Welcome to Feng Yan's Homepage
I have moved to University of Houston from Fall 2022. This site is no longer maintained, please visit my new website at University of Houston.
I am Associate Professor at the Computer Science & Engineering Department of University of Nevada, Reno. I earned M.S and Ph.D. degrees in Computer Science of William & Mary, where I worked with Evgenia Smirni and Alma Riska from EMC. I also worked at Microsoft Research with Yuxiong He, Olatunji Ruwase, and Trishul Chilimbi and HP Labs with Lucy Cherkasova.
My research bridges Big Data, Machine Learning, and System areas. I also enjoy interdisciplinary research and have been using Big Data and Machine Learning to innovate domain science and engineering.
Some of my recently focused research topics include: Large-scale Distributed Deep Learning, Machine Learning as a Service (MLaaS), AutoML/Neural Architecture Search (NAS), Serverless Computing, Federated Learning, Big Data/AI-driven Wildfire/Material/Pavement.
Some of my recently focused research topics include: Large-scale Distributed Deep Learning, Machine Learning as a Service (MLaaS), AutoML/Neural Architecture Search (NAS), Serverless Computing, Federated Learning, Big Data/AI-driven Wildfire/Material/Pavement.
I am actively publishing at the most prestigious venues in Machine Learning (e.g., NIPS, KDD, AAAI, etc.) and Computer Systems (e.g., SOSP, SC, HPDC, VLDB, USENIX ATC, EuroSys, FAST, etc.). I am actively collaborating with industry and national labs to solve important yet challenging problems to generate real-world impact.
UNR is a Carnegie R1 (highest research activity) institution and among the top doctoral research universities in the US. According to CSRankings, UNR is ranked at 101nd (the 74th in the last 2 years) overall in Computer Science. I am ranked the 1st in CSE in the number of papers published at top venues and leading UNR to rank at the 25th in High-performance computing (HPC) (the 12th in the last 5 years and the 7th in the last 2 years), the 49th in Operating systems (the 29th in the last 2 years), the 115th in Artificial intelligence (the 93th in the last 2 years), and the 125th in Machine learning & data mining (the 102th in the last 2 years).
Multiple PhD/MS/BS (with assistantship) Openings: I am always looking for self-motivated students to join my team. If you are interested, please send me your CV and materials that you believe will help you get the position (e.g., Research Statement, Personal Statement, Publication, Transcripts, Awards, etc.).
• For Fall enrollment, contact me by July. For Spring enrollment, contact me by Nov.
• For undergraduates, you can apply the UNR PREP and NSF REU Site for financial support.
• Due to the large volume of application emails, I may not be able to respond every email. I usually review them in a batch and will contact you if I decide to move forward with you to the next stage.
• If you want a prioritized consideration and my email response, you can pick one (or a few) paper(s) from my recent publications and write a paper review (summary, your thoughts of the paper, especially weakness, what can be improved, potential follow up directions, etc.).
Our NSF REU Site is hiring undergraduate students for Summer 2022, please apply via this link.
Please follow ACM SIGMETRICS Twitter, LinkedIn, and YouTube Channel (for any social media questions regarding ACM SIGMETRICS, contact me at fyan at unr.edu).
Selected Awards and Grants
-
• NSF EPSCoR Award ($20M in total)
• Regents' Rising Researcher Award, 2022
• Outstanding Service Award of IEEE ACSOS, 2022
• NSF CAREER Award (Sole PI)
• CSE Best Researcher Award, 2020
• NSF BIGDATA Award (Lead PI)
• NSF CRII Award (Sole PI)
• NSF National AI Research Institutes (planning) Award (UNR PI)
• NSF REU Award (Co-PI)
• FAA BAKFAA Award (Co-PI)
• AWS Cloud Credits for Research Award (Sole PI)
• Best Student Paper Award, IEEE CLOUD 2018
• Best Paper Award, CLOUD 2019
• Best Student Paper Award, ITNG 2021
Publications
-
top-cs: top-tier Computer Science publication venue according to CSRankings
top-cr: top-tier Computer Science publication venue according to Conference Ranks
top-w: workshop in top-tier publication venue
20 top-cs papers have been published during 5 years at UNR -
VLDB 2022 (top-cs, top-cr)
Ahsan Ali, Riccardo Pinciroli, Feng Yan, Evgenia Smirni, Optimizing Inference Serving on Serverless Platforms, in Proceedings of the 48th International Conference on Very Large Data Bases (VLDB 2022), Sydney, Australia, September, 2022 (Acceptance rate: TBD). -
AutoML 2022 (top venue in AutoML)
Hsin-Pai Cheng, Feng Liang, Meng Li, Bowen Cheng, Feng Yan, Hai Li, Vikas Chandra, Yiran Chen, ScaleNAS: Multi-Path One-Shot NAS for Scale-Aware High-Resolution Representation, in Proceedings of the AutoML Conference 2022 (co-located with ICML 2022) (AutoML 2022), Baltimore, US, July, 2022 (Acceptance rate: 19.2%). -
FL-AAAI 2022 (top-w)
Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo Angel, Yi Zhou, Feng Yan, Ali R. Butt, Tokenized Incentive for Federated Learning, in Proceedings of the International Workshop on Trustable, Verifiable and Auditable Federated Learning in Conjunction with AAAI 2022 (FL-AAAI 2022), Vancouver, BC, Canada, March, 2022. -
IPDPS 2022 (top-cr)
Olamide Timothy Tawose, Bin Li, Lei Yang, Feng Yan, Dongfang Zhao, Topological Modeling and Parallelization of Multidimensional Data on Microelectrode Arrays, in Proceedings of the 36th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2022), Lyon, France, June, 2022 (Acceptance rate: TBD). -
NeurIPS 2021 (top-cs, top-cr)
Heyang Qin, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement, in Proceedings of the Neural Information Processing Systems 2021 (NeurIPS 2021), Virtual, December, 2021 (Acceptance rate: 2371/9122=26%). -
SOSP 2021 (top-cs, top-cr)
Youhui Bai, Cheng Li, Quan Zhou, Jun Yi, Ping Gong, Feng Yan, Ruichuan Chen, Yinlong Xu Gradient Compression Supercharged High-Performance Data Parallel DNN Training, in Proceedings of the 28th ACM Symposium on Operating Systems Principles (SOSP 2021), Virtual, October, 2021 (Acceptance rate: 54/348=15.5%). -
SoCC 2021 (top venue in cloud)
Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, Feng Yan, Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning, in Proceedings of the ACM Symposium on Cloud Computing 2021 (SoCC 2021), Seattle, WA, November, 2021 (Acceptance rate: 46/145=31.7%). -
SC 2021 (top-cs, top-cr)
Abdullah Al-Mamun, Feng Yan, Dongfang Zhao, BAASH: Lightweight, Efficient, and Reliable Blockchain-As-A-Service for HPC Systems, in Proceedings of International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2021), St. Louis, MO, November, 2021 (Acceptance rate: 86/365=23.6%). -
SC 2021 (top-cs, top-cr)
Yiduo Wang, Cheng Li, Xinyang Shao, Youxu Chen, Feng Yan, Yinlong Xu, Lunule: An Agile and Judicious Metadata Load Balancer for CephFS, in SC21 Workshop on Data Analysis and Reduction for Big Scientific Data (SC 2021), St. Louis, MO, November, 2021 (Acceptance rate: 86/365=23.6%). -
SC-W 2021 (top-w)
Xinying Wang, Lipeng Wan, Jieyang Chen, Qian Gong, Ben Whitney, Jinzhen Wang, Ana Gainaru, Qing Liu, Norbert Podhorszki, Dongfang Zhao, Feng Yan, Scott Klasky, Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression, in Proceedings of International Conference for High Performance Computing, Networking, Storage and Analysis (DRBSD-7), St. Louis, MO, November, 2021 (6-pages full paper). -
VLDB 2021 (top-cs, top-cr)
Jiawei Wang, Cheng Li, Kai Ma, Jingze Huo, Feng Yan, Xinyu Feng, and Yinlong Xu, AutoGR: Automated Geo-Replication with Fast System Performance and Preserved Application Semantics, in Proceedings of the 47th International Conference on Very Large Data Bases (VLDB 2021), Copenhagen, Denmark, August, 2021 (Acceptance rate: TBD). -
AAAI 2021 (top-cs, top-cr)
Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, and Feng Yan, Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning, in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2021), Virtual, Feb, 2021 (Acceptance rate: 1692/7911=21%). -
AAAI 2021 (top-cs, top-cr)
Hsin-Pai Cheng, Tunhou Zhang, Yixing Zhang, Shiyu Li, Feng Liang, Feng Yan, Meng Li, Vikas Chandra, Hai Li, Yiran Chen, NASGEM: Neural Architecture Search via Graph Embedding Method, in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2021), Virtual, Feb, 2021 (Acceptance rate: 1692/7911=21%). -
ICDE 2021 (top-cr)
Abdullah Al-Mamun, Feng Yan, Dongfang Zhao, SciChain: Blockchain-enabled Lightweight and Efficient Data Provenance for Reproducible Scientific Computing, in Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE 2021), Chania, Crete, Greece, April, 2021 (Short Paper, Acceptance rate: TBD). -
PASC 2021
Feng Li, Dali Wang, Feng Yan, Fengguang Song, X-Composer: Enabling Cross-Environments In-Situ Workflows between HPC and Cloud, in Proceedings of the ACM and CSCS Platform for Advanced Scientific Computing (PASC 2021), University of Geneva, Switzerland, July, 2021 (Acceptance rate: TBD). -
ITNG 2021
Adam Cassell, Andrew Munoz, Brianna Blain-Castelli, Nikkolas Irwin, Feng Yan, Sergiu Dascalu, and Frederick C Harris, CARS: A Containerized Amazon Recommender System, in Proceedings of the 18th International Conference on Information Technology: New Generations (ITNG 2021), Las Vegas, NV, USA, April, 2021 (Best Student Paper Award). -
ICSE-W 2021 (top-w)
Chengru Yang, Zhehao Li, Chaoyi Ruan, Guanbin Xu, Cheng Li, Ruichuan Chen, Feng Yan, PerfEstimator: A Generic and Extensible Performance Estimator for Data Parallel DNN Training, in ICSE21 Workshop on Cloud Intelligence(ICSE Workshops 2021), Madrid, Spain, May, 2021 (6 pages long paper). -
INFOCOM-W 2021 (top-w)
Md Kamran Chowdhury Shisher, Heyang Qin, Lei Yang, Feng Yan, and Yin Sun, The Age of Correlated Features in Supervised Learning based Forecasting, in IEEE INFOCOM Age of Information Workshop (INFOCOM Workshops 2021), Virtual Conference, May, 2021. -
Preprint 2021
Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, Feng Yan, Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX , preprint 2021. -
SC 2020 (top-cs, top-cr)
Ahsan Ali*, Riccardo Pinciroli*, Feng Yan, Evgenia Smirni, BATCH: Machine Learning Inference Serving on Serverless Platforms with Adaptive Batching, in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2020), Atlanta, GA, USA, Nov, 2020 (*Equal Contribution and Co-First Authors, Acceptance rate: 85/380=22%). -
SC 2020 (top-cs, top-cr)
Amirhesam Yazdi, Xing Lin, Lei Yang, Feng Yan, SEFEE: Lightweight Storage Error Forecasting in Large Scale Enterprise Storage Systems, in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2020), Atlanta, GA, USA, Nov, 2020 (Acceptance rate: 85/380=22%). -
SIGKDD 2020 (top-cs, top-cr)
Wei Wen, Feng Yan, Yiran Chen, Hai Li, AutoGrow: Automatic Layer Growing in Deep Convolutional Networks, in Proceedings of the 2020 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2020), San Diego, CA, August, 2020 (Research Track, Oral Presentation, Acceptance rate: 216/1279=16.8%), Code. -
USENIX ATC 2020 (top-cs, top-cr)
Chengliang Zhang, Suyi Li, Junzhe Xia, Wei Wang, Feng Yan, Yang Liu, BatchCrypt: Efficient Homomorphic Encryption for Cross-Silo Federated Learning, in Proceedings of the 2020 USENIX Annual Technical Conference (USENIX ATC 2020), Boston, MA, USA, July, 2020 (Acceptance rate: 65/348=18.6%). -
HPDC 2020 (top-cs, top-cr)
Zheng Chai*, Ahsan Ali*, Syed Zawad*, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng, TiFL: A Tier-based Federated Learning System, in Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020), Stockholm, Sweden, June, 2020 (*Equal Contribution and Co-First Authors, Full paper, Acceptance rate: 16/71=22%). -
FAST 2020 (top-cs, top-cr)
Ao Wang, Jingyuan Zhang, Xiaolong Ma, Ali Anwar, Lukas Rupprecht, Dimitrios Skourtis, Vasily Tarasov, Feng Yan, Yue Cheng, InfiniCache: Exploiting Ephemeral Serverless Functions to Build a Cost-Effective Memory Cache, in Proceedings of the 18th USENIX Conference on File and Storage Technologies (FAST 2020), Santa Clara, CA, USA, Feb, 2020 (Acceptance rate: 23/138=16.7%). -
IPDPS 2020 (top-cr)
Jun Yi, Chengliang Zhang, Wei Wang, Cheng Li, Feng Yan, Not All Explorations Are Equal: Harnessing Heterogeneous Profiling Cost for Efficient MLaaS Training, in Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS 2020), New Orleans, LA, USA, May, 2020 (Acceptance rate: 110/446=24.7%). -
AAAI 2020 (Oral) (top-cs, top-cr)
Tunhou Zhang, Hsin-Pai Cheng, Zhenwen Li, Feng Yan, Chengyu Huang, Hai Li, Yiran Chen, AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture, in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, USA, Feb, 2020 (Oral Presentation, Paper acceptance rate: 1591/7737=20.6%, Oral acceptance rate: 453/7737=5.9%). -
AAAI 2020 (Oral) (top-cs, top-cr)
Xinying Wang, Timothy Tawose, Feng Yan, Dongfang Zhao, HDK: Toward High-Performance Deep-Learning-Based Kirchhoff Analysis, in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2020 (Oral)), New York, NY, USA, Feb, 2020 (Oral Presentation, Paper acceptance rate: 1591/7737=20.6%, Oral acceptance rate: 453/7737=5.9%). -
IoT 2020 (top journal, impact factor: 9.515)
Heyang Qin, Syed Zawad, Yanqi Zhou, Lei Yang, Sanjay Padhi, Feng Yan, Reinforcement Learning Empowered MLaaS Scheduling for Serving Intelligent Internet of Things, in IEEE Internet of Things Journal (IoT 2020). -
TBD 2020 (top journal, impact factor: 5.67)
Xinying Wang, Cong Xu, Ke Wang, Feng Yan, Dongfang Zhao, Memory Scaling of Cloud-based Big Data Systems: A Hybrid Approach, in IEEE Transactions on Big Data (IEEE TBD 2020). -
TCC 2020 (top journal, impact factor: 5.967)
Chengliang Zhang, Minchen Yu, Wei Wang, Feng Yan, Enabling Cost-Effective, SLO-Aware Machine Learning Inference Serving on Public Cloud, in IEEE Transactions on Cloud Computing (TCC 2020). -
TNSM 2020 (top journal, impact factor: 4.682)
Riccardo Pinciroli, Ahsan Ali, Feng Yan, Evgenia Smirni, CEDULE+: Resource Management for Burstable Cloud Instances Using Predictive Analytics, in IEEE Transactions on Network and Service Management (TNSM 2020), 2020. -
TMC 2020 (top journal, impact factor: 4.474)
Lixing Yu, Ming Li, Wenqiang Jin, Yifan Guo, Qianlong Wang, Feng Yan, Pan Li, STEP: A Spatio-Temporal Fine-Granular User Traffic Prediction System for Cellular Networks, in IEEE Transactions on Mobile Computing (TMC 2020). -
CVPR-W 2020 (top-w)
Huanrui Yang, Minxue Tang, Wei Wen, Feng Yan, Daniel Hu, Ang Li, Hai Li, Yiran Chen, Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification, in Joint Workshop on Efficient Deep Learning in Computer Vision (CVPR Workshops 2020), Seattle, WA, USA, June, 2020. -
Preprint 2020
Hsin-Pai Cheng, Feng Liang, Meng Li, Bowen Cheng, Feng Yan, Hai Li, Vikas Chandra, Yiran Chen, ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition , preprint 2020. -
Preprint 2020
Xinying Wang, Olamide Timothy Tawose, Feng Yan, Dongfang Zhao, Distributed Nonblocking Commit Protocols for Many-Party Cross-Blockchain Transactions, preprint 2020. -
Preprint 2020
Feng Li, Dali Wang, Feng Yan, Fengguang Song, ElasticBroker: Combining HPC with Cloud to Provide Realtime Insights into Simulations, preprint 2020. -
SC 2019 (top-cs, top-cr)
Heyang Qin, Syed Zawad, Yanqi Zhou, Lei Yang, Dongfang Zhao, Feng Yan, Swift Machine Learning Model Serving Scheduling: A Region Based Reinforcement Learning Approach, in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2019), Denver, CO, USA, Nov, 2019 (Acceptance rate: 78/344=22%). -
USENIX ATC 2019 (top-cs, top-cr)
Chengliang Zhang, Minchen Yu, Wei Wang, Feng Yan, MArk: Exploiting Cloud Services for Cost-Effective, SLO-Aware Machine Learning Inference Serving, in Proceedings of the 2019 USENIX Annual Technical Conference (USENIX ATC 2019), Renton, WA, USA, July, 2019 (Acceptance rate: 71/356=20%). -
EuroSys 2019 (top-cs, top-cr)
Connor Holmes, Daniel Mawhirter, Yuxiong He, Feng Yan, Bo Wu, GRNN: Low-Latency and Scalable RNN Inference on GPUs, in Proceedings of the 14th European Conference on Computer Systems (EuroSys 2019), Dresden, Germany, March, 2019 (Acceptance rate: 45/207=21%). -
Middleware 2019 (top-cr)
Ahsan Ali, Riccardo Pinciroli, Feng Yan, Evgenia Smirni, It’s not a Sprint, it’s a Marathon: Stretching Multi-resource Burstable Performance in Public Clouds, in Proceedings of the ACM/IFIP/USENIX Middleware 2019 (Middleware 2019) , Davis, CA, USA, December, 2019 (Industry track, acceptance rate: 32%). -
BMVC 2019 (top-cr)
Yanqi Zhou, Peng Wang, Sercan Arik, Haonan Yu, Syed Zawad, Feng Yan, Greg Diamos, EPNAS: Efficient Progressive Neural Architecture Search, in Proceedings of the 2019 30th British Machine Vision Conference (BMVC 2019), Cardiff, UK, September, 2019 (Acceptance rate: 231/815=28%). -
CLOUD 2019 (Best Paper Award) (flagship venue in cloud)
Xinying Wang, Abdullah Al-Mamun, Feng Yan, Dongfang Zhao, BlockLite: Toward Accurate and Effcient Emulation of Public Blockchains in the Cloud, in Proceedings of the 2019 International Conference on Cloud Computing (CLOUD 2019), San Diego, CA, USA, June, 2019 (Best Paper Award, Paper acceptance rate: 26.7%). -
CLOUD 2019 (flagship venue in cloud)
Hsin-Pai Cheng*, Patrick Yu*, Haojing Hu*, Syed Zawad*, Feng Yan, Shiyu Li, Hai Li, Yiran Chen, Towards Decentralized Deep Learning with Differential Privacy, in Proceedings of the 2019 International Conference on Cloud Computing (CLOUD 2019), San Diego, CA, USA, June, 2019 (*Equal Contribution and Co-First Authors, Acceptance rate: 26.7%). -
ICCV-W 2019 (top-w)
Hsin-Pai Cheng, Tunhou Zhang, Yukun Yang, Feng Yan, Harris Teague, Hai Li, Yiran Chen, MSNet: Structural Wired Neural Architecture Search for Internet of Things, in Proceedings of ICCV 2019 Neural Architects Workshop , Seoul, Korea, Oct, 2019. -
AGU 2019
Jingting Huang, Amir Ghasemkhani, Sandra Marcela Loria Salazar, Feng Yan, Lei Yang, Evgenia Smirni, Jens Redemann, Heather Holmes, Using Novel Machine Learning Algorithms to Improve the Spatiotemporal Coverage of Satellite Aerosol Optical Depth, in AGU Fall Meeting 2019 (AGU 2019), San Francisco, CA, USA, Dec, 2019. -
ITNG 2019
Syed Zawad, Feng Yan, Rui Wu, Lee Barford, Frederick C Harris, Randomized Benchmarking of Quantum Gates on a GPU, in 16th International Conference on Information Technology-New Generations (ITNG 2019), Las Vegas, NV, USA, April, 2019. -
Preprint 2019
Hsin-Pai Cheng, Tunhou Zhang, Yukun Yang, Feng Yan, Shiyu Li, Harris Teague, Hai Li, Yiran Chen, SwiftNet: Using Graph Propagation as Meta-knowledge to Search Highly Representative Neural Architectures, preprint 2019. -
CLOUD 2018 (Best Student Paper Award) (flagship venue in cloud)
Xinying Wang, Cong Xu, Ke Wang, Feng Yan, Dongfang Zhao, Toward Cost-effective Memory Scaling in Clouds: Symbiosis of Virtual and Physical Memory, in Proceedings of the 10th IEEE International Conference on Cloud Computing (IEEE CLOUD 2018), San Francisco, CA, USA, July, 2018 (Best Student Paper Award (1 out of 300+), Paper acceptance rate: 20%) News. -
ICDCS 2018 (top-cr)
Chengliang Zhang, Huangshi Tian, Wei Wang, Feng Yan, Stay Fresh: Speculative Synchronization for Fast Distributed Machine Learning , in Proceedings of the 38th IEEE International Conference on Distributed Computing Systems (ICDCS 2018), Vienna, Austria, July, 2018 (Acceptance rate: 78/378=20%). -
ICAC 2018 (top-cr)
Ahsan Ali, Riccardo Pinciroli, Feng Yan, Evgenia Smirni, CEDULE: A Scheduling Framework for Burstable Performance in Cloud Computing, in Proceedings of the 15th IEEE International Conference on Autonomic Computing (ICAC 2018), Trento, Italy, September, 2018 (Acceptance rate: 15/49=30%). -
TNSM 2018 (top journal, impact factor: 4.682)
Feng Yan, Yuxiong He, Olatunji Ruwase, Evgenia Smirni, Efficient Deep Neural Network Serving: Fast and Furious, in IEEE Transactions on Network and Service Management (TNSM 2018), 2018. -
NIPS-W 2018 (top-w)
Hsin-Pai Cheng*, Yuanjun Huang*, Xuyang Guo*, Feng Yan, Yifei Huang, Wei Wen, Hai Li, Yiran Chen, Differentiable Fine-grained Quantization for Deep Neural Network Compression, in Proceedings of NIPS 2018 Workshop on Compact Deep Neural Networks with Industrial Applications (CDNNRIA) , Montreal, Canada, Dec, 2018 (*Equal Contribution and Co-First Authors, Spotlight Presentation). -
NIPS-W 2018 (top-w)
Hsin-Pai Cheng*, Patrick Yu*, Haojing Hu*, Feng Yan, Shiyu Li, Hai Li, Yiran Chen, LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning, in Proceedings of NIPS 2018 Workshop on Privacy Preserving Machine Learning (PPML) , Montreal, Canada, Dec, 2018 (*Equal Contribution and Co-First Authors). -
CoDA 2018
Panika Valecha, Huiping Cao, Qixu Gong, Mai Zheng, Feng Yan, Xing Lin, and Art Harkin, Analysis and Prediction of Storage Error Events for High Performance Computing Systems, at Department of Energy (DOE) Conference on Data Analysis (CoDA 2018), Santa Fe, NM, USA, March, 2018. -
Preprint 2018
Wei Wen, Yandan Wang, Feng Yan, Cong Xu, Yiran Chen, Hai Li, SmoothOut: Smoothing Out Sharp Minima for Generalization in Large-Batch Deep Learning, preprint 2018, Code. -
NIPS 2017 (Oral) (top-cs, top-cr)
Wei Wen, Cong Xu, Feng Yan, Chunpeng Wu, Yandan Wang, Yiran Chen, Hai Li, TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning, in Proceedings of the Neural Information Processing Systems 2017 (NIPS 2017), Long Beach, CA, USA, Dec, 2017 (Oral Presentation, Oral acceptance rate: 40/3240=1.2%, Paper acceptance rate: 20% ) In Official Pytorch, Github, Video, Poster. -
Middleware 2017 (top-cr)
Jeff Rasley, Yuxiong He, Feng Yan, Olatunji Ruwase, Rodrigo Fonseca, HyperDrive: Exploring Hyperparameters with POP Scheduling, in Proceedings of the ACM/IFIP/USENIX Middleware 2017 (Middleware 2017), Las Vegas, NV, USA, Dec, 2017 (Acceptance rate: 20/85=23%). -
CLOUD 2017 (flagship venue in cloud)
Feng Yan, Lihua Ren, Daniel Dubois, Giuliano Casale, Jiawei Wen, Evgenia Smirni, How to Supercharge the Amazon T2: Observations and Suggestions , in Proceedings of the 10th IEEE International Conference on Cloud Computing (CLOUD 2017), Honolulu, Hawaii, USA, June, 2017 (Acceptance rate: 18%). -
TCC 2017 (top journal, impact factor: 5.967)
Feng Yan, Ludmila Cherkasova, Zhuoyao Zhang, Evgenia Smirni, DyScale: a MapReduce Job Scheduler for Heterogeneous Multi-core Processors, in IEEE Transactions on Cloud Computing (TCC 2017), 2017. -
SOSP-W 2017 (top-w)
Jeff Rasley, Yuxiong He, Feng Yan, Olatunji Ruwase, Rodrigo Fonseca, HyperDrive: Flexible and Efficient Parallel Hyperparameter Exploration, in Proceedings of Workshop on AI Systems at Symposium on Operating Systems Principles (SOSP 2017), Shanghai, China, Oct, 2017. -
SC 2016 (top-cs, top-cr)
Feng Yan, Yuxiong He, Olatunji Ruwase, Evgenia Smirni, SERF: Efficient Scheduling for Fast Deep Neural Network Serving via Judicious Parallelism, in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2016), Salt Lake City, USA, Nov, 2016 (Acceptance rate: 82/446=18%, Cloud Track Acceptance rate: 8%). -
TOMPECS 2016 (top journal, impact factor: TBD)
Feng Yan, Xenia Mountrouidou, Alma Riska, Evgenia Smirni, PREFiguRE: an Analytic Framework for HDD Management, in ACM Transaction on Modeling and Performance Evaluation of Computing Systems (TOMPECS 2016), 2016. -
Cluster Computing 2016 (journal, impact factor: 1.851)
Ji Xue, Feng Yan, Alma Riska, Evgenia Smirni, Scheduling Data Analytics Work with Performance Guarantees: Queuing and Machine Learning Models in Synergy, in Proceedings of the Cluster Computing Journal (Cluster Computing 2016), 2016. -
NOMS-D 2016
Feng Yan, Evgenia Smirni, Workload Interleaving with Performance Guarantees in Data Centers, in Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS 2016). -
SIGKDD 2015 (Oral) (top-cs, top-cr)
Feng Yan, Olatunji Ruwase, Yuxiong He, Trishul Chilimbi, Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems, in Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2015), Sydney, Australia, August, 2015 (Oral Presentation, Acceptance rate: 19%). -
CNSM 2015
Ji Xue, Feng Yan, Robert Birke, Lydia Y. Chen, Thomas Scherer, Evgenia Smirni, PRACTISE: Robust Prediction of Data Center Time Series, in Proceedings of the 11th International Conference on Network and Service Management (CNSM 2015), Barcelona, Spain, November, 2015 (Acceptance rate: 18/102=17%). -
CAC 2015 (top-cr)
Ji Xue, Feng Yan, Alma Riska, Evgenia Smirni, Proactive Management of Systems via Hybrid Analytic Techniques, in Proceedings of 2015 IEEE International Conference on Cloud and Autonomic Computing (CAC 2015), Cambridge, MA, September, 2015 (Acceptance rate: 33%). -
UCC-D 2015
Thomas Scherer, Ji Xue, Feng Yan, Robert Birke, Lydia Y. Chen, Evgenia Smirni, PRACTISE – Demonstrating a neural network based framework for robust prediction of data center workload, in IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2015), Limassol, Cyprus, December, 2015. -
CLOUD 2014 (flagship venue in cloud)
Feng Yan, Ludmila Cherkasova, Zhuoyao Zhang, Evgenia Smirni, Optimizing Power and Performance Trade-offs of MapReduce Job Processing with Heterogeneous Multi-Core Processors , in Proceedings of the 7th IEEE International Conference on Cloud Computing (CLOUD 2014), Alaska, USA, June, 2014, (Acceptance rate: 18%). -
ICAC 2014 (top-cr)
Ji Xue, Feng Yan, Alma Riska, Evgenia Smirni, Model-Based Storage Tiering for Smooth System Operation , in Proceedings of the 11th International Conference on Autonomic Computing (ICAC 2014), Philadelphia, PA, June, 2014, (Acceptance rate: 22%). -
NOMS 2014 (top-cr)
Feng Yan, Ludmila Cherkasova, Zhuoyao Zhang, Evgenia Smirni, Heterogeneous Cores For MapReduce Processing: Opportunity or Challenge? , in Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS 2014), Krakow, Poland, May, 2014. -
ICPE 2014
Feng Yan, Shannon Hughes, Alma Riska, Evgenia Smirni, Agile Middleware for Scheduling: Meeting Competing Performance Requirements of Diverse Tasks , in Proceedings of the 5th ACM/SPEC International Conference on Performance Engineering (ICPE 2014), Dublin, Ireland, March, 2014, (Acceptance rate: 30%). -
MASCOTS 2013 (top-cr)
Feng Yan, Shannon Hughes, Alma Riska, Evgenia Smirni, Overcoming Limitations of Off-the-shelf Priority Schedulers in Dynamic Environments , in Proceedings of the 21th ACM/IEEE Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2013), San Francisco, CA, August, 2013, IEEE Press (Acceptance rate: 27%). -
ICAC-P 2013
Feng Yan, Xenia Mountrouidou, Alma Riska, Evgenia Smirni, Toward Automating Disk Power Savings with Performance Guarantees , in ICAC 2013 Ph.D. Forum (in conjunction with ATC 2013), San Jose, CA, June, 2013. -
STC 2013
Feng Yan, Xenia Mountrouidou, Alma Riska, Evgenia Smirni, PREFiguRE: a Performance, Power, and Reliability Framework for Disk Drives, in the IEEE Computer Society Special Technical Community on Sustainable Computing (STC), Volume 2, Issue 2, April, 2013. -
HotPower 2012 (top-w)
Feng Yan, Xenia Mountrouidou, Alma Riska, Evgenia Smirni, Quantitative Estimation of the Performance Delay with Propagation Effects in Disk Power Savings , in HotPower 2012 (in conjunction with OSDI 2012), Hollywood, CA, October, 2012 (Acceptance rate: 25%). -
ICAC 2012 (top-cr)
Feng Yan, Alma Riska, Evgenia Smirni, Toward Fast Eventual Consistency with Performance Guarantees , in Proceedings of the 9th International Conference on Autonomic Computing (ICAC 2012), San Jose, CA, September, 2012, ACM, pp. 167-171. -
ICAC-P 2012
Feng Yan, Alma Riska, Evgenia Smirni, Toward Fast Eventual Consistency with Performance Guarantees , Poster, the 9th International Conference on Autonomic Computing (ICAC 2012), San Jose, CA, September, 2012. -
ICDCSW 2012 (top-w)
Feng Yan, Alma Riska, Evgenia Smirni, Fast Eventual Consistency with Performance Guarantees for Distributed Storage , in Proceedings of the 32nd International Conference on Distributed Computing Systems Workshops, IEEE Computer Society, pp.23-28, in DCPerf 2012 (in conjunction with ICDCS 2012), Macau, China, June, 2012, pp. 23-28 (Invited paper). -
ICPE 2012
Feng Yan, Alma Riska, Evgenia Smirni, Busy Bee: How to Use Traffic Information for Better Scheduling of Background Tasks , in Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering (ICPE 2012) , Boston, USA, April, 2012, ACM, pp.145-156 (Acceptance rate: 28%). -
SIGMETRICS-W 2011 (top-w)
Feng Yan, Xenia Mountrouidou, Alma Riska, Evgenia Smirni, Copy Rate Synchronization with Performance Guarantees for Work Consolidation in Storage Clusters , in Proceedings of the ACM SIGMETRICS Performance Evaluation Review (PER), Volume 39, Issue 3, in GreenMetrics 2011 (in conjunction with SIGMETRICS 2011), San Jose, CA, June, 2011. -
MASCOTS 2011 (top-cr)
Feng Yan, Xenia Mountrouidou, Alma Riska, Evgenia Smirni, Toward Automating Work Consolidation with Performance Guarantees in Storage Clusters , in Proceedings of the 19th ACM/IEEE Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2011), Singapore, July, 2011, IEEE Press, pp.326-335 (Acceptance rate: 26%).