Introducing HydraConda: create multiple related conda envs for more productivity

***UPDATE: All attendees must fill out the Georgetown University Visitor Registration form for COVID19 prior to attending. See the form here: https://gucovid.my.site.com/visitor/s/?event=VE7508***

This event will be in person. We expect to have food and networking at 6:30pm ET and the talk to start at 7pm ET. The event is in room WALSH 495 in Georgetown. See location information below.

We will try to add an online streaming option if the space and hardware will accommodate. Check back here at 6:45pm ET on the evening of the event and if there's a link here, then that's an option. If there's not, then it's not. Same goes for recording. :)

This event is co-hosted with Georgetown University Association for Women in Mathematics (GUAWM).

Description:
Computation-based research is often messy, non-linear, and highly exploratory. At the same time, there is a need for developed code to be reproducible for scientific integrity and to aid collaboration. Furthermore, long-term maintainability of computation-based projects benefit from modularization.

Software engineering tools can help but often involve an inappropriate level of formality and tool introduction; Creating programming-language specific 'libraries' of software to organize and distribute code is often too cumbersome and unnecessary. The first concern of scientific software is often just reproducibility. How can computational code be advanced without getting bogged down by software engineering rigor? Come learn how hydraconda can help?

Speaker Bio:
Majid has been involved in scientific computing generally for 12 years; most of which has been in data-oriented computing. He is currently a data scientist at Pacific Northwest National Labs. Majid holds a Bachelors in Mechanical Engineering and Economics from Vanderbilt University as well as a Masters degree in Mechanical Engineering. He also earned a Masters degree in computational science from George Mason University.