Events

Explore our latest events, seminar series and conferences.

Oct

14

2026

Physics Colloquia

Physics Colloquium with Leland Ellison

Title TBA

3:15 pm – 4:15 pm In Person

Speaker(s): Leland Ellison

Oct

19

2026

Machine Learning in Physics

Machine Learning Seminar

These meetings are for discussions of machine learning research within the department: training, journal club-style meetings, and applications. No prior machine learning expertise is required

2:00 pm – 3:30 pm In Person

Oct

20

2026

Weinberg Institute Seminar

WI Seminar- Alejandro Vilar Lopez

Title TBA

2:00 pm – 3:30 pm In Person

Speaker(s): Alejandro Vilar Lopez

Oct

21

2026

Physics Colloquia

Physics Colloquium with Robert Boyd

Title TBA

3:15 pm – 4:15 pm In Person

Speaker(s): Robert Boyd

Oct

22

2026

IFS Seminar

IFS Seminar with Yashika Ghai

“From first-principles simulations to machine-learning surrogates for energetic particle transport"

2:00 pm – 3:30 pm In Person

Speaker(s): Yashika Ghai

Nov

2

2026

Machine Learning in Physics

Machine Learning Seminar

These meetings are for discussions of machine learning research within the department: training, journal club-style meetings, and applications. No prior machine learning expertise is required

2:00 pm – 3:30 pm In Person

Nov

3

2026

Weinberg Institute Seminar

WI Seminar- Kev Abazajian

Title TBA

2:00 pm – 3:30 pm In Person

Speaker(s): Kev Abazajian

Nov

4

2026

Visualizing Science 2027 Submission Deadline

The college’s Visualizing Science competition helps raise the profile of UT science, with public displays of images that celebrate the extraordinary beauty of science and the scientific process.

11:59 pm Virtual

Nov

10

2026

Weinberg Institute Seminar

WI Seminar- Daniel Scolnic

Title TBA

2:00 pm – 3:30 pm In Person

Speaker(s): Daniel Scolnic

Nov

16

2026

Machine Learning in Physics

Machine Learning Seminar

These meetings are for discussions of machine learning research within the department: training, journal club-style meetings, and applications. No prior machine learning expertise is required

2:00 pm – 3:30 pm In Person