Talks

Joseph E. (Joey) Gonzalez · Professor in EECS, UC Berkeley

Selected talks, most recent first. Slides are linked where available.

A North Star for AI Research in the Era of AGI and Frontier Labs

How academic research can choose directions while frontier labs rapidly advance general-purpose models, guided by the question of what new problems today's solutions will create, with examples from my group's work on systems for AI agents.

  • August 20, 2026: Plenary talk, Workshop on Human-Centered Machine Learning, hosted by Apple, Apple Park, Cupertino. Slides (PDF)
  • May 22, 2026: Invited talk, Samsung Research America AI Summit, Mountain View. Slides (PDF)
  • April 23, 2026: Invited faculty talk, Amazon AI PhD Fellowship Summit, Seattle. Slides (PDF)

Other selected talks

  • May 2026: Keynote, Data Discovery Symposium, UC Berkeley.
  • September 2025: Keynote, Samsung AI Forum (online).
  • 2022: Cloud Intelligence and AIOps Workshop, “The Evolution of Model Deployment from the Cloud to the Sky.”
  • 2022: China Database Committee Conference, “The Co-Evolution of Data and ML Systems from the Cloud to the Sky.”
  • 2021: UC Berkeley Office of the CTO Cloud Computing Meetup, “To the Cloud and Beyond: A Brief View of Cloud Computing Research at UC Berkeley.”
  • 2020: Colloquium, Department of Computer and Information Science, University of Pennsylvania, “Advances in Machine Learning Systems Research.”
  • 2020: Keynote, 14th Annual Machine Learning Symposium, New York Academy of Sciences, “Advances in AI-Systems Research.”
  • 2020: Keynote, ISSCC Forum on Machine Learning Processors, “Hardware Opportunities in the Machine Learning Lifecycle.”
  • 2020: Keynote, Workshop on MLOps at MLSys 2020, “Advances in Prediction Serving Systems.”
  • 2018: Keynote, Data Eng Conference, “Managing the Machine Learning Lifecycle.”
  • 2017: Keynote, SOSP Workshop, “Research at the Intersection of AI and Systems.”
  • 2017: Keynote, AAAI Systems Workshop, “Rise to the Challenges of AI Systems.”
  • 2016: Keynote, ICML Workshop, “Prediction Serving: What Happens After Learning?”
  • 2015: Keynote, NIPS Workshop, “Intelligent Services: Serving Machine Learning Predictions.”
  • 2015: ODSC, “Intelligent Services: Serving Machine Learning Predictions.”
  • 2015: CIDR, “The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox.”
  • 2014: OSDI, “GraphX: Graph Processing in a Distributed Dataflow Framework.”
  • 2014: Annual Meeting of the International Society for Bayesian Analysis (ISBA), “Concurrency Control for Scalable Bayesian Inference.”
  • 2014: Tutorial, International Conference on Machine Learning (ICML), “Emerging Systems for Large-Scale Machine Learning.”
  • 2014: IPDPS, Session on Graph Algorithms Building Blocks, “GraphX: Unifying Table and Graph Analytics.”
  • 2014: NetApp ATG University Day, “Large Scale Graph Analytics: Applications and Systems.”
  • 2014: Keynote, Workshop on Big Graph Mining at WWW, “From Graphs to Tables: The Design of Scalable Systems for Graph Analytics.”
  • 2013: SIAM CSE Minisymposium on Frontiers in Large-Scale Graph Analysis, “Large-Scale Graph-Structured Machine Learning: GraphLab in the Cloud and GraphChi in Your PC.”
  • 2012: OSDI, “PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs.”
  • 2011: IDGA Data Center Consolidation Summit, “GraphLab: A New Parallel Framework for Machine Learning.”
  • 2009: UAI, “Distributed Parallel Inference on Large Factor Graphs.”