![](https://dblp.org/img/logo.ua.320x120.png)
![](https://dblp.org/img/dropdown.dark.16x16.png)
![](https://dblp.org/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.org/img/search.dark.16x16.png)
![search dblp](https://dblp.org/img/search.dark.16x16.png)
default search action
Ming Zhao 0002
Person information
- affiliation: Arizona State University, Tempe, AZ, USA
- affiliation: Florida International University, Miami, FL, USA
Other persons with the same name
- Ming Zhao — disambiguation page
- Ming Zhao 0001 — Tsinghua University, National Laboratory for Information Science and Technology, Beijing, China
- Ming Zhao 0003 — Google (and 1 more)
- Ming Zhao 0004 — Xi'an Jiatong University, China
- Ming Zhao 0005
— Nanyang Technological University, School of Electrical and Electronic Engineering, Singapore
- Ming Zhao 0006
— Xi'an Jiaotong University, School of Mechanical Engineering, China (and 1 more)
- Ming Zhao 0007
— Central South University, School of Software, Changsha, China
- Ming Zhao 0008
— University of Science and Technology of China, School of Information Science and Technology, CAS Key Laboratory of Wireless-Optical Communications, Hefei, China
- Ming Zhao 0009
— Shanghai Maritime University, Department of Information Engineering / Department of Logistics Engineering, China (and 2 more)
- Ming Zhao 0010
— Ministry of Transport, China Waterborne Transport Research Institute, Beijing, China
- Ming Zhao 0011
— Yangtze University, School of Computer Science, Jingzhou, China
Refine list
![note](https://dblp.org/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c66]Kaiqi Zhao, Ming Zhao:
Self-Supervised Quantization-Aware Knowledge Distillation. AISTATS 2024: 4375-4383 - [c65]Chongzhuo Yang
, Zhang Cao
, Chang Guo
, Ming Zhao
, Zhichao Cao
:
Can ZNS SSDs be Better Storage Devices for Persistent Cache? HotStorage 2024 - [i12]Kaiqi Zhao, Ming Zhao:
Self-Supervised Quantization-Aware Knowledge Distillation. CoRR abs/2403.11106 (2024) - 2023
- [j12]Ankur Chowdhary
, Kritshekhar Jha
, Ming Zhao:
Generative Adversarial Network (GAN)-Based Autonomous Penetration Testing for Web Applications. Sensors 23(18): 8014 (2023) - [c64]Qirui Yang, Runyu Jin, Ni Fan, Devasena Inupakutika, Bridget Davis, Ming Zhao:
AdaCache: A Disaggregated Cache System with Adaptive Block Size for Cloud Block Storage. CLOUD 2023: 348-359 - [c63]Kaiqi Zhao, Animesh Jain, Ming Zhao:
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions. AISTATS 2023: 10470-10486 - [c62]Runyu Jin, Qirui Yang, Ming Zhao:
When Edge Meets FaaS: Opportunities and Challenges. EDGE 2023: 23-25 - [c61]Kaiqi Zhao, Yitao Chen, Ming Zhao:
A Contrastive Knowledge Transfer Framework for Model Compression and Transfer Learning. ICASSP 2023: 1-5 - [c60]Kaiqi Zhao
, Ming Zhao
:
Poster: Self-Supervised Quantization-Aware Knowledge Distillation. SEC 2023: 250-252 - [c59]Ming Zhao, Kritshekhar Jha, Sungho Hong:
GPU-enabled Function-as-a-Service for Machine Learning Inference. IPDPS 2023: 918-928 - [i11]Ming Zhao, Kritshekhar Jha, Sungho Hong:
GPU-enabled Function-as-a-Service for Machine Learning Inference. CoRR abs/2303.05601 (2023) - [i10]Kaiqi Zhao, Yitao Chen, Ming Zhao:
A Contrastive Knowledge Transfer Framework for Model Compression and Transfer Learning. CoRR abs/2303.07599 (2023) - [i9]Kaiqi Zhao, Animesh Jain, Ming Zhao:
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions. CoRR abs/2303.08595 (2023) - [i8]Qirui Yang, Runyu Jin, Ni Fan, Devasena Inupakutika, Bridget Davis, Ming Zhao:
AdaCache: A Disaggregated Cache System with Adaptive Block Size for Cloud Block Storage. CoRR abs/2306.17254 (2023) - [i7]Runyu Jin, Qirui Yang, Ming Zhao:
When Edge Meets FaaS: Opportunities and Challenges. CoRR abs/2307.06397 (2023) - [i6]Kaiqi Zhao, Ming Zhao:
Poster: Self-Supervised Quantization-Aware Knowledge Distillation. CoRR abs/2309.13220 (2023) - 2022
- [c58]Sang-Hun Sim, Tara Paranjpe, Nicole Roberts, Ming Zhao:
Exploring Edge Machine Learning-based Stress Prediction using Wearable Devices. ICMLA 2022: 1266-1273 - [c57]Kaiqi Zhao, Hieu Nguyen, Animesh Jain, Nathan Susanj, Athanasios Mouchtaris, Lokesh Gupta, Ming Zhao:
Knowledge Distillation via Module Replacing for Automatic Speech Recognition with Recurrent Neural Network Transducer. INTERSPEECH 2022: 4436-4440 - [c56]Qirui Yang, Runyu Jin, Bridget Davis, Devasena Inupakutika, Ming Zhao:
Performance Evaluation on CXL-enabled Hybrid Memory Pool. NAS 2022: 1-5 - [i5]Kaiqi Zhao, Animesh Jain, Ming Zhao:
Iterative Activation-based Structured Pruning. CoRR abs/2201.09881 (2022) - [i4]Kaiqi Zhao, Animesh Jain, Ming Zhao:
Adaptive Activation-based Structured Pruning. CoRR abs/2201.10520 (2022) - [i3]Kaiqi Zhao, Yitao Chen, Ming Zhao:
Enabling Deep Learning on Edge Devices through Filter Pruning and Knowledge Transfer. CoRR abs/2201.10947 (2022) - 2021
- [j11]Saman Biookaghazadeh, Pravin Kumar Ravi, Ming Zhao:
Toward Multi-FPGA Acceleration of the Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 17(2): 25:1-25:23 (2021) - [c55]Saman Biookaghazadeh, Fengbo Ren, Ming Zhao:
Characterizing Loop Acceleration in Heterogeneous Computing. CLOUD 2021: 445-455 - [c54]Liana V. Rodriguez, Farzana Beente Yusuf, Steven Lyons, Eysler Paz, Raju Rangaswami, Jason Liu, Ming Zhao, Giri Narasimhan:
Learning Cache Replacement with CACHEUS. FAST 2021: 341-354 - [c53]Eugene N. Kuznetsov, Yitao Chen, Ming Zhao:
SecureFL: Privacy Preserving Federated Learning with SGX and TrustZone. SEC 2021: 55-67 - 2020
- [j10]Jianyu Fu
, Youyou Lu, Jiwu Shu, Guangming Liu, Ming Zhao:
COWCache: effective flash caching for Copy-on-Write virtual disks. Clust. Comput. 23(2): 623-639 (2020) - [e3]Irfan Ahmad, Ming Zhao:
3rd USENIX Workshop on Hot Topics in Edge Computing, HotEdge 2020, June 25-26, 2020. USENIX Association 2020 [contents] - [i2]Qirui Yang, Runyu Jin, Nabil Gandhi, Xiongzi Ge, Hoda Aghaei Khouzani, Ming Zhao:
EdgeBench: A Workflow-based Benchmark for Edge Computing. CoRR abs/2010.14027 (2020)
2010 – 2019
- 2019
- [j9]Vasily Tarasov, Lukas Rupprecht, Dimitris Skourtis, Wenji Li, Raju Rangaswami, Ming Zhao:
Evaluating Docker storage performance: from workloads to graph drivers. Clust. Comput. 22(4): 1159-1172 (2019) - [j8]Pengfei Zuo, Yu Hua, Ming Zhao, Wen Zhou, Yuncheng Guo:
Write Deduplication and Hash Mode Encryption for Secure Nonvolatile Main Memory. IEEE Micro 39(1): 44-51 (2019) - [j7]George Amvrosiadis, Ali Raza Butt, Vasily Tarasov, Erez Zadok, Ming Zhao:
Selected Results of the Workshop on Data Storage Research 2025. login Usenix Mag. 44(4) (2019) - [c52]Yitao Chen, Saman Biookaghazadeh, Ming Zhao
:
Exploring the capabilities of mobile devices in supporting deep learning. SEC 2019: 127-138 - [c51]Yitao Chen, Kaiqi Zhao, Baoxin Li, Ming Zhao:
Exploring the Use of Synthetic Gradients for Distributed Deep Learning across Cloud and Edge Resources. HotEdge 2019 - [c50]Ming Zhao, Yiqi Xu:
vPFS+: Managing I/O Performance for Diverse HPC Applications. MSST 2019: 51-64 - [c49]Saman Biookaghazadeh, Yitao Chen, Kaiqi Zhao, Ming Zhao:
KnowledgeNet: Disaggregated and Distributed Training and Serving of Deep Neural Networks. OpML 2019: 47-49 - [c48]Douglas Otstott, Ming Zhao, Sean Williams, Latchesar Ionkov, Michael Lang:
A Foundation for Automated Placement of Data. PDSW@SC 2019: 50-59 - [c47]Qirui Yang, Runyu Jin, Ming Zhao:
SmartDedup: Optimizing Deduplication for Resource-constrained Devices. USENIX ATC 2019: 633-646 - 2018
- [c46]Ragini Sharma, Saman Biookaghazadeh, Baoxin Li, Ming Zhao
:
Are Existing Knowledge Transfer Techniques Effective for Deep Learning with Edge Devices? EDGE 2018: 42-49 - [c45]Ming Zhao, Jorge Cabrera:
RTVirt: enabling time-sensitive computing on virtualized systems through cross-layer CPU scheduling. EuroSys 2018: 27:1-27:13 - [c44]Saman Biookaghazadeh, Ming Zhao, Fengbo Ren:
Are FPGAs Suitable for Edge Computing? HotEdge 2018 - [c43]Giuseppe Vietri, Liana V. Rodriguez, Wendy A. Martinez, Steven Lyons, Jason Liu, Raju Rangaswami, Ming Zhao, Giri Narasimhan:
Driving Cache Replacement with ML-based LeCaR. HotStorage 2018 - [c42]Ragini Sharma, Saman Biookaghazadeh, Ming Zhao:
Are Existing Knowledge Transfer Techniques Effective For Deep Learning on Edge Devices? HPDC (Posters/Doctoral Consortium) 2018: 15-16 - [c41]Yitao Chen, Saman Biookaghazadeh, Ming Zhao
:
Exploring the Capabilities of Mobile Devices Supporting Deep Learning. HPDC (Posters/Doctoral Consortium) 2018: 17-18 - [c40]Jianyu Fu, Dulcardo Arteaga, Ming Zhao:
Locality-driven MRC Construction and Cache Allocation. HPDC (Posters/Doctoral Consortium) 2018: 19-20 - [c39]Ming Zhao, Lixi Wang, Yun Lv, Jing Xu:
Cross-Layer Optimization for Virtual Machine Resource Management. IC2E 2018: 90-98 - [c38]Pengfei Zuo, Yu Hua, Ming Zhao
, Wen Zhou, Yuncheng Guo:
Improving the Performance and Endurance of Encrypted Non-Volatile Main Memory through Deduplicating Writes. MICRO 2018: 442-454 - [e2]Ming Zhao, Abhishek Chandra, Lavanya Ramakrishnan:
Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2018, Tempe, AZ, USA, June 11-15, 2018. ACM 2018 [contents] - [i1]Saman Biookaghazadeh, Fengbo Ren, Ming Zhao:
Are FPGAs Suitable for Edge Computing? CoRR abs/1804.06404 (2018) - 2017
- [j6]Douglas Otstott
, Latchesar Ionkov, Michael Lang, Ming Zhao:
TCASM: An asynchronous shared memory interface for high-performance application composition. Parallel Comput. 63: 61-78 (2017) - [c37]Saman Biookaghazadeh, Shujia Zhou, Ming Zhao:
Kaleido: Enabling Efficient Scientific Data Processing on Big-Data Systems. NAS 2017: 1-10 - [c36]Vasily Tarasov, Lukas Rupprecht, Dimitris Skourtis, Amit Warke, Dean Hildebrand, Mohamed Mohamed, NagaPramod Mandagere, Wenji Li, Raju Rangaswami, Ming Zhao:
In Search of the Ideal Storage Configuration for Docker Containers. FAS*W@SASO/ICCAC 2017: 199-206 - 2016
- [j5]Hector A. Duran-Limon, Jesus Flores-Contreras, Nikos Parlavantzas, Ming Zhao, Angel Meulenert-Peña:
Efficient execution of the WRF model and other HPC applications in the cloud. Earth Sci. Informatics 9(3): 365-382 (2016) - [c35]Wenji Li, Gregory Jean-Baptise, Juan Riveros, Giri Narasimhan, Tony Zhang, Ming Zhao:
CacheDedup: In-line Deduplication for Flash Caching. FAST 2016: 301-314 - [c34]Dulcardo Arteaga, Jorge Cabrera, Jing Xu, Swaminathan Sundararaman, Ming Zhao:
CloudCache: On-demand Flash Cache Management for Cloud Computing. FAST 2016: 355-369 - [c33]Yiqi Xu, Ming Zhao:
IBIS: Interposed Big-data I/O Scheduler. HPDC 2016: 111-122 - 2015
- [c32]Saman Biookaghazadeh, Yiqi Xu, Shujia Zhou, Ming Zhao:
Enabling scientific data storage and processing on big-data systems. IEEE BigData 2015: 1978-1984 - [c31]Lixi Wang, Jing Xu, Hector A. Duran-Limon, Ming Zhao:
QoS-Driven Cloud Resource Management through Fuzzy Model Predictive Control. ICAC 2015: 81-90 - [c30]Sajib Kundu, Raju Rangaswami, Ming Zhao, Ajay Gulati, Kaushik Dutta:
Revenue Driven Resource Allocation for Virtualized Data Centers. ICAC 2015: 197-206 - 2014
- [j4]Yun Lu, Ming Zhao, Lixi Wang, Naphtali Rishe:
v-TerraFly: large scale distributed spatial data visualization with autonomic resource management. J. Big Data 1: 4 (2014) - [c29]Michel Angelo Roger, Yiqi Xu, Ming Zhao:
BigCache for big-data systems. IEEE BigData 2014: 189-194 - [c28]Douglas Otstott, Noah Evans, Latchesar Ionkov, Ming Zhao, Michael Lang
:
Enabling composite applications through an asynchronous shared memory interface. IEEE BigData 2014: 219-224 - [c27]Dulcardo Arteaga, Ming Zhao:
Client-side Flash Caching for Cloud Systems. SYSTOR 2014: 7:1-7:11 - 2013
- [c26]Ricardo Koller, Leonardo Mármol, Raju Rangaswami, Swaminathan Sundararaman, Nisha Talagala, Ming Zhao:
Write policies for host-side flash caches. FAST 2013: 45-58 - [c25]Yiqi Xu, Ming Zhao:
Two-level Throughput and Latency IO Control for Parallel File Systems. Feedback Computing 2013 - [c24]Yiqi Xu, Adrian Suarez, Ming Zhao:
IBIS: interposed big-data I/O scheduler. HPDC 2013: 109-110 - [c23]Yun Lu, Ming Zhao, Guangqiang Zhao, Lixi Wang, Naphtali Rishe:
Massive GIS Database System with Autonomic Resource Management. ICMLA (2) 2013: 451-456 - [c22]Yonggang Liu, Renato J. O. Figueiredo
, Yiqi Xu, Ming Zhao:
On the design and implementation of a simulator for parallel file system research. MSST 2013: 1-5 - [e1]Yixin Diao, Jie Liu, Ming Zhao:
8th International Workshop on Feedback Computing, San Jose, CA, USA, June 25, 2013. USENIX Association 2013 [contents] - 2012
- [c21]Lixi Wang, Jing Xu, Ming Zhao:
Application-aware cross-layer virtual machine resource management. ICAC 2012: 13-22 - [c20]Yiqi Xu, Dulcardo Arteaga, Ming Zhao, Yonggang Liu, Renato J. O. Figueiredo
, Seetharami Seelam:
vPFS: Bandwidth virtualization of parallel storage systems. MSST 2012: 1-12 - [c19]Sajib Kundu, Raju Rangaswami, Ajay Gulati, Ming Zhao, Kaushik Dutta:
Modeling virtualized applications using machine learning techniques. VEE 2012: 3-14 - 2011
- [c18]Lixi Wang, Jing Xu, Ming Zhao, José A. B. Fortes:
Adaptive virtual resource management with fuzzy model predictive control. ICAC 2011: 191-192 - [c17]Lixi Wang, Jing Xu, Ming Zhao, Yicheng Tu, José A. B. Fortes:
Fuzzy Modeling Based Resource Management for Virtualized Database Systems. MASCOTS 2011: 32-42 - [c16]Dulcardo Arteaga, Ming Zhao:
Towards Scalable Application Checkpointing with Parallel File System Delegation. NAS 2011: 130-139 - [c15]Hector A. Duran-Limon, Luis A. Silva-Banuelos, Victor H. Tellez-Valdez, Nikos Parlavantzas, Ming Zhao:
Using Lightweight Virtual Machines to Run High Performance Computing Applications: The Case of the Weather Research and Forecasting Model. UCC 2011: 146-153 - 2010
- [c14]Sajib Kundu, Raju Rangaswami, Kaushik Dutta, Ming Zhao:
Application performance modeling in a virtualized environment. HPCA 2010: 1-10 - [c13]Jason Liu
, Raju Rangaswami, Ming Zhao:
Model-driven network emulation with virtual time machine. WSC 2010: 688-696
2000 – 2009
- 2009
- [c12]Juan C. Martinez, Lixi Wang, Ming Zhao, S. Masoud Sadjadi:
Experimental study of large-scale computing on virtualized resources. VTDC@ICAC 2009: 35-42 - [c11]Jing Xu, Ming Zhao, José A. B. Fortes:
Cooperative Autonomic Management in Dynamic Distributed Systems. SSS 2009: 756-770 - 2008
- [j3]Jing Xu, Ming Zhao, José A. B. Fortes, Robert Carpenter, Mazin S. Yousif:
Autonomic resource management in virtualized data centers using fuzzy logic-based approaches. Clust. Comput. 11(3): 213-227 (2008) - 2007
- [c10]Jing Xu, Ming Zhao, José A. B. Fortes, Robert Carpenter, Mazin S. Yousif:
On the Use of Fuzzy Modeling in Virtualized Data Center Management. ICAC 2007: 25 - [c9]Jack DiGiovanna, Loris Marchal
, Prapaporn Rattanatamrong, Ming Zhao, Shalom Darmanjian, Babak Mahmoudi, Justin C. Sanchez, José C. Príncipe, Linda Hermer-Vazquez, Renato J. O. Figueiredo
, José A. B. Fortes:
Towards Real-Time Distributed Signal Modeling for Brain-Machine Interfaces. International Conference on Computational Science (1) 2007: 964-971 - [c8]Ming Zhao, Renato J. O. Figueiredo
:
Experimental study of virtual machine migration in support of reservation of cluster resources. VTDC@SC 2007: 5:1-5:8 - [c7]Ming Zhao, Renato J. O. Figueiredo
:
A user-level secure grid file system. SC 2007: 45 - 2006
- [j2]Ming Zhao, Jian Zhang, Renato J. O. Figueiredo
:
Distributed File System Virtualization Techniques Supporting On-Demand Virtual Machine Environments for Grid Computing. Clust. Comput. 9(1): 45-56 (2006) - [c6]Ming Zhao, Jing Xu, Renato J. O. Figueiredo:
Towards Autonomic Grid Data Management with Virtualized Distributed File Systems. ICAC 2006: 209-218 - [c5]Ming Zhao, Renato J. O. Figueiredo
:
Application-Tailored Cache Consistency for Wide-Area File Systems. ICDCS 2006: 41 - 2005
- [j1]Sumalatha Adabala, Vineet Chadha, Puneet Chawla, Renato J. O. Figueiredo
, José A. B. Fortes, Ivan Krsul, Andréa M. Matsunaga
, Maurício O. Tsugawa, Jian Zhang, Ming Zhao, Liping Zhu, Xiaomin Zhu:
From virtualized resources to virtual computing grids: the In-VIGO system. Future Gener. Comput. Syst. 21(6): 896-909 (2005) - [c4]Andréa M. Matsunaga
, Maurício O. Tsugawa, Ming Zhao, Liping Zhu, Vivekananthan Sanjeepan, Sumalatha Adabala, Renato J. O. Figueiredo
, Herman Lam, José A. B. Fortes:
On the Use of Virtualization and Service Technologies to Enable Grid-Computing. Euro-Par 2005: 1-12 - [c3]Ming Zhao, Vineet Chadha, Renato J. O. Figueiredo:
Supporting application-tailored grid file system sessions with WSRF-based services. HPDC 2005: 24-33 - 2004
- [c2]Jithendar Paladugula, Ming Zhao, Renato J. O. Figueiredo
:
Support for Data-Intensive, Variable-Granularity Grid Applications via Distributed File System Virtualization - A Case Study of Light Scattering Spectroscopy. CLADE 2004: 12 - [c1]Ming Zhao, Jian Zhang, Renato J. O. Figueiredo:
Distributed File System Support for Virtual Machines in Grid Computing. HPDC 2004: 202-211
Coauthor Index
![](https://dblp.org/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-23 18:26 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint