For last week’s meeting we were fortunate enough to have Professor Rekatsinas ( come in to discuss his perspective on Data Science. I’d very much encourage you to check out his slides and potentially reach out to him about research opportunities (provided you have programming experience). As we discussed at our research meeting, don’t be afraid to follow up if you don’t hear back in a week!


Shell scripting and being able to use the command line is a critical skill for anyone doing analyses. Many CS students don’t learn how to navigate a terminal until they’re forced to, so it’s definitely a skill worth having. We’ll be joined this week by Professor Tyler Caraza-Harter, who will be leading a workshop on this integral skill.

[DataSci] BASH: The Command Line
Scheduled: Mar 28, 2019 at 6:30 PM
Location: Room 1441, Genetics-Biotech

Right before spring break we met to go over the Do’s and Don’ts of building your résumé. Tech Specialist Amy Yang gave a presentation and discussed keeping a master résumé and customizing it for each company you apply to. She also discussed whether or not you need a cover letter and some caveats for styling your résumé, as well as opportunities for free professional attire. Please see the attach presentation (I promise it’s useful).

THIS WEEK – Résumé Workshop
Do you have a professional résumé? Are you applying for internships and research labs? This week we welcome tech specialist Amy Yang of UW’s SuccessWorks to do a workshop on presenting yourself to employers. We’ll discuss the Do’s and Don’ts of résumé building.

LAST WEEK – Machine Learning Crash Course
Sorry for the delay. Thanks for coming to the machine learning crash course last Thursday! We had ML PhD Finn Kuusisto discuss a variety of different supervised learning models, specifically Neural Networks, SVMs, Decision Trees, k-Nearest Neighbor, etc. Finn also gave some insights on graduate study and some specifics about deep learning.

Machine Learning Postdoc Finn Kuusisto will be joining us to give an overview of machine learning, specifically focusing on a few common models and their applications! This meeting is meant to acquaint you with some new terminology—it is not meant to go in depth nor discuss the intimate details of implementation.

After last week’s meeting with Dr. Richard Barker, I sent out this interest form. This information has been passed on to the Doc, but if you’d like to continue receiving some additional information, please join the #astrobotany channel of our slack workspace, dotDataGroup.


Thanks for coming tonight! Click here for the presentation slides. Major announcement regarding meeting time + frequency:

Meetings will be at 6:30pm every Thursday in Genetics-Biotech room 1441.

This frequency shift is due to the increase in interest from presenters + the number of topics we’d like to cover.
This time shift (later by 30 minutes) is because of room scheduling + some people had class.

We’ve now created a calendar with all meeting information!
[Subscribe here!]

Two different people specifically asked about making a slack group… We actually already have one!
😬 The slack channel is @dotdatagroup, so feel free to join

Someone mentioned a biological modeling course they had really enjoyed! If you’re interested, it’s Biochem 570 and the only pre-requisites are Calculus II and any intro bio sequence!

Semester Meeting Schedule (somewhat tentative):
• February 14th — Kickoff 
• February 28th — Getting into Research & NASA GeneLab 
• March 7th — Machine Learning Overview
• March 14th — Résumé Workshop (SuccessWorks)
• March 28th — SHELL: The Command Line
• April 4th — TBD (Data Visualization?)
• April 11th — TBD (Git: Version Control?)
• April 18th — TBD (Applying to graduate school?)
• April 25th — TBD (Bring in Researcher to hunt down undergrads?)
• May 2nd — Elections/Wrap-up meeting

Interested in Machine Learning & Data Mining (in Python)? 
On November 8th, we will be having a postdoctoral researcher coming in to speak about his work and some projects he’s completed. Dr. Kuusisto completed his Computer Science PhD in Machine Learning in 2015 at UW-Madison, and works in the Regenerative Biology lab at the Morgridge Institute to build models from genetic expression data that can predict when compounds are toxic to developing neurological tissues.