Continual Learning Circle Meetup & Dinner

Today’s AI systems are still remarkably limited in how well they understand the people using them. Most rely on narrow silos of context: a few prior chats, a handful of connected apps, or fragmented signals that do not add up to real shared understanding.

This session explores what it would take for AI systems to build broader common ground with humans. Omar Shaikh will present two research projects that model human context from general computer interaction: one focused on learning user preferences over time across apps and workflows, and another focused on predicting a user’s next action from rich interaction history. Together, they point toward AI systems that can stay better grounded in who we are, what we care about, and what we are trying to do.

This event is part of the Frontier AI Research Series hosted by Across AI, AI Circle, and Adaptation on the future of grounding, memory, reasoning, and continual learning in AI systems.

Agenda

5:30 - 6:00 - Networking and Refreshments

6:00 - 6:10 - Introduction and Welcome

6:10 - 7:00 - Research Presentation and Discussion

7:00 - 8:00 - Networking

Who this event is for

This event is primarily for AI researchers, research engineers, PhD students, and technical builders working on NLP, HCI, agents, reasoning, memory, and related systems topics. It is also relevant to a smaller group of Heads of AI and technical enterprise leaders who want to understand where frontier research is headed and what it may mean for real-world AI systems.

Speaker

Omar Shaikh is a fourth-year PhD student in Computer Science at Stanford University, advised by Diyi Yang and Michael Bernstein.

His research sits at the intersection of NLP and HCI, with a focus on human-AI grounding: how shared context between humans and AI systems can be defined, measured, and computationally modeled.

His work has received Best Paper Honorable Mentions at UIST ’25 and CHI ’26, and an oral presentation at ACL ’25.

Connect with Omar.

Our Hosts

Across AI builds AI agents with long-term memory configured to your process that raises everyone’s performance. Learn more about Across AI.

AI Circle is a community of practitioners who are developing and deploying models. We host events globally at our chapters in SF, NYC, Seattle, London, and Paris. Learn more about AI Circle.

Adaption creates adaptive datasets to train AI models to target new objectives and scale quality. Learn more about Adaption.