- Machine Learning Driven Cloud Resource Management
Keynote talk at MLSys’22 Workshop on Cloud Intelligence - Machine Learning Driven Cloud Resource Management
Invited talk at MLSys’22 Workshop on Practical Adoption Challenges of ML for Systems in Industry - INFaaS: Automated Model-less Inference Serving
Topics in AI Webinar at the Industry-Academia Partnership (IAP), December 2021 - Model-less Inference Serving for ease-to-use and cost-efficiency
Keynote talk at ICML’21 Workshop on ML deployment - Research in Machine Learning for Systems: Insights and Guidelines
IBM Research, Almaden, November 20 - Machine Learning for Resource Management
Chalmers AI Research Centre, Chalmers University of Technology, Gothenberg, Sweden, May 2019 - A Case for Managed and Model-less Inference Serving
The 17th workshop on Hot Topics in Operating Systems (HotOS’19), Bertinoro, Italy, May 15th, 2019 - Model-based Resource Allocation in the Public Cloud
Platforms Lab Seminar, Stanford, CA, January 2019 - Research in Machine Learning for Systems: Insights and Guidelines
Invited Speaker at Workshop on ML for Systems at NeurIPS 2018, December 8th, 2018 - Machine Learning for Resource Management in the Datacenter and the Cloud
Lawrence Berkeley National Lab, Berkeley, CA, January 2018 - Machine Learning for Resource Management in the Datacenter and the Cloud
Platforms Lab, Stanford, CA, November 2017 - Machine Learning for Resource Management in the Datacenter and the Cloud
Microsoft Research, Redmond, WA, November 2017 - Selecting the Best VM across Multiple Public Clouds: A Data-Driven Performance Modeling Approach
ACM Symposium on Cloud Computing (SoCC), Santa Clara, CA, September 2017 - Selecting the Best VM across Multiple Public Clouds using PARIS: A Data-Driven Performance Modeling Approach
RISELab/VMware Day, Berkeley, CA, May 2017 - Selecting the Best VM across Multiple Public Clouds using PARIS: A Data-Driven Performance Modeling Approach
Google, Mountain View, CA, May 2017 - Data-Driven Modeling for Cloud-Hosted Systems’ Management and Optimization
Smule, San Francisco, CA, Jan 2017 - Let your Workloads Choose your VMs in the Cloud using PARIS
RISELab Winter Retreat, Berkeley, CA, Jan 2017 - Data-Driven Modeling for Cloud Management and Optimization
Splunk, San Francisco, CA, July 2016 - Data-Driven Modeling for System Management and Optimization
SAP Dublin, CA, June 2016 - PARIS: Model Based Performance Estimation Across the Cloud
AMPLab Summer Retreat June 2016 - Managing Sample Bias in a Model-Based Cluster Resource Manager
AMPLab Summer Retreat June 2016 - The Judgement of PARIS: Performance-Aware Resource Inference System
Microsoft Research, Redmond, Intern Talk, August 2015 and AMPLab Winter Retreat, January 2016 - Faster Jobs in Distributed Processing Systems using Machine Learning
Department Seminar, Department of Computer Science and Automation (CSA), Indian Institute of Science (IISc), May 2015 - Faster Jobs in Distributed Data Processing using Multi-Task Learning
SIAM International Conference on Data Mining (SDM), April 2015 - Wrangler: Predictable and Faster Jobs using Fewer Resources
ACM Symposium on Cloud Computing (SoCC), November 2014 - Wrangler: A Machine Learning Approach for Straggler Avoidance
AMPLab Summer Retreat, May 2014 and AMPLab All Hands 2014 - Zone Localization Methods and Services
Software Defined Buildings (SDB) Winter Retreat, Jan 2014 - Discovery of Application Workloads from Network File Traces
Usenix Conference on File and Storage Technologies (FAST) Feb 2010 and Riverbed Technology, Feb 2010
