8:30 AM
In-Person Agenda
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Monday, September 18
8:30 AM
Breakfast and Networking
Rayground
9:30 AM
Keynote, Day 1
Robert Nishihara — Co-founder and CEO, Anyscale
Ion Stoica — Executive Chairman and President, Anyscale, Professor, UC Berkeley
Ya Xu — VP of Engineering, Head of Data and AI, LinkedIn
John Schulman — Co-founder, OpenAI
Sidney Rabsatt — Head of Product, Anyscale
Justin Boitano — VP of Enterprise Products, NVIDIA
Dr. Ameer Haj Ali — Head of Cloud Infrastructure and Platform Engineering, Anyscale
11:30 AM
Lunch and Networking Break
Rayground
11:30 AM
Rayground Open/Expo
Rayground
11:45 AM
GenAI for Enterprises—Practical Considerations From Pilot to Scale
Kannan Keeranam — Director of AI Strategic Engagements, Intel
12:00 PM
Running ML Workloads with AWS Purpose Build ML Accelerators and Ray
Matthew McClean — Sr Manager, AWS
12:15 PM
Developing Ray Applications on Google Cloud TPUs
Allen Wang — Software Engineer, Google
Alex Spiridonov — Group Product Manager, Google
12:30 PM
Standing Up Ray Clusters in the Blink of an AI to Drive Private AI
Chris Wolf — Vice President, VMware AI Labs, VMware
1:00 PM
1:00 PM
Building Samsara's Machine Learning Platform with Ray
Pang Wu, Samsara
Saurabh Tripathi, Samsara
Sharan Srinivasan, Samsara
1:00 PM
1:00 PM
From Good to Great: Elevating DoorDash Model Training with Ray
Swaroop Chitlur, DoorDash
Dhaval Shah, DoorDash
1:00 PM
Building Context-Aware Reasoning Applications with LangChain and LangSmith
Harrison Chase, LangChain
1:00 PM
Enterprise Vector-based Information Retrieval & Prompt Engineering at Scale using Open Source on AWS
Vedant Jain, Amazon Web Services
1:00 PM
The Interactive Roadmap Experience Part 1 of 2: Focus on Anyscale
Matt Connor, Anyscale
Robin Singh, Anyscale
Siddharth Venkatesh, Anyscale
Sidney Rabsatt, Anyscale
1:30 PM
Break
Rayground
1:45 PM
Embeddings and Vectors are the Key to Production AI
Jeff Huber, Chroma
1:45 PM
1:45 PM
Ray, Knative, and Running Serverless Workloads in the Cloud
Paul Schweigert, IBM
Michael Maximilien, IBM
1:45 PM
Practical Data Considerations for Building Production-Ready LLM Applications
Jerry Liu, LlamaIndex
1:45 PM
From Spark to Ray: An Exabyte-Scale Production Migration Case Study
Patrick Ames, Amazon
1:45 PM
Making your Enterprise GenAI Ready and GenAI Enterprise Ready
Ali Arsanjani, Google
1:45 PM
Managed Cloud Infrastructure for LLMs
Yifei Feng, Anyscale
Allen Yin, Anyscale
Bruce Zhang, Anyscale
Lanbo Chen, Anyscale
2:15 PM
Break
Rayground
2:30 PM
Last Mile Data Processing for ML Training using Ray
Chia-Wei Chen, Pinterest
Qingxian Lai, Pinterest
Raymond Lee, Pinterest
2:30 PM
Hyperparameter Tuning with Ray[Tune] for Next-Gen Training Platform at LinkedIn
Wei-Yu Yen, Linkedin
2:30 PM
The Different Shades of using KubeRay with Kubernetes
Ali Kanso, Microsoft
2:30 PM
Advances in Foundation Models — Technology, Society, and Applications
Dr. Percy Liang, Stanford
2:30 PM
Developing and Serving RAG-Based LLM Applications in Production
Philipp Moritz, Anyscale
Goku Mohandas, Anyscale
2:30 PM
Automatically scaling the execution of Foundation Models workflows: Ray with CodeFlare and Red Hat OpenShift Data Science Pipelines
Yuan-Chi Chang, IBM
Alex Corvin, Red Hat
2:30 PM
Fast, Flexible, and Scalable Data Loading for ML Training with Ray Data
Stephanie Wang, Anyscale
Scott Lee, Anyscale
3:00 PM
Break
Rayground
3:00 PM
On-Demand Ray Clusters in ML Workflows via KubeRay & Sematic
Josh Bauer, Sematic (sematic.dev)
3:15 PM
Building Production AI Applications with Ray Serve
Shreyas Krishnaswamy, Anyscale
Edward Oakes, Anyscale
3:15 PM
Gorilla: Large Language Models Connected with Massive APIs
Shishir G Patil, UC Berkeley
3:15 PM
A Ray-based ML Platform for Early Cancer Detection
Zachary Carrico, Freenome
3:15 PM
Large Scale Pathways Recommender Systems (PaRS) at Verizon
Luyang Wang, Verizon
Xuning (Mike) Tang, Verizon
3:15 PM
Optimizing LLM Training with Airbnb's Next-Gen ML Platform
Shaowei Su, Airbnb
3:15 PM
Ray Train: A Production-Ready Library for Distributed Deep Learning
Yunxuan Xiao, Anyscale
3:15 PM
Integrating Ray.io into the Google Cloud Ecosystem for the Enterprise
Ali Arsanjani, Google
3:15 PM
OneDigital ML Platform: Unleashing the Power of Machine Learning at Scale
Paridhi Jha, Wesfarmers OneDigital
3:45 PM
Break
Rayground
4:00 PM
The Interactive Roadmap Experience Part 2 of 2: Focus on Ray and Open Source Projects
Sidney Rabsatt, Anyscale
Richard Liaw, Anyscale
Goku Mohandas, Anyscale
4:00 PM
How Snorkel Builds Interactive Enterprise ML Products Using Ray
Will Hang, Snorkel AI
John Allard, OpenAI
4:00 PM
Llama, Scaling Up LLMs in an Open Ecosystem
Joseph Spisak, Meta
4:00 PM
KubeRay: A Ray cluster management solution on Kubernetes
Kai-Hsun Chen, Anyscale
Archit Kulkarni, Anyscale
4:30 PM
Extended Networking Break
Rayground
4:30 PM
Making it easy to provision Ray clusters to support enterprise AI/ML efforts
Chris Van Dyke — Principal Product Manager, Cloudera
4:45 PM
Bridging MLOps and LLMOps: Integrating Governed Generative AI into your Enterprise
Ahmet Gyger — Senior Director, Product Management, Domino Data Lab
5:00 PM
Community Bash (Networking)
Rayground
5:00 PM
Decentralized Ray - Scaling Ray for Global Inference
Ahmad Shadid — Co-Founder & CTO, io.net
Matej Tomazin — Co-Founder & COO, Antbit.io
5:15 PM
Ray Serve for IOT at Samsara
Brian Westphal — Senior Machine Learning Engineer, Samsara
5:30 PM
Real-Time Vectorization for Transactional Workloads with MongoDB Atlas + Anyscale
Sigfrido Narvaez — Executive Solutions Architect, MongoDB
5:45 PM
Building an Instant-On Serverless Platform for Large-Scale Data Processing Using Ray
Japson Jeyasekaran — Sr Software Engineer, AWS
Harish Sitaraman — Software Development Manager, AWS
6:00 PM
Parallel inferencing with KServe Ray integration
Ted Chang — Software Engineer, IBM
Jim Busche — Software Engineer, IBM
6:15 PM
Unleashing the Power of GenAI: Scaling with Ray and Orchestrating with Kubernetes
Apoorva Kulkarni — Sr. Specialist Solutions Architect, AWS
6:30 PM
TimeGPT: A Foundation Large Time Series Model
Azul Garza — CTO, Nixtla
Max Mergenthaler — CEO & Co-Founder, Nixtla
Tuesday, September 19
8:30 AM
Breakfast and Networking
Rayground
9:00 AM
Keynote, Day 2
Albert Greenberg — VP of Engineering, Uber
Brian McClendon — Senior Vice President of Engineering, Niantic, Inc
Hien Luu — Senior Engineering Manager, DoorDash
Zhitao Li — Principal Software Engineer/Tech Lead Manager, Uber
Ben Horowitz — Co-founder and General Partner, Andreessen Horowitz
Se Won Jang — Engineering Manager, ML Data Platform, Pinterest
Robert Nishihara — CEO, Anyscale
Alex Spiridonov — Group Product Manager, Google
Allen Wang — Software Engineer, Google
Ersin Yumer — Sr. Director, AI/ML Platform and Data, Adobe
Rich Heaton — Director Neuron Software (Inferentia and Trainium), AWS
11:00 AM
Building Next Generation AI Infrastructure on Ray
Hien Luu — Senior Engineering Manager, DoorDash
Zhitao Li — Principal Software Engineer/Tech Lead Manager, Uber
Se Won Jang — Engineering Manager, ML Data Platform, Pinterest
Zhe Zhang — Head of Open Source Engineering, Anyscale
11:30 AM
Lunch and Networking Break
Rayground
11:30 AM
Rayground Open/Expo
Rayground
11:45 AM
How to simplify execution of cloud-native model training and validation with CodeFlare: A Hands-On Demo
Mustafa Eyceoz — Software Engineer, Red Hat
Atin Sood — Program Manager - IBM Research, IBM
12:00 PM
Tend and Tune Your MARL Experiments with Ray and Weights & Biases
Anish Shah — Machine Learning Engineer, Weights & Biases
12:15 PM
50x Faster Fine-Tuning in 10 Lines of YAML with Ludwig and Ray
Travis Addair — Chief Technology Officer, Predibase Inc.
12:30 PM
How to Build an AI Copilot for Your Application
Tristan Zajonc — CEO , Continual
12:45 PM
Gismo for Ray: A Multi-Node Shared Memory Object Store That Accelerates Ray Workloads
Charles Fan — Co-Founder & CEO, MemVerge
1:00 PM
SkyPilot: Run AI on Any Cloud
Zongheng Yang, UC Berkeley Sky Computing Lab
1:00 PM
1:00 PM
Deploying Many Models Efficiently with Ray Serve
Sihan Wang, Anyscale
Jon Park, Clari
Cindy Zhang, Anyscale
1:00 PM
AI Factory Accelerating Solutions with Ray
Peter Haddad, Lockheed Martin
1:00 PM
Best Practices for Productionizing Distributed Training with Ray Train
Justin Yu, Anyscale
1:00 PM
Build Augmented Reality Maps With Ray
Qi Zhou, Niantic
1:00 PM
Simplified Training, Tuning and Deployment of Foundational Models as a Service with Red Hat OpenShift AI
Carlos Costa, IBM Research
Taneem Ibrahim, Red Hat
Nick Hill, IBM Research
1:00 PM
Ray Data Streaming for Large-Scale ML Training and Inference
Eric Liang, Anyscale
1:30 PM
Break
Rayground
1:30 PM
Efficient Expert Witness Profiling with Ray: Automated Key Phrase Extraction from Legal Documents
Harshit Singh, LexisNexis
1:45 PM
Scaling up Terascale Deep Learning on Commodity CPUs with ThirdAI and Ray
Anshumali Shrivastava, ThirdAI Corp
1:45 PM
Ray Scalability Deep Dive: The Journey to Support 4,000 Nodes
Yi Cheng, Anyscale
1:45 PM
How Spotify Built a Robust Ray Platform with a Frictionless Developer Experience
David Xia, Spotify
Keshi Dai, Spotify
1:45 PM
Ray-based Horizontally Scalable In-Memory Graph Platform at BASF
Janez Ales, BASF
1:45 PM
1:45 PM
The Ray Dataplane: History and the Cloudsort World Record
Stephanie Wang, Anyscale
Frank Luan, UC Berkeley
1:45 PM
Easily Scale to Production-Ready Generative AI with NVIDIA and Anyscale
Adel El Hallak, NVIDIA AI Enterprise
1:45 PM
Anyscale Workspaces: A Scalable Interactive ML Development Environment with Zero Setup
Sofian Hnaide, Anyscale
2:15 PM
Break
Rayground
2:15 PM
Building a Distributed Query Engine with Ray
Tony Wang, Stanford
2:30 PM
Scaling time-series forecasting models to cope with the multi-verse with Ray
Peyman Tavallali, JP Morgan Chase
2:30 PM
Ray Observability 2.0: How to Debug Your Ray Applications with New Observability Tooling
SangBin Cho, Anyscale
Alan Guo, Anyscale
Chao Wang, Anyscale
2:30 PM
Forecasting Covid Infections for the UK's National Health Service using Ray and Kubernetes
Alex Remedios, treebeardtech
2:30 PM
Python-centric AI Application Building in Minutes with Lepton and Ray
Yangqing Jia, Lepton AI
2:30 PM
2:30 PM
Faster and Cheaper Offline Batch Inference with Ray
Amog Kamsetty, Anyscale
Balaji Veeramani, Anyscale
2:30 PM
Perplexity AI: How We Built the World's Best LLM-Powered Search Engine in Six Months, With Less Than $4M Spent
Aravind Srinivas, Perplexity
2:30 PM
3:00 PM
Break
Rayground
3:15 PM
3:15 PM
Modernizing DoorDash Model Serving Platform with Ray Serve
Siddharth Kodwani, DoorDash
Kornel Csernai, DoorDash
3:15 PM
Supercharging self-driving algorithms development with Ray: scaling simulation workloads and democratizing autotuning at Zoox
Yunpeng Pan, Zoox
Ritwik Bera, Zoox
3:15 PM
How Ray Empowered Ant Group to Deliver a Large-Scale Online Serverless Platform
Chong Li, Ant Group
Guyang Song, Ant Group
3:15 PM
3:15 PM
Open Source LLMs: Viable for Production or a Low-Quality Toy?
M Waleed Kadous, Anyscale
3:15 PM
FlightAware and Ray: Scaling Distributed XGBoost and Parallel Data Ingestion
Patrick Dolan, FlightAware
3:15 PM
Intellectual Property with GenAI: What LLM Developers Need to Know
Justin Olsson, Anyscale
3:45 PM
Break
Rayground
4:00 PM
Deploying Ray Cluster on an Air-Gapped Kubernetes Cluster with Tight Security Control: Challenges and Best Practices
Yiqing Wang, Instabase
Ruoyu Huang, Instabase
4:00 PM
Redesigning Scheduling in Ray to Improve Cost-Efficiency at Scale
Jiajun Yao, Anyscale
4:00 PM
Scaling AI Health Assistants: Challenges and Solutions
Joshua Albert, Touch Medical Intelligence Inc.
4:00 PM
NLP And The Future of Search With You.com
Bryan McCann, You.com
4:00 PM
Understanding the Landscape of the Latest Large Models
Chris Van Pelt, Weights and Biases
4:00 PM
4:00 PM
Semiconductor Fab Production Scheduling Using Deep Reinforcement Learning
Jasper van Heugten, minds.ai
4:00 PM
Large Language-Style Universal Models for Short Video Recommendations
Dinesh Ramasamy, Verse Innovation
Wednesday, September 20
9:00 AM
Introduction to Ray AI Libraries for Deep Learning
Emmy Li — Technical Trainer, Anyscale
9:00 AM
Learn How to Build and Productionize LLM-Powered Applications with Ray and Anyscale
Adam Breindel — Technical Trainer, Anyscale
9:00 AM
Implementing a production MLOps pipeline to deliver end-to-end ML applications at scale
Goku Mohandas — AI Education Lead, Anyscale
1:00 PM
GenAI - Fine-tuning and Deploying Stable Diffusion Models with Ray and Anyscale
Emmy Li — Technical Trainer, Anyscale
1:00 PM
Real-time ML - Deploying online inference pipelines
Adam Breindel — Technical Trainer, Anyscale
1:00 PM
Practical Data and Evaluation Considerations for Building Production-Ready LLM Applications with LlamaIndex and Ray
Simon Suo — Co-founder and CTO, LlamaIndex
Amog Kamsetty — Software Engineer, Anyscale
Goku Mohandas — AI Education Lead, Anyscale
1:00 PM
Ray Core Deep Dive: API, Architectures, and Best Practices
Jules Damji — Lead Developer Advocate, Ray Team, Anyscale
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