Hack The Universe 2019
CMU's inaugural physics hackathon
1st-3rd February
Carnegie Mellon University
a r e y o u r e a d y ?
a r e y o u r e a d y ?
A hackathon is an invention marathon. Participants come together to solve interesting problems and create software in the span of a few days.
$0. We will also cater all meals for the duration of the event.
Students at any level, as well as postdocs and faculty members, from any department are welcome to attend.
We encourage you to attend HTU even if you do not have a physics background, as long as you’re interested in working on physics-related problems. HTU will focus on using data analysis and theory to solve physics problems, so skillsets in computer science, statistics, machine learning, math, etc. are very appropriate. We would also encourage you to attend if you’re just interested in learning about applying any of these topics to physics problems.
The event is being hosted on CMU’s campus, in Wean Hall 7316. Teams may also use other rooms on campus, but all major events/catering will happen in 7316
There are no restrictions on the number of members in a team.
We cannot offer travel reimbursements at this point.
There is a team-forming session at the start of the first day so feel free to come along on your own or with friends.
Absolutely! We’ll aggregate a list of interesting problems to work on. We will also have physics datasets made available. In addition, you can hear other participants’ ideas and join a team that interests you. If you’re still feeling unsure, drop us a message and we’ll do our best to help!
| 14:30 | Start of registration |
|---|---|
|
16:30 | 17:30 |
Intro & Reception (Piada catering) |
|
17:30 | 18:30 |
Idea pitches & team formation |
| 18:30 | Kick-off |
|
08:00 | 10:00 |
Breakfast |
|---|---|
|
12:00 | 13:00 |
Lunch (Chipotle) |
|
14:00 | 15:00 |
Secret fun event |
|
18:00 | 19:00 |
Dinner (Choolaah) |
|
08:00 | 10:00 |
Breakfast |
|---|---|
|
12:00 | 13:00 |
Lunch (Aladdin) |
|
14:00 | 15:30 |
Final presentations & wrap-up |
Time: Wednesday 23rd Jan, 12.30 - 14.00
Description: Learn about data visualization in python using matplotlib, seaborn and plotly.
Time: Tuesday 29th Jan, 16.30 - 18.00
Description: Introduction to numerical methods such as Markov Chain Monte Carlo
Time: Wednesday 30th Jan, 16.30 - 18.00
Description: Overview of supervised machine learning techniques and recent applications in physics and astronomy.
