I am an Assistant Professor of Computer Science and Engineering at University of California Santa Cruz, and an Adjunct Assistant Professor of Computer Science at Virginia Tech. I lead the Experimental and Virtualized Systems (ELVES) Research Lab.
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Brief BioDr. Liting Hu is currently an Assistant Professor of Computer Science and Engineering at University of California Santa Cruz. She received her Ph.D. degree in Computer Science from Georgia Institute of Technology in 2016, advised by Professor Karsten Schwan; and her bachelor degree in Computer Science from Huazhong University of Science and Technology in 2007. Prior to joining UCSC, she was an Assistant Professor of Computer Science at Virginia Tech from 2021 to 2022 and an Assistant Professor of Computer Science at Florida International University from 2017 to 2021.During her Ph.D. study, Liting has been fortunate to intern at different research labs and learn from many remarkable researchers. She spent the summer of 2015 at IBM T.J. Watson Research Center working with Shu Tao, Hui Kang and Michael V. Le. She spent the summer of 2013 at Intel Science & Technology Center for Cloud Computing, Carnegie Mellon University working with Michael Kozuch. She spent the summer of 2012 at IBM T.J. Watson Research Center working with Dilma Da Silva and Kyung Ryu. She spent the fall of 2011 at Microsoft Research Asia working with Zhenyu Guo. She spent the summer of 2010 at VMware working with Ajay Gulati. Liting’s research interests are in experimental computer systems, including stream processing systems, cloud and edge computing, distributed systems, systems virtualization. Her latest interests focus on building next-generation large-scale stream processing systems for the cloud and the edge. Her work has appeared in top systems venues like USENIX ATC, EuroSys, ICS, Middleware, IPDPS, ICDCS, HPDC, ICAC, TPDS, SIGOPS. Her research is gratefully supported by NSF, Department of Homeland Security, as well as a few more industry and university grants. She has received many research awards and scholarships, including an NSF CAREER Award, a Meta Faculty Research Award, and a Cyber Florida Seed Award. |
Research InterestsI lead the Experimental and Virtualized Systems (ELVES) Research Lab, which conducts Experimental Computer Systems research in the areas of Stream Processing Systems , Cloud and Edge Computing , Distributed Systems , and Systems Virtualization . Examples include stream processing systems (with Spark Streaming, Storm, Flink), identifying threats (e.g., fake news, rumors, social bots) in online social networks, federated learning systems, container as a service (with Docker and Kubernetes), and resource management in large-scale data centers (with Xen and KVM). |
See some of my recent projects for more details about my background and expertise:
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Selected Awards and Grants
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PublicationsStudents advised by me are identified by "*"1. Conference Papers[EuroSys'24] Cheng-Wei Ching*, Xin Chen, Taehwan Kim*, Bo Ji, Qingyang Wang, Dilma Da Silva, Liting Hu, “ Totoro: A Scalable Federated Learning Engine for the Edge”, in Proceedings of the 19th ACM SIGOPS European Conference on Computer Systems (EuroSys'24), Athens, Greece, April 2024. [Middleware'23] Jianshu Liu, Qingyang Wang, Shungeng Zhang, Liting Hu, Dilma Da Silva, “ Sora: A Latency Sensitive Approach for Microservice Soft Resource Adaption”, in Proceedings of the 36th ACM International Conference on Supercomputing (Middleware'23), Bologna, Italy, December 2023. [ICS'22] Mingzhe Liu, Haikun Liu, Chencheng Ye, Xiaofei Liao, Hai Jin, Yu Zhang, Ran Zheng, Liting Hu, “ Towards Low-Latency I/O Services for Mixed Workloads Using Ultra-Low Latency SSDs”, in Proceedings of the 36th ACM International Conference on Supercomputing (ICS'22), virtual event, June 2022. [USENIX ATC'21] Pinchao Liu*, Dilma Da Silva, Liting Hu, “ DART: A Scalable and Adaptive Edge Stream Processing Engine”, in Proceedings of the 2021 USENIX Annual Technical Conference (USENIX ATC'21), virtual event, July 2021. Acceptance Rate: 64/341 = 18.8%. [Middleware'20] Hailu Xu*, Pinchao Liu*, Susana Cruz-Diaz*, Dilma Da Silva, Liting Hu, “ SR3: Customizable Recovery for Stateful Stream Processing Systems”, in Proceedings of ACM/IFIP Middleware 2020 (Middleware'20), virtual event, December 2020. [IROS'20] Xin Chen, Thomas M. Tucker, Thomas R. Kurfess, Richard W. Vuduc, Liting Hu, “ Max Orientation Coverage: Efficient Path Planning to Avoid Collisions in the CNC Milling of 3D Objects”, in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'20), virtual event, October 2020. [IPDPS'20] Pinchao Liu*, Hailu Xu*, Dilma Da Silva, Qingyang Wang, Sarker Tanzir Ahmed, Liting Hu, “ FP4S: Fragment-based Parallel State Recovery for Stateful Stream Applications”, in Proceedings of the 34th IEEE International Parallel & Distributed Processing Symposium (IPDPS'20), virtual event, May 2020. [Big Data Congress'19] Boyuan Guan*, Pinchao Liu*, Hailu Xu*, Jennifer Fu, Qingyang Wang, Liting Hu, “ dpSmart: A Flexible Group Based Recommendation Framework for Digital Repository Systems”, in Proceedings of the 2019 International Congress on Big Data (Big Data Congress'19), Milan, Italy, July 2019. [Cloud'19] Hailu Xu*, Pinchao Liu*, Boyuan Guan*, Liting Hu, “ Exploiting the Spam Correlations in Scalable Online Social Spam Detection”, in Proceedings of the 2019 International Conference on Cloud Computing (Cloud'19), San Diego, CA, June 2019. Best Student Paper Award [IDCIS'19] Pinchao Liu*, Adnan Maruf, Farzana Beente Yusuf, Labiba Jahan, Hailu Xu*, Boyuan Guan*, Liting Hu, Sitharama S. Iyengar, “ Towards Adaptive Replication for Hot/Cold Blocks in HDFS using MemCached”, in 2019 2nd International Conference on Data Intelligence and Security (ICDIS), South Padre Island, TX, June 2019. [Cloud'18] Pinchao Liu*, Hailu Xu*, Zhiyuan Shi*, Jason Liu, Qingyang Wang, Jai Dayal, Yuzhe Tang, Liting Hu, “ A Toolset for Detecting Containerized Application's Dependencies in CaaS Clouds”, in Proceedings of the 11th International Conference on Cloud Computing (Cloud'18), San Francisco, CA, July 2018. [Cloud'18] Hailu Xu*, Pinchao Liu*, Yao Xiao, Wentao Wang, Jai Dayal, Qingyang Wang, Yuzhe Tang, Liting Hu, “ Oases: An Online Scalable Spam Detection System for Social Networks”, in Proceedings of the 11th International Conference on Cloud Computing (Cloud'18), San Francisco, CA, July 2018. [ICAC'17] Xin Chen, Ymir Vigfusson, Douglas M. Blough, Fang Zheng, Kun-Lung Wu, Liting Hu, “ GOVERNOR: Smoother Stream Processing Through Smarter Backpressure”, in Proceedings of the 14th IEEE International Conference on Autonomic Computing (ICAC'17), Columbus, Ohio, July 2017. [Cloud'17] Xin Chen*, Liangqi Liu*, Jing Chang*, Diana Leante Bone*, Liting Hu, “ Breaking Down Hadoop Distributed File Systems Data Analytics Tools: Apache Hive vs. Apache Pig vs. Pivotal HWAQ”, in Proceedings of the 10th IEEE International Conference on Cloud Computing (Cloud'17), Honolulu, Hawaii, June 2017. [ICDCS'17] Xin Chen*, Liting Hu, Douglas M. Blough, Michael A. Kozuch, Matthew Wolf, “ RBAY: A Scalable and Extensible Information Plane for Federating Distributed Datacenter Resources”, in Proceedings of the 37nd IEEE International Conference on Distributed Computing Systems (ICDCS'17), Atlanta, GA, June 2017. [USENIX ATC'14] Liting Hu, Karsten Schwan, Hrishikesh Amur, Xin Chen, “ ELF: Efficient Lightweight Fast Stream Processing at Scale”, in Proceedings of the 2014 USENIX Annual Technical Conference (USENIX ATC'14), Philadelphia, PA, June 2014. Acceptance rate: 36/241=14.9%. [ICAC'12] Liting Hu, Karsten Schwan, Ajay Gulati, Junjie Zhang, Chengwei Wang, “ Net-Cohort: Detecting and Managing VM Ensembles in Data Center Systems”, in Proceedings of the 9th ACM International Conference on Autonomic Computing (ICAC'12), New York, NY, September 2012. [ICDCS'12] Liting Hu, Kyung Dong Ryu, Dilma Da Silva, Karsten Schwan, “ v-Bundle: Flexible Group Resource Offerings in Clouds”, in Proceedings of the 32nd IEEE International Conference on Distributed Computing Systems (ICDCS'12), Macau, China, June 2012. [ICAC'11] Chengwei Wang, Karsten Schwan, Vanish Talwar, Greg Eisenhauer, Liting Hu, Matthew Wolf, “ A Flexible Architecture Integrating Monitoring and Analytics for Managing Large-Scale Data Centers”, in Proceedings of the 8th ACM International Conference on Autonomic Computing (ICAC'11), Karlsruhe, Germany, June 2011. [HPDC'09] Haikun Liu, Hai Jin, Xiaofei Liao, Liting Hu, Chen Yu, “ Live Migration of Virtual Machine Based on Execution Trace and Deterministic Replay”, in Proceedings of the 18th International ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC'09), Munich, Germany, June 2009. [Cluster'08] Liting Hu, Hai Jin, Xiaofei Liao, Xianjie Xiong, Haikun Liu, “ Magnet: A Novel Scheduling Policy for Power Reduction in Cluster with Virtual Machines”, in Proceedings of the 2008 IEEE International Conference on Cluster Computing (Cluster'08), Tsukuba, Japan, September 2008. 2. Journal Articles[TPDS] Hailu Xu*, Pinchao Liu*, Sarker Tanzir Ahmed, Dilma Da Silva, Liting Hu, “ Adaptive Fragment-based Parallel State Recovery for Stream Processing Systems”, in IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), vol. 34, no. 8, pp. 2464-2478, August 2023. [IEEE Access] Hailu Xu*, Pinchao Liu*, Boyuan Guan*, Qingyang Wang, Dilma Da Silva, Liting Hu, “ Online and Scalable Information Integrity by Harnessing Social Spam Correlations”, in IEEE Access (IEEE Access), vol. 11, pp. 7768-7781, January 2023. [IEEE Access] Hailu Xu*, Pei-Hung Lin, Murali Emani, Liting Hu, Chunhua Liao, “ XUnified: A Framework for Guiding Optimal Use of GPU Unified Memory”, in IEEE Access (IEEE Access), vol. 10, pp. 82614-82625, August 2022. [TPDS] Shungeng Zhang, Qingyang Wang, Yasuhiko Kanemasa, Huasong Shan, Liting Hu, “ The Impact of Event Processing Flow on Asynchronous Server Efficiency”, in IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), vol. 31, no. 3, pp. 565-579, March 2020. [ETSS] Yuzhe Tang, Kai Li, Katchaguy Areekijseree, Shuigeng Zhou, Liting Hu, “ Privacy-Preserving Multi-Party Directory Services”, in EAI Endorsed Transactions on Security and Safety, January 2019. [TPDS] Qingyang Wang, Hui Chen, Shungeng Zhang, Liting Hu, Balaji Palanisamy, “ Integrating Concurrency Control in n-Tier Application Scaling Management in the Cloud”, in IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), vol. 30, no. 4, pp. 855-869, April 2019. [SIGOPS] Chengwei Wang, Soila P. Kavulya, Jiaqi Tan, Liting Hu, Mahendra Kutare, Mike Kasick, Karsten Schwan, Priya Narasimhan, Rajeev Gandhi, “ Performance Troubleshooting in Data Centers: An Annotated Bibliography”, in ACM SIGOPS Operating Systems Review, vol. 47, no. 3, pp. 50-62, December 2013. [Cluster Computing] Xiaofei Liao, Liting Hu, Hai Jin, “ Energy Optimization Schemes in Cluster with Virtual Machines”, in Cluster Computing, vol. 13, no. 2, pp 113-126, June 2010. [Concurrency&Computation] Xiaofei Liao, Hai Jin, Liting Hu, Haikun Liu, “ Towards Virtualized Desktop Environment”, in IEEE Concurrency and Computation: Practice and Experience, vol. 22, no. 4, pp 419-440, March 2010. 3. Workshop Papers[ECAI'23] Cheng-Wei Ching*, Chirag Gupta*, Zi Huang*, Liting Hu, “ An IoT-Edge Orchestrated Online Deep Compressed Sensing Framework”, in 2023 IEEE 43rd International Conference on Distributed Computing Systems Workshop (ICDCSW) on Edge-to-Cloud AI Orchestration (ECAI'23), Hong Kong, China, July 2023. [MCHPC'19] Hailu Xu*, Murali Emani, Pei-Hung Lin, Liting Hu, Chunhua Liao, “ Machine Learning Guided Optimal Use of GPU Unified Memory”, in Proceedings of the Workshop on Memory Centric High Performance Computing, in conjunction with SC 19 (MCHPC'19), Denver, CO, November 2019. [BSMDMA'18] Hailu Xu*, Boyuan Guan*, Pinchao Liu*, William Escudero*, Liting Hu, “ Harnessing the Nature of Spam in Scalable Online Social Spam Detection”, in Proceedings of the 2018 International Workshop on Big Social Media Data Management and Analysis, in conjunction with IEEE Big Data (BSMDMA'18), Seattle, WA, December 2018. [MBDS'12] Rajalakshmi Ramesh, Liting Hu, Karsten Schwan, “ Project Hoover: Auto-Scaling Streaming Map-Reduce Applications”, in Proceedings of the 2nd Workshop on Management of Big Data Systems, in conjunction with ACM ICAC’12 (MBDS'12), New York, NY, September 2012. [HotCloud'10] Renuka Apte, Liting Hu, Arpan Ghosh, Karsten Schwan, “ Look Who’s Talking: Discovering Dependencies between Virtual Machines Using CPU Utilization”, in Proceedings of the 2nd USENIX Workshop on Hot Topics in Cloud Computing (HotCloud'10), Boston, MA, June 2010. [SVM'08] Xiaofei Liao, Xianjie Xiong, Hai Jin, Liting Hu, “ LVD: A Lightweight Virtual Desktop Management Architecture”, in International Workshop on Systems and Virtualization Management (VM'08), Springer, Munich, Germany, October 2008. |
Research GroupPh.D. Students (Primary Advisor)Cheng-Wei Ching (Summer 2022 - present) Chaeeun Kim (Fall 2023 - present) Co-advised with Dr. Chen Qian Boyuan Guan (Ph.D. 2022) First Job Tech Lead and Lead Developer of the FIU Library Pinchao Liu (Ph.D. 2021) First Job Research Scientist at Meta Hailu Xu (Ph.D. 2020) First Job Tenure-track Assistant Professor of Computer Science at California State University, Long Beach Master Students (Primary Advisor) Chirag Gupta (starting in Spring 2022 - present) Manoj Prabhakar Paidiparthy (M.S. 2023) First Job Software Engineer at Microsoft Junyi Yu (M.S. 2023) First Job Software Engineer at Flexport Taehwan Kim (M.S. 2022) First Job Software Engineer at Google Undergraduates (Primary Advisor) Ulises Fernandez (B.S. 2021) First Job Software Engineer at Deloitte Rebecca Dupuis (B.S. 2021) First Job Software Engineer at Microsoft Susana Cruz Diaz (B.S. 2020) First Job Software Engineer Associate at Lockheed Martin William Escudero (B.S. 2019) First Job Software Engineer at JPMorgan Chase & Co |
Teaching
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Professional ServicesJournal EditorshipOrganizing Committee Program Committee Journal Review Diversity Activities School Coordinator |