Foundation Models x Graphs Meetup – New York
Foundation Models x Graphs: Train Nothing. Predict Anything.
A new kind of model is emerging—purpose-built for relational data, and ready to change everything.
Following a sold-out session in San Francisco, we’re bringing this highly requested workshop to New York on May 21—featuring fresh insights, hands-on demos, and a lineup of voices shaping the future of applied AI.
Explore how foundation model techniques and graph-based architectures are converging to unlock instant predictions, scalable embeddings, and faster experimentation—without the burden of complex feature engineering. From multi-table relational data to real-time decisioning, this is your front-row seat to what’s next.
This hands-on evening blends deep tech talks, a live demo, and a panel featuring leaders from Google, Coinbase, Ro, and Kumo. You’ll leave with a clearer understanding of how graph-transformer-based approaches are accelerating predictive tasks—and connect with fellow builders leading the next wave of AI.
Featured Speakers
Vanja Josifovski – CEO & Co-founder @ Kumo
Bryan Perozzi - Senior Staff Research Scientist, Google
Ben Berger – Data Scientist at Kumo
Indrayana Rustandi - Machine Learning Engineer, Coinbase
Nick Hardy - Vice President of Data, Ro
Event Format
Agenda
5:00 PM – 5:30 PM | Mixer & Welcome Reception
Light food and drinks. Connect with peers and speakers.
5:30 PM – 6:05 PM | Visionary keynotes from Kumo Co-Founder & CEO Vanja Josifovski and Google’s Bryan Perozzi on the convergence of foundation models, graphs, and relational data
6:05 PM – 6:50 PM | Fireside Chat + Panel: Real-world lessons from deploying foundation models and graph-based AI systems in production - featuring leaders from Coinbase, Ro, and Kumo.
6:50 PM – 7:10 PM | Break
7:10 PM – 7:40 PM | Hands-On Workshop
Predict the Future in Minutes: Deep Learning on Relational Data. Bring your laptop!
7:40 PM – 8:00 PM | Closing & Networking Mixer
Wrap-up and networking over food and drinks.
Who Should Attend
Data Scientists & ML Engineers
You'll learn how to:
Complete modeling projects up to 20x faster
Eliminate complex feature engineering and data prep
Build models that understand entity relationships natively
Expand predictive capabilities across customer, product, and risk domains
Explore cutting-edge techniques inspired by foundation models, applied to structured data
AI & ML Platform Engineers
You'll learn ways to:
Generate accurate, scalable embeddings from relational data
Enhance RAG systems using structured data representations
Connect graph-based AI models directly to your data warehouse
Lay the groundwork for next-gen AI infrastructure built on relational context
Registration
Registration is free but approval is required.Applications will be reviewed to ensure a relevant technical audience.Limited to 40 participants to ensure meaningful discussions and personalized guidance.
Note: Security will not allow entry without an approved registration.