October 2026 has a mix of machine-learning workshops, university seminar series and conferences, including events on scientific ML, high-performance computing, energy systems and AI for scientific discovery. This is a curated selection, not a complete global calendar; check each organizer’s page for current access and registration details before making plans.
October 2026 events at a glance
| Date | Event | Topic and format | Location and access |
|---|---|---|---|
| October 2, 16 and 30 | Columbia Machine Learning and AI Seminar Series | Academic talks, Fridays from 11 a.m. to noon | In person, Columbia Statistics Department. External guests must register by noon the previous day and receive a QR code by email. |
| October 5 | Workshop on Scientific Machine Learning | Scientific machine learning workshop | Peter O’Donnell Jr. Building, POB 6.304, The University of Texas at Austin. |
| October 5–6 | NCSA Regional Workshop on AI | Hands-on machine-learning training for academic researchers, with a focus on HPC workflows for domain science | In person, University of Illinois Urbana-Champaign. Intended for researchers new to ML or seeking intermediate skills. |
| October 7 and 14 | Stanford HAI/Marlowe AI + Data for Science seminars | Seminars on AI and data for science | Stanford; the organizer lists room details for each date. Talk titles are announced by organizers. |
| October 19–21 | UChicago and Caltech AI+Science Conference | AI and machine learning for scientific discovery across physical and biological sciences | David Rubenstein Forum, Chicago. Registration is closed. |
| October 20 | “A Riemannian Geometry Perspective on Foundation Models” | Texas AI talk, 3:30–4:30 p.m.; speaker Rex Ying of Yale University | POB 6.304 and Zoom. |
| October 23–24 | Fall into ML 2026 | Machine learning and AI conference for researchers, students and industry professionals | HSE University Cultural Centre, Moscow. Attendee registration is listed through October 20. |
| October 28 | AI-Enabled Energy Systems: Technologies, Intelligence, and Security | Talks, a panel and an afternoon roadmap workshop; 9 a.m.–5 p.m. | Glass Pavilion, Johns Hopkins University Homewood campus, Baltimore. Outside participants are welcome; registration includes breakfast and lunch. |
Events by date and what to expect
October 2, 16 and 30: Columbia seminar series
Columbia’s Friday series runs from 11 a.m. to noon in the Statistics Department. The October 2 speaker is Benjamin Eysenbach of Princeton, October 16 is Aviral Kumar of Carnegie Mellon, and October 30 is Stephen Tu of USC. These are in-person listings, not an announced online series. External guests need to register by noon the day before; Columbia says registered guests receive an email QR code for campus entry.
As an Amazon Associate I earn from qualifying purchases.
October 5: Scientific machine learning at UT Austin
The Oden Institute describes this as its fourth annual Workshop on Scientific Machine Learning. It is scheduled for the Peter O’Donnell Jr. Building, room POB 6.304, at The University of Texas at Austin. The listing identifies the venue but does not state a remote attendance option.
October 5–6: NCSA’s regional AI workshop
The University of Illinois Urbana-Champaign’s National Center for Supercomputing Applications (NCSA) describes this as an in-person, hands-on workshop for academic researchers who are new to machine learning or want intermediate skills. Its focus is practical workflows for using high-performance computing in domain science. The organizer says the event will introduce tools and workflows to simplify HPC use for machine-learning applications and help researchers integrate ML into domain-science work.
#1 Best Overall
October 7 and 14: Stanford AI + Data for Science
Stanford lists Olivier Gevaert for October 7 and Curtis Langlotz for October 14 in its HAI/Marlowe seminar series. The listing provides room information for each date, but says talk titles are announced by organizers. Check the Stanford event page for the specific room and any updated details.
October 19–21: UChicago and Caltech AI+Science Conference
This conference at Chicago’s David Rubenstein Forum centers on AI and machine learning for scientific discovery in the physical and biological sciences. Registration is closed according to the event page, so it is not currently an option for new registrants.
Rank #2
- Use scikit-learn to track an example ML project end to end
- Explore several models, including support vector machines, decision trees, random forests, and ensemble methods
- Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection
- Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers
- Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning
October 20: Texas AI on foundation models and geometry
Rex Ying of Yale University is listed for “A Riemannian Geometry Perspective on Foundation Models,” scheduled from 3:30 to 4:30 p.m. The event offers both POB 6.304 on the UT Austin campus and Zoom, making it one of the listed options with an explicit remote format.
Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteWindows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOctober 23–24: Fall into ML 2026
HSE University’s fifth Fall into ML conference takes place at its Cultural Centre in Moscow. The intended audience includes machine-learning and AI researchers, students and industry professionals. The event page lists attendee registration through October 20; confirm availability with the organizer if registering close to that date.
Rank #3
October 28: AI-enabled energy systems at Johns Hopkins
Johns Hopkins schedules this event from 9 a.m. to 5 p.m. at the Glass Pavilion on its Homewood campus in Baltimore. Its program combines invited talks and a panel with an afternoon roadmap workshop. The event page welcomes outside participants and says registration includes breakfast and lunch. The format described is in person.
Other topics in the October calendar
The AIhub roundup also lists October seminars on machine learning and decision-making, detecting LLM-generated text with statistical methods, AI ethics, optimization and neural networks. The roundup names speakers and organizers, but attendance instructions differ: some listings point to mailing-list signup, some require event registration, and others advise contacting the organizer for a Zoom link. Verify the individual listing rather than assuming these talks share a format or access policy.
Rank #4
How to choose and verify an event
- Choose by subject: the schedule includes scientific ML, HPC training, foundation models, AI for science and energy systems, along with decision-making, AI ethics, optimization and neural networks.
- Check the format: the NCSA workshop and Columbia series are in person; the Texas AI talk explicitly offers Zoom as well as a campus room. Do not infer remote access for events whose listings name only a venue.
- Confirm eligibility and registration: Columbia has a deadline for external guests, Fall into ML lists an attendee-registration deadline, and the UChicago–Caltech conference says registration is closed. Johns Hopkins explicitly welcomes outside participants.
- Recheck logistics with the organizer: venues, available registration, schedules and online links can change. Use the event page before booking travel or relying on a participation link.
For current details, consult the organizer listings: AIhub’s October roundup, Oden Institute events, NCSA events, Columbia Statistics, Texas AI, HSE University, Johns Hopkins AI, UChicago, and Stanford HAI events.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Quick Recap
Best Value
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
