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  2025 (4)
Extrapolability improvement of machine learning-based evapotranspiration models via domain-adversarial neural networks. Shi, H.; and Cai, X. Environ. Model. Softw., 187: 106383. 2025.
Extrapolability improvement of machine learning-based evapotranspiration models via domain-adversarial neural networks [link]Paper   doi   link   bibtex  
Shadow Detection in Remote Sensing Images Based on Multibranch Feature Aggregation and Channel-Spatial Attention. Chang, X.; Shi, H.; Zhang, T.; Jin, H.; and Xu, A. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 18: 2618–2630. 2025.
Shadow Detection in Remote Sensing Images Based on Multibranch Feature Aggregation and Channel-Spatial Attention [link]Paper   doi   link   bibtex  
AIBrix: Towards Scalable, Cost-Effective Large Language Model Inference Infrastructure. Shan, J.; Gupta, V.; Xu, L.; Shi, H.; Zhang, J.; Wang, N.; Xu, L.; Kang, R.; Liu, T.; Zhang, Y.; Zhu, Y.; Jin, S.; Lim, G.; Chen, B.; Chen, Z.; Liu, X.; Chen, X.; Yin, K.; Chung, C.; Jiang, C.; Lu, Y.; Chen, J.; Lin, C.; Xiang, W.; Shi, R.; and Xie, L. CoRR, abs/2504.03648. 2025.
AIBrix: Towards Scalable, Cost-Effective Large Language Model Inference Infrastructure [link]Paper   doi   link   bibtex  
PolyServe: Efficient Multi-SLO Serving at Scale. Zhu, K.; Shi, H.; Xu, L.; Shan, J.; Krishnamurthy, A.; Kasikci, B.; and Xie, L. CoRR, abs/2507.17769. 2025.
PolyServe: Efficient Multi-SLO Serving at Scale [link]Paper   doi   link   bibtex  
  2024 (4)
Fisher discrimination multiple kernel dictionary learning for robust identification of nonlinear features in machinery health monitoring. Zhang, X.; Yang, T.; Long, H.; Shi, H.; Wang, J.; and Yang, L. Inf. Sci., 677: 120862. 2024.
Fisher discrimination multiple kernel dictionary learning for robust identification of nonlinear features in machinery health monitoring [link]Paper   doi   link   bibtex  
Potential of Domain Adaptation in Machine Learning in Ecology and Hydrology to Improve Model Extrapolability. Shi, H. CoRR, abs/2403.11331. 2024.
Potential of Domain Adaptation in Machine Learning in Ecology and Hydrology to Improve Model Extrapolability [link]Paper   doi   link   bibtex  
Extrapolability Improvement of Machine Learning-Based Evapotranspiration Models via Domain-Adversarial Neural Networks. Shi, H. CoRR, abs/2406.00805. 2024.
Extrapolability Improvement of Machine Learning-Based Evapotranspiration Models via Domain-Adversarial Neural Networks [link]Paper   doi   link   bibtex  
Approaches for enhancing extrapolability in process-based and data-driven models in hydrology. Shi, H. CoRR, abs/2408.07071. 2024.
Approaches for enhancing extrapolability in process-based and data-driven models in hydrology [link]Paper   doi   link   bibtex  
  2023 (3)
Krypton: Real-time Serving and Analytical SQL Engine at ByteDance. Chen, J.; Shi, R.; Chen, H.; Zhang, L.; Li, R.; Ding, W.; Fan, L.; Wang, H.; Xiong, M.; Chen, Y.; Dong, B.; Guo, K.; Lin, Y.; Liu, X.; Shi, H.; Wang, P.; Wang, Z.; Yang, Y.; Zhao, J.; Zhou, D.; Zuo, Z.; and Liang, Y. Proc. VLDB Endow., 16(12): 3528–3542. 2023.
Krypton: Real-time Serving and Analytical SQL Engine at ByteDance [pdf]Paper   doi   link   bibtex  
Adaptive Fast Chirplet Transform and Its Application Into Rolling Bearing Fault Diagnosis Under Time-Varying Speed Condition. Qin, Y.; Yang, R.; Shi, H.; He, B.; and Mao, Y. IEEE Trans. Instrum. Meas., 72: 1–12. 2023.
Adaptive Fast Chirplet Transform and Its Application Into Rolling Bearing Fault Diagnosis Under Time-Varying Speed Condition [link]Paper   doi   link   bibtex  
Accelerating Cloud-Native Databases with Distributed PMem Stores. Sun, J.; Ma, H.; Zhang, L.; Liu, H.; Shi, H.; Luo, S.; Wu, K.; Bruhwiler, K.; Zhu, C.; Nie, Y.; Chen, J.; Zhang, L.; and Liang, Y. In 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023, pages 3043–3057, 2023. IEEE
Accelerating Cloud-Native Databases with Distributed PMem Stores [link]Paper   doi   link   bibtex  
  2022 (1)
A Global Meta-Analysis of Soil Salinity Prediction Integrating Satellite Remote Sensing, Soil Sampling, and Machine Learning. Shi, H.; Hellwich, O.; Luo, G.; Chen, C.; He, H.; Ochege, F. U.; de Voorde, T. V.; Kurban, A.; and Maeyer, P. D. IEEE Trans. Geosci. Remote. Sens., 60: 1–15. 2022.
A Global Meta-Analysis of Soil Salinity Prediction Integrating Satellite Remote Sensing, Soil Sampling, and Machine Learning [link]Paper   doi   link   bibtex  
  2021 (5)
Analysis of the Impacts of Environmental Factors on Rat Hole Density in the Northern Slope of the Tienshan Mountains with Satellite Remote Sensing Data. Shi, H.; Pan, Q.; Luo, G.; Hellwich, O.; Chen, C.; de Voorde, T. V.; Kurban, A.; Maeyer, P. D.; and Wu, S. Remote. Sens., 13(22): 4709. 2021.
Analysis of the Impacts of Environmental Factors on Rat Hole Density in the Northern Slope of the Tienshan Mountains with Satellite Remote Sensing Data [link]Paper   doi   link   bibtex  
Assessing Satellite, Land Surface Model and Reanalysis Evapotranspiration Products in the Absence of In-Situ in Central Asia. Ochege, F. U.; Shi, H.; Li, C.; Ma, X.; Igboeli, E. E.; and Luo, G. Remote. Sens., 13(24): 5148. 2021.
Assessing Satellite, Land Surface Model and Reanalysis Evapotranspiration Products in the Absence of In-Situ in Central Asia [link]Paper   doi   link   bibtex  
An Improved Viterbi Algorithm for Adaptive Instantaneous Angular Speed Estimation and Its Application Into the Machine Fault Diagnosis. Shi, H.; Qin, Y.; Wang, Y.; Bai, H.; and Zhou, X. IEEE Trans. Instrum. Meas., 70: 1–11. 2021.
An Improved Viterbi Algorithm for Adaptive Instantaneous Angular Speed Estimation and Its Application Into the Machine Fault Diagnosis [link]Paper   doi   link   bibtex  
Aging Assessment of Oil-Paper Insulation Based on Visional Recognition of the Dimensional Expanded Raman Spectra. Song, R.; Chen, W.; Yang, D.; Shi, H.; Zhang, R.; and Wang, Z. IEEE Trans. Instrum. Meas., 70: 1–10. 2021.
Aging Assessment of Oil-Paper Insulation Based on Visional Recognition of the Dimensional Expanded Raman Spectra [link]Paper   doi   link   bibtex  
HatRPC: hint-accelerated thrift RPC over RDMA. Li, T.; Shi, H.; and Lu, X. In de Supinski, B. R.; Hall, M. W.; and Gamblin, T., editor(s), International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2021, St. Louis, Missouri, USA, November 14-19, 2021, pages 36, 2021. ACM
HatRPC: hint-accelerated thrift RPC over RDMA [link]Paper   doi   link   bibtex  
  2020 (2)
CirroData: Yet Another SQL-on-Hadoop Data Analytics Engine with High Performance. Jin, Z.; Shi, H.; Hu, Y.; Zha, L.; and Lu, X. J. Comput. Sci. Technol., 35(1): 194–208. 2020.
CirroData: Yet Another SQL-on-Hadoop Data Analytics Engine with High Performance [link]Paper   doi   link   bibtex  
INEC: fast and coherent in-network erasure coding. Shi, H.; and Lu, X. In Cuicchi, C.; Qualters, I.; and Kramer, W. T., editor(s), Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2020, Virtual Event / Atlanta, Georgia, USA, November 9-19, 2020, pages 66, 2020. IEEE/ACM
INEC: fast and coherent in-network erasure coding [link]Paper   doi   link   bibtex  
  2019 (3)
UMR-EC: A Unified and Multi-Rail Erasure Coding Library for High-Performance Distributed Storage Systems. Shi, H.; Lu, X.; Shankar, D.; and Panda, D. K. In Weissman, J. B.; Butt, A. R.; and Smirni, E., editor(s), Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2019, Phoenix, AZ, USA, June 22-29, 2019, pages 219–230, 2019. ACM
UMR-EC: A Unified and Multi-Rail Erasure Coding Library for High-Performance Distributed Storage Systems [link]Paper   doi   link   bibtex   1 download  
An online intelligent vehicle routing and scheduling approach for B2C e-commerce urban logistics distribution. Shi, H.; Sun, L.; Teng, Y.; and Hu, X. In Rudas, I. J.; Csirik, J.; Toro, C.; Botzheim, J.; Howlett, R. J.; and Jain, L. C., editor(s), Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 23rd International Conference KES-2019, Budapest, Hungary, 4-6 September 2019, volume 159, of Procedia Computer Science, pages 2533–2542, 2019. Elsevier
An online intelligent vehicle routing and scheduling approach for B2C e-commerce urban logistics distribution [link]Paper   doi   link   bibtex  
TriEC: tripartite graph based erasure coding NIC offload. Shi, H.; and Lu, X. In Taufer, M.; Balaji, P.; and Peña, A. J., editor(s), Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2019, Denver, Colorado, USA, November 17-19, 2019, pages 44:1–44:34, 2019. ACM
TriEC: tripartite graph based erasure coding NIC offload [link]Paper   doi   link   bibtex   1 download  
  2018 (4)
DLoBD: A Comprehensive Study of Deep Learning over Big Data Stacks on HPC Clusters. Lu, X.; Shi, H.; Biswas, R.; Javed, M. H.; and Panda, D. K. IEEE Trans. Multi Scale Comput. Syst., 4(4): 635–648. 2018.
DLoBD: A Comprehensive Study of Deep Learning over Big Data Stacks on HPC Clusters [link]Paper   doi   link   bibtex  
EC-Bench: Benchmarking Onload and Offload Erasure Coders on Modern Hardware Architectures. Shi, H.; Lu, X.; and Panda, D. K. In Zheng, C.; and Zhan, J., editor(s), Benchmarking, Measuring, and Optimizing - First BenchCouncil International Symposium, Bench 2018, Seattle, WA, USA, December 10-13, 2018, Revised Selected Papers, volume 11459, of Lecture Notes in Computer Science, pages 215–230, 2018. Springer
EC-Bench: Benchmarking Onload and Offload Erasure Coders on Modern Hardware Architectures [link]Paper   doi   link   bibtex  
Spark-uDAPL: Cost-Saving Big Data Analytics on Microsoft Azure Cloud with RDMA Networks\(^\mbox*\). Lu, X.; Shankar, D.; Shi, H.; and Panda, D. K. In Abe, N.; Liu, H.; Pu, C.; Hu, X.; Ahmed, N. K.; Qiao, M.; Song, Y.; Kossmann, D.; Liu, B.; Lee, K.; Tang, J.; He, J.; and Saltz, J. S., editor(s), IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018, pages 321–326, 2018. IEEE
Spark-uDAPL: Cost-Saving Big Data Analytics on Microsoft Azure Cloud with RDMA Networks\(^\mbox*\) [link]Paper   doi   link   bibtex  
High-Performance Multi-Rail Erasure Coding Library over Modern Data Center Architectures: Early Experiences. Shi, H.; Lu, X.; Shankar, D.; and Panda, D. K. In Proceedings of the ACM Symposium on Cloud Computing, SoCC 2018, Carlsbad, CA, USA, October 11-13, 2018, pages 530–531, 2018. ACM
High-Performance Multi-Rail Erasure Coding Library over Modern Data Center Architectures: Early Experiences [link]Paper   doi   link   bibtex  
  2017 (2)
Performance characterization and acceleration of big data workloads on OpenPOWER system. Lu, X.; Shi, H.; Shankar, D.; and Panda, D. K. In Nie, J.; Obradovic, Z.; Suzumura, T.; Ghosh, R.; Nambiar, R.; Wang, C.; Zang, H.; Baeza-Yates, R.; Hu, X.; Kepner, J.; Cuzzocrea, A.; Tang, J.; and Toyoda, M., editor(s), 2017 IEEE International Conference on Big Data (IEEE BigData 2017), Boston, MA, USA, December 11-14, 2017, pages 213–222, 2017. IEEE Computer Society
Performance characterization and acceleration of big data workloads on OpenPOWER system [link]Paper   doi   link   bibtex  
Characterizing Deep Learning over Big Data (DLoBD) Stacks on RDMA-Capable Networks. Lu, X.; Shi, H.; Javed, M. H.; Biswas, R.; and Panda, D. K. In 25th IEEE Annual Symposium on High-Performance Interconnects, HOTI 2017, Santa Clara, CA, USA, August 28-30, 2017, pages 87–94, 2017. IEEE Computer Society
Characterizing Deep Learning over Big Data (DLoBD) Stacks on RDMA-Capable Networks [link]Paper   doi   link   bibtex