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Upcoming Events

AllConferenceSeminars
Center for Decoding the Universe Fall Forum
Nov 09, 202612:00 PM - 6:00 PM
November
09
2026

Please note that this event is open to Stanford affiliates only.

November
09
2026

Center for Decoding the Universe Fall Forum

Nov 09, 202612:00 PM - 6:00 PM

Please note that this event is open to Stanford affiliates only.

Data Science
Daniel Wurgaft | A Resource Rational Analysis of Representations: Geometry, Inference, Capacity
SeminarNov 09, 20264:00 PM - 5:30 PM
November
09
2026

A Center for Neural Data Science Seminar Series

November
09
2026

Daniel Wurgaft | A Resource Rational Analysis of Representations: Geometry, Inference, Capacity

Nov 09, 20264:00 PM - 5:30 PM

A Center for Neural Data Science Seminar Series

Data Science
HAI & AI Governance Lab | A Conversation with Jacob Coxon & Rob Reich
Nov 09, 20264:30 PM - 5:30 PM
November
09
2026

This in-person event is open to current Stanford faculty, students, and staff. ID will be required at check in. Other guests are invited to join the webinar.

November
09
2026

HAI & AI Governance Lab | A Conversation with Jacob Coxon & Rob Reich

Nov 09, 20264:30 PM - 5:30 PM

This in-person event is open to current Stanford faculty, students, and staff. ID will be required at check in. Other guests are invited to join the webinar.

Regulation, Policy, Governance
Marlowe | AI + Data for Science with Alex Pentland
SeminarNov 11, 20264:30 PM - 5:30 PM
November
11
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

November
11
2026

Marlowe | AI + Data for Science with Alex Pentland

Nov 11, 20264:30 PM - 5:30 PM

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Data Science
Khaoula Chehbouni | Best Practices for the Use of LLMs as Judges
SeminarNov 13, 20261:00 PM - 2:15 PM
November
13
2026

An AI Measurement Science (AIMS) Seminar Series

November
13
2026

Khaoula Chehbouni | Best Practices for the Use of LLMs as Judges

Nov 13, 20261:00 PM - 2:15 PM

An AI Measurement Science (AIMS) Seminar Series

Data Science
Special Seminar and Fireside Chat: Understanding Work Using AI
Nov 13, 20262:00 PM - 4:00 PM
November
13
2026

Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.

November
13
2026

Special Seminar and Fireside Chat: Understanding Work Using AI

Nov 13, 20262:00 PM - 4:00 PM

Phil Lewis from the National Center for O*NET Development will talk about data infrastructure the US Department of Labor provides, and how AI is used to update it. A panel with Diyi Yang from the Stanford Computer Science Department and DEL’s Erik Brynjolfsson will discuss the opportunities of a new partnership between Stanford and the National Center for O*NET Development.

Machine Learning
Industry, Innovation
Government, Public Administration
Regulation, Policy, Governance
Christopher Ong | Research Acceleration: The View Inside OpenAI
Nov 16, 202612:00 PM - 1:00 PM
November
16
2026

In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.

November
16
2026

Christopher Ong | Research Acceleration: The View Inside OpenAI

Nov 16, 202612:00 PM - 1:00 PM

In the last year, AI models have rapidly improved on public benchmarks measuring their ability to carry out research tasks autonomously. Such performance suggests that models may be capable of automating parts of the AI R&D process itself, thereby accelerating the pace of AI progress.

Machine Learning
Industry, Innovation
AI100 | AI Goes Mainstream: The Scaling Era and the Rise of Generative AI
SeminarNov 18, 202612:00 PM - 1:15 PM
November
18
2026

This talk will cover key insights from the third AI100 report, AI Goes Mainstream: The Scaling Era and the Rise of Generative AI, set for release in November 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.

November
18
2026

AI100 | AI Goes Mainstream: The Scaling Era and the Rise of Generative AI

Nov 18, 202612:00 PM - 1:15 PM

This talk will cover key insights from the third AI100 report, AI Goes Mainstream: The Scaling Era and the Rise of Generative AI, set for release in November 2026. The report was commissioned by the AI100 standing committee and led by study panel chair Michael Wooldridge.

Foundation Models
Industry, Innovation
Democracy
Marlowe | AI + Data for Science with Andreas Tolias
SeminarNov 18, 20264:30 PM - 5:30 PM
November
18
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

November
18
2026

Marlowe | AI + Data for Science with Andreas Tolias

Nov 18, 20264:30 PM - 5:30 PM

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Data Science
Marlowe | AI + Data for Science with Leonidas Guibas
SeminarDec 02, 20264:30 PM - 5:30 PM
December
02
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

December
02
2026

Marlowe | AI + Data for Science with Leonidas Guibas

Dec 02, 20264:30 PM - 5:30 PM

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Data Science
Angèle Christin & Hannah Zeavin | Gurus, Hucksters, Entertainers: How Influencers Reshaped Social Media
SeminarDec 09, 202612:00 PM - 1:15 PM
December
09
2026

Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies. 

December
09
2026

Angèle Christin & Hannah Zeavin | Gurus, Hucksters, Entertainers: How Influencers Reshaped Social Media

Dec 09, 202612:00 PM - 1:15 PM

Please join us for an illuminating investigation of the complex work of social media content creators—their lives, conflicts, and controversies. 

Communications, Media
YoungJu Jo | Data-driven Discovery and Control of Neural Computations
SeminarDec 14, 20264:00 PM - 5:30 PM
December
14
2026

A Center for Neural Data Science Seminar Series

December
14
2026

YoungJu Jo | Data-driven Discovery and Control of Neural Computations

Dec 14, 20264:00 PM - 5:30 PM

A Center for Neural Data Science Seminar Series

Data Science
2027 Conference on Physics and AI (PhyStat 2027)
ConferenceMay 24, 2027
May
24
2027

The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced statistical and computational methods. 

May
24
2027

2027 Conference on Physics and AI (PhyStat 2027)

May 24, 2027

The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced statistical and computational methods. 

Data Science

Featured Videos

Hear from speakers and attendees at recent Stanford HAI events across research, policy, and education.

Previous Events at HAI

AllConferenceSeminarsWorkshops
2026 SC2 Student Conference
ConferenceNov 06, 20268:30 AM - 5:00 PM
November
06
2026

Please note that this event is open to Stanford affiliates only or by invitation.

2026 SC2 Student Conference

Nov 06, 20268:30 AM - 5:00 PM

Please note that this event is open to Stanford affiliates only or by invitation.

Data Science
Marlowe | AI + Data for Science with Ruijiang Li
SeminarNov 04, 20264:30 PM - 5:30 PM
November
04
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Marlowe | AI + Data for Science with Ruijiang Li

Nov 04, 20264:30 PM - 5:30 PM

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Data Science
Marcos Santiago Rojas Pino & Thomas Caruso | Building an International AI Platform for Health Professions Education and the Learning Sciences
SeminarNov 04, 202612:00 PM - 1:15 PM
November
04
2026

Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.

Marcos Santiago Rojas Pino & Thomas Caruso | Building an International AI Platform for Health Professions Education and the Learning Sciences

Nov 04, 202612:00 PM - 1:15 PM

Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.

Healthcare
Education, Skills
NVIDIA & Marlowe | Scale Training Across GPUs and Nodes - Zoe Ryan
Nov 04, 202612:00 PM - 1:00 PM
November
04
2026

Our November session is Scaling Training Across GPUs and Nodes with speaker Zoe Ryan. This session focuses on efficient strategies for using multiple GPUs and nodes. We will discuss how to deploy strategies of data parallelism and model parallelism to scale to multiple GPUs through PyTorch, enabling faster training times and better model performance.

Location: CoDa W401 & Zoom
Refreshments and snacks provided

Please follow the link to register

NVIDIA & Marlowe | Scale Training Across GPUs and Nodes - Zoe Ryan

Nov 04, 202612:00 PM - 1:00 PM

Our November session is Scaling Training Across GPUs and Nodes with speaker Zoe Ryan. This session focuses on efficient strategies for using multiple GPUs and nodes. We will discuss how to deploy strategies of data parallelism and model parallelism to scale to multiple GPUs through PyTorch, enabling faster training times and better model performance.

Location: CoDa W401 & Zoom
Refreshments and snacks provided

Please follow the link to register

Data Science
Olawale (Wale) Salaudeen | On Construct Validity in AI: The Scientific Work We Have Yet to Do
SeminarOct 30, 20261:00 PM - 2:15 PM
October
30
2026

An AI Measurement Science (AIMS) Seminar Series

Olawale (Wale) Salaudeen | On Construct Validity in AI: The Scientific Work We Have Yet to Do

Oct 30, 20261:00 PM - 2:15 PM

An AI Measurement Science (AIMS) Seminar Series

Data Science
Marlowe | AI + Data for Science with Dan Yamins
SeminarOct 28, 2026
October
28
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Marlowe | AI + Data for Science with Dan Yamins

Oct 28, 2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Data Science
Confronting Our AI Future: Hope, Fear, and the Choices Ahead
ConferenceOct 28, 20269:00 AM - 6:45 PM
October
28
2026

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

Confronting Our AI Future: Hope, Fear, and the Choices Ahead

Oct 28, 20269:00 AM - 6:45 PM

The rapid acceleration of AI comes with a profound wave of anxiety. Across every sector of society, people are facing unsettling questions about their worth and their place in a shifting world.

Workforce, Labor
Sciences (Social, Health, Biological, Physical)
Daniel Rock | The Free Hypothesis: AI and Shifted Bottlenecks in Science
Oct 26, 202612:00 PM - 1:00 PM
October
26
2026

Scientific progress is a key driver of economic growth and prosperity. There is great excitement- but also concerns- about the impacts of AI on science, but so far little data. We provide early insights on this from three data sources: a sample of 15 million Gemini interactions, an inventory of over 2,600 specialized AI models across disciplines, and a survey of over 600 scientists.

Daniel Rock | The Free Hypothesis: AI and Shifted Bottlenecks in Science

Oct 26, 202612:00 PM - 1:00 PM

Scientific progress is a key driver of economic growth and prosperity. There is great excitement- but also concerns- about the impacts of AI on science, but so far little data. We provide early insights on this from three data sources: a sample of 15 million Gemini interactions, an inventory of over 2,600 specialized AI models across disciplines, and a survey of over 600 scientists.

Machine Learning
Economy, Markets
Industry, Innovation
Marlowe | AI + Data for Science with Anshul Kundaje
SeminarOct 21, 2026
October
21
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Marlowe | AI + Data for Science with Anshul Kundaje

Oct 21, 2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Data Science
Bay Area Tech Economics Seminar with Rehan Khan, Snowflake
SeminarOct 20, 20266:30 PM - 8:30 PM
October
20
2026

The Bay Area Tech Economics Seminar is for graduate-trained economists and other quantitative social scientists from academia, policy, or the private sector who are interested in the tech economy and methods for analyzing it, and in making connections with others in this broadly defined space.

Bay Area Tech Economics Seminar with Rehan Khan, Snowflake

Oct 20, 20266:30 PM - 8:30 PM

The Bay Area Tech Economics Seminar is for graduate-trained economists and other quantitative social scientists from academia, policy, or the private sector who are interested in the tech economy and methods for analyzing it, and in making connections with others in this broadly defined space.

Economy, Markets
Data Science
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