU Technology Conference 2012 (GTC 2012), San Jose, USA, 2012
  40. Weiguo Liu, Bertil Schmidt, Yongchao Liu, and Wolfgang Müller-Wittig: "Mapping of the BLASTP algorithm onto GPU clusters". 17th IEEE International Conference on Parallel and Distributed Systems (ICPADS 2011), 2011, 236-243
  41. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "An ultrafast scalable many-core motif discovery algorithm for multiple GPUs". 25th IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW 2011), 428-434
  42. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "MSA-CUDA: multiple sequence alignment on graphics processing units with CUDA". 20th IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP 2009), 2009, 121-128 (Best Paper Award)
  43. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "Parallel reconstruction of neighbor-Joining trees for large multiple sequence alignments using CUDA". 23th IEEE International Symposium on Parallel and Distributed Processing (IPDPS 2009), 2009, 1-8.

Journal Articles

  1. Li Ma, Yongchao Liu, Xiaofeng Gao, Peng Zhang, Chuntao Hong: "Building robust and trustworthy HGNN models: a learnable threshold approach for node classification". ACM Transactions on Knowledge Discovery from Data (impact factor 4.0), 2024.
  2. Chengying Huan, Yongchao Liu, Heng Zhang, Shiyang Chen, Shuaiwen Leon Song, Yanjun Wu, Hang Liu:"TeGraph+: scalable temporal graph processing enabling flexible edge modifications". IEEE Transactions on Parallel and Distributed Systems (impact factor 5.3), 2024.
  3. Chengying Huan, Yongchao Liu, Heng Zhang, Shuaiwen Song, Santosh Pandey, Shiyang Chen, Xiangfei Fang, Yue Jin, Baptiste Lepers, Hang Liu, Yanjun Wu: "TEA+: a novel temporal graph random walk engine with hybrid storage architecture." ACM Transactions on Architecture and Code Optimization (impact factor 1.6), 2024.
  4. Xiaowei Zhu, Zhisong Fu, Zhenxuan Pan, Jin Jiang, Chuntao Hong, Yongchao Liu, Yang Fang, Wenguang Chen, Changhua He: "Taking the Pulse of Financial Activities with Online Graph Processing". ACM SIGOPS Operating Systems Review, vol 55, no.1, 2021
  5. Tony C Pan, Patrick Flick, Chirag Jain, Yongchao Liu and Srinivas Aluru: "Kmerind: a exible parallel library for k-mer indexing of biological sequences on distributed memory systems". IEEE/ACM Transactions on Computational Biology and Bioinformatics (impact factor 1.955), 2019, 16(4):1117-1131.
  6. Shuozhi Xu, Thomas Payne, Hao Chen, Yongchao Liu, Liming Xiong, Youping Chen and David McDowell: "PyCAC: The concurrent atomistic-continuum simulator with a Python scripting interface". Journal of Materials Research (impact factor 1.673), 2018, 33(7):857-871.
  7. Yongchao Liu and Bertil Schmidt: "LightSpMV: faster CUDA-compatible sparse matrix-vector multiplication using compressed sparse rows". Journal of Signal Processing Systems (impact factor 0.508), 2018, 90(1):69-86.
  8. Yongchao Liu, Fabian Ripp, Rene Koeppe, Hanno Schmidt, Lukas Hellmann, Mathias Weber, Christopher Felix Krombholz, Bertil Schmidt and Thomas Hankeln: "AFS: identification and quantification of species composition by metagenomic sequencing". Bioinformatics (impact factor 7.307), 2017, 33 (9): 1396-1398.
  9. Sharma V. Thankachan, Sriram P. Chockalingam, Yongchao Liu, Ambujam Krishnan, Srinivas Aluru: "A greedy alignment-free distance estimator for phylogenetic inference". BMC Bioinformatics (impact factor 2.58), 2017, 18(Suppl 8):238.
  10. Jorge Gonzalez-Dominguez, Yongchao Liu, Juan Tourino and Bertil Schmidt: "MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems". Bioinformatics (impact factor 5.766), 2016, 32(24): 3826-3828
  11. Yongchao Liu, Martin Loewer, Srinivas Aluru and Bertil Schmidt: "SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations". BMC Systems Biology (impact factor 2.435), 2016, 10(suppl 2): 47
  12. Jorge González-Domínguez, Yongchao Liu, Bertil Schmidt: "Parallel and scalable short-read alignment on multi-core clusters using UPC++". PLoS One (impact factor 3.234), 2016, 11(1): e0145490.
  13. Tuan Tu Tran, Yongchao Liu, Bertil Schmidt: "Bit-parallel approximate pattern matching: Kepler GPU versus Xeon Phi". Parallel Computing (impact factor 1.511), 2016, 54: 128-138.
  14. Sharma V. Thankachan, Sriram P. Chockalingam, Yongchao Liu, Alberto Apostolico and Srinivas Aluru: "ALFRED: a practical method for alignment-free distance computation". Journal of Computational Biology (impact factor 1.737), 2016, 23(6): 452-460
  15. Yongchao Liu, Thomas Hankeln, and Bertil Schmidt: "Parallel and space-efficient construction of Burrows-Wheeler transform and suffix array for big genome data". IEEE Transactions on Computational Biology and Bioinformatics (impact factor 1.536), 2016, 13(3): 592-598.
  16. Yongchao Liu, Bertil Schmidt: "GSWABE: faster GPU-accelerated sequence alignment with optimal alignment retrieval for short DNA sequences". Concurrency and Computation: Practice and Experience (impact factor 0.784), 2015, 27: 958-972
  17. Fabian Ripp, Christopher F Krombholz, Yongchao Liu, Mathias Weber, Anne Sch?fer, Bertil Schmidt, Rene K?ppel and Thomas Hankeln: "All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing". BMC Genomics (impact factor 4.40), 2014, 15:639 [Reported by Austrilian Food News]
  18. Adrianto Wirawan, Robert S Harris, Yongchao Liu, Bertil Schmidt and Jan Schr?der: "HECTOR: A parallel multistage homopolymer spectrum based error corrector for 454 sequencing data." BMC Bioinformatics (impact factor 3.02), 2014, 15:131
  19. Yongchao Liu, Bernt Popp, and Bertil Schmidt: "CUSHAW3: sensitive and accurate base-space and color-space short-read alignment with hybrid seeding." PLOS ONE (impact factor 3.730), 2014, 9(1): e86869
  20. Yongchao Liu and Bertil Schmidt: "CUSHAW2-GPU: empowering faster gapped short-read alignment using GPU computing". IEEE Design & Test (impact factor 1.623), 2014, 31(1): 31-39
  21. Yongchao Liu, Adrianto Wirawan and Bertil Schmidt: "CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions". BMC Bioinformatics (impact factor 3.02), 2013, 14:117.
  22. Yongchao Liu, Jan Schr?der, and Bertil Schmidt: "Musket: a multistage k-mer spectrum based error corrector for Illumina sequence data". Bioinformatics (impact factor 5.323), 2013, 29(3): 308-315
  23. Yongchao Liu and Bertil Schmidt: "Long read alignment based on maximal exact match seeds". Bioinformatics(impact factor 5.468), 2012, 28(18): i318-i324 (also from ECCB 2012)
  24. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows-Wheeler transform". Bioinformatics (impact factor 5.468), 2012, 28(14): 1830-1837
  25. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "Parallelized short read assembly of large genomes using de Bruijn graphs". BMC Bioinformatics (impact factor 3.43), 2011, 12:354
  26. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI". BMC Bioinformatics (impact factor 3.43), 2011, 12:85 [Reported by GenomeWeb]
  27. Lakshmi Kuttippurathu, Michael Hsing, Yongchao Liu, Bertil Schmidt, Douglas L.Maskell, Kyungjoon Lee, Aibin He, William T. Pu, and Sek Won Kong: "CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments". Bioinformatics (impact factor 4.926), 2011, 27(5): 715-717
  28. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "MSAProbs: multiple sequence alignment based on pair hidden Markov models and partition function posterior probabilities". Bioinformatics (impact factor 4.926), 2010, 26(16): 1958 -1964
  29. Yongchao Liu, Bertil Schmidt, and Douglas L. Maskell: "CUDASW++2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions". BMC Research Notes, 2010, 3:93
  30. Yongchao Liu, Bertil Schmidt, Weiguo Liu, and Douglas L. Maskell: "CUDA-MEME: accelerating motif discovery in biological sequences using CUDA-enabled graphics processing units". Pattern Recognition Letters (impact factor 1.559), 2010, 31(14): 2170 - 2177
  31. Yongchao Liu, Douglas L. Maskell, and Bertil Schmidt: "CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units". BMC Research Notes, 2009, 2:73
  32. 李庆诚, 刘永超(Yongchao Liu), 刘嘉鑫: "平台无关的PDF嵌入式高性价比解析器设计与实现(Design and implementation of a platform-independent, high-performance-cost-ratio, embedded PDF format parser*)". 计算机应用(Computer Applications), 2007, 27(z1). [*translated by myself]

Book Chapters

  1. Yongchao Liu and Bertil Schmidt: "CUSHAW Suite: parallel and efficient algorithms for NGS read alignment". Algorithms for Next-Generations Sequencing Data: Techniques, Approaches and Applications, edited by Mourad Elloumi, Springer, 2017.
  2. Yongchao Liu and Bertil Schmidt: "Pairwise DNA sequence alignment optimization". High Performance Parallelism Pearls Volume Two - Multicore and Many-core Programming Approaches, edited by James Reinders and Jim Jeffers, 2015, pp. 43-54
  3. Yongchao Liu and Bertil Schmidt: "Multiple protein sequence alignment with MSAProbs". Methods in Molecular Biology, Edited by David Russell, Springer, 2014, 1079: 211-218
  4. Lukasz Ligowski, Witold Rudnicki, Yongchao Liu, and Bertil Schmidt: "Accurate scanning of sequence databases with the Smith-Waterman algorithm". GPU Computing Gems, Edited by Wen-mei W. Hwu, Elsevier 2011, Pages 155-172
  5. Yongchao Liu, Bertil Schmidt , and Douglas L. Maskell: "Parallel bioinformatics algorithms for CUDA-enabled GPUs". Bioinformatics: High Performance Parallel Computer Architectures, Edited by Bertil Schmidt, CRC Press 2010, Pages 117-137

Technical Reports

  1. Yuwei Hu, Runlin Lei, Xinyi Huang, Zhewei Wei, Yongchao Liu: "Scalable and accurate graph reasoning with LLM-based multi-agents". arXiv:2410.05130, 2024.
  2. Ant Group, and other institutions: "Graph+AI: 大模型浪潮下的图计算", White Paper. 2024.
  3. Boci Peng, Yun Zhu, Yongchao Liu, Xiaohe Bo, Haizhou Shi, Chuntao Hong, Yan Zhang, Siliang Tang: "Graph Retrieval-Augmented Generation: A Survey". https://arxiv.org/abs/2408.08921, 2024.
  4. Ant Group, Tsinghua University, Beijing University of Posts and Telecommunications, Sun Yat-sen University, Shanghai Jiao Tong University, Fudan University, Zhijiang Laboratory, Alibaba Group:" 图风控行业技术报告". 2023
  5. Qinkai Zheng, Houyi Li, Peng Zhang, Zhixiong Yang, Guowei Zhang, Xintan Zeng, Yongchao Liu: "GIPA: general information propagation algorithm for graph learning. https://arxiv.org/abs/2105.06035, 2021
  6. Yongchao Liu, Houyi Li, Guowei Zhang, Xintan Zeng, Yongyong Li, Bin Huang, Peng Zhang, Zhao Li, Xiaowei Zhu, Changhua He, Wenguang Chen: "GraphTheta: A distributed graph neural network learning system with flexible training strategy". arXiv:2104.10569, 2021
  7. Yongchao Liu, Yue Jin, Yong Chen, Teng Teng, Hang Ou, Rui Zhao, Yao Zhang: "Woodpecker-DL: Accelerating Deep Neural Networks via Hardware-Aware Multifaceted Optimizations". arXiv:2008.04567, 2020.
  8. Yongchao Liu, Tony Pan, Oded Green and Srinivas Aluru: "Parallelized Kendall's tau coefficient computation via SIMD vectorized sorting on many-integrated-core processors". arXiv:1704.03767, 2017.
  9. Yongchao Liu and Srinivas Aluru: "LightScan: faster scan primitive on CUDA compatible manycore processors". arXiv:1604.04815 [Cs.DC], 2016.
  10. Yongchao Liu: "Research statement for assistant professorship application". ResearchGate, 2016, doi: 10.13140/RG.2.2.28828.90243/1
  11. Yongchao Liu: "OpenGraphAssembly: abstract, modularize and parallelize fundamental building blocks for graph-based genome assembly". ResearchGate, 2015, doi: 10.13140/RG.2.2.11212.825
  12. Yongchao Liu, Bernt Popp, and Bertil Schmidt: "High-speed and accurate color-space short-read alignment with CUSHAW2". arXiv:1304.4766 [q-bio.GN], 2013