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Complete Agenda Overview

 

MLW's HYBRID AI 2026

May 5-6 in San Francisco
 
Prices go up tomorrow, Friday March 20th

AI is everywhere—but real value from AI is still rare. MLW's HYBRID AI 2026 agenda reveals how to obtain the value. Review the sessions below and see which ones correspond with your challenges. 

Agenda Overview

Keynote: Predictive AI’s New Killer App: GenAI’s Reliability Layer
Dr. Eric Siegel, Conference FounderMachine Learning Week

Keynote: The AI-Value Sweet Spot: Blending LLMs with Enterprise ML
Kirk Mettler, Chief Data Scientist and R guyIBM

Hybrid AI for Fraud Detection: Incorporating Generative AI and Machine Learning for Real-World Impact
Dean Abbott, Chief Data ScientistAbbott Analytics


When AI Agents Go Rogue: Unmasking Risky Enterprise AI Behavior with Unsupervised Learning
Millie Huang, Staff Data ScientistSalesforce

Enterprise-Scale GenAI Frameworks: Automating Data Modeling, Validation, and Cloud Provisioning
Vatsal Kishorbhai Mavani, Cloud EngineerCVS Health

From Medical Codes to Cash and Coverage: Risk-Filtered Insurance Claims Automation
Oliver Shetler, Senior Data Scientist, NextGen Healthcare

Hybrid AI in Production at HP: A Reliability Layer that Marries Predictive & GenAI (with Humans-in-the-Loop)
Samaresh Kumar Singh, Principal Engineer, Technology Innovation, HP

Keynote on Generative Architecture: An Imperative for AI Validation in the Architecture, Engineering, and Construction Industry
Julia Ling, Applied AI Leader, X, the moonshot factory

Delivering Hybrid AI with Decision Agents
James Taylor, Executive PartnerBlue Polaris

Taming Non-Determinism: a Framework for Evaluation and Observability in Autonomous Agent Trajectories
Naman Goyal, Machine Learning EngineerGoogle DeepMind

How Twilio Uses Its Own AI Builder to Transform Customer Conversations
Rikki Singh, VP, R&D, Emerging Technology and InnovationTwilio

Validating External Data at Scale: a Solution to the Latest Challenges
James Haney, Senior Manager, Data Science and AnalyticsRepublic Finance

Efficient Cross-Accelerator RLHF: A Service-Oriented Approach to Large-Scale Reinforcement Learning from Human Feedback
Suvendu Mohanty, Sr ML EngineerAmazon

Building Production-Ready LLM Agents: Serverless Architecture Patterns with Model Context Protocol
Sowjanya Pandruju, Cloud Application ArchitectAmazon Web Services

Enterprise Anomaly Detection: Architecting ML Systems for Governance at Scale
Sai Vineeth Kandappa Reddi Gari, Founder

Keynote: Context Engineering: How Machines Remember and Forget

Emre Okcular, Solutions ArchitectOpenAI

Memory Wall for AI
Tejas Chopra, Sr. EngineerNetflix

GenAI for Personalizing Music, Videos, Podcasts and Audiobooks
Tony Jebara, VP of EngineeringSpotify

Predictive AI Breakthrough: Driving Decisions with Expected Value, Not Raw Model Score
Luba Gloukhova, CTOGooder AI

Agent-in-the-Loop: Continuous Learning Flywheel for Fraud Detection
Jiting Xu, Machine Learning EngineerDoorDash

Stress-Testing AI: How CSAA Built an Independent Model Validation Function to Catch Risk Before It Reaches Production
Aaron Simon, Sr. Manager, Independent Model ValidationCSAA Insurance Group
Bipin Chadha, SVP Data ScienceCSAA Insurance (AAA)

Keynote: AI Transformation Hinges on Very Particular Organizational Requirements
Jon Francis, Digital Channel Performance ExecutiveState Farm

EXPERT PANEL: Squeezing Proven Value Out of AI
Dr. John Elder, Founder & ChairElder ResearchSteven Ramirez, CEOBeyond the Arc

Real-Time Scoring, the Best Approach for Taking Advantage of AI within High-Volume Transaction Systems
Jonathan Sloan, IBM LinuxONE Evangelist and Subject Matter ExpertIBM

Scaling AI from POC to Production: Engineering Hybrid Intelligence That Delivers
Rohit Agarwal, Chief AI OfficerBizom

Telemetry-Driven AI: Using Observability to Maintain Model Performance in Hybrid AI Systems
Prashanthi Matam, Senior mlops engineerDiscover Financial Services / Capital One
Venkata Naga Karthik Pidatala, Software EngineerMicrosoft

Transforming Organizations through Applied Machine Learning and GenAI
Santosh Kumar Kotakonda, Associate Software EngineerJP Morgan Chase

Identifying Undiagnosed Rare Disease Patients Using Multi-Model Large Language Frameworks on Real-World Physician Notes
Shantanu Seth, Senior DirectorAxtria

Machine Learning in Hospitality to enhance Customer Experience
Rupam Priya, Manager - Marketing AnalyticsWynn Las Vegas

See the full agenda here.
Why MLW is different

For 18 years, Machine Learning Week has focused on practical, real-world machine learning—not hype.

You’ll join practitioners working on:

  • deploying AI systems
  • scaling ML in production
  • making AI reliable enough for real business impact

We’d love to have you back with the MLW community this May.

These are uncertain times—but they’re also a moment of extraordinary opportunity. And the best insights still come from conversations with smart peers.

Hope to see you in San Francisco.

Best regards,
The Machine Learning Week Team

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