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In academia, it’s inevitable to have to travel and present at conferences and meetings. As an introvert, I’ve been trying to compile a few tips that have helped me navigate large conferences so I don’t feel overwhelmed. It is unfortunate that though the academic community has many introverts, conference and meeting structure is heavily biased towards extroverts. (No offense to extroverts, but some of you can sometimes seem like blowhards to us introverts.

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Sorry for the lack of posts. I have been busy with co-teaching our Health Informatics course (HSMP410) for the OHSU/PSU School of Public Health. I’m trying to make most of my lectures activity-driven for my students, who are Community Health Education and Nursing majors. I believe that you can teach mathematical concepts visually, so I am experimenting with using LearnR/Shiny to teach the basics of data literacy. I’m also using datacamp-light to show my students a simple intro to data science.

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This term, I’m co-teaching an undergraduate course for the PSU/OHSU School of Public Health called Health Informatics with a number of my collegues in my department, including Bill Hersh, Eilis Boudreau, Karen Eden, and Virginia Lankes. We’re trying to give students a feel for what informatics is about in an accessible way. I’m trying to make the lectures as understandable as I can. This week we tackled Genome Wide Association Studies and discussed the strength of evidence behind SNP variants associated with phenotypes.

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Last week I had the good fortune to attend the From Evidence to Scholarship Conference at my alma mater, Reed College. The focus of the conference was improving the research process for undergraduates using digital scholarship. I came away from it excited about the work other people are doing in this realm and thinking about ways we could adapt these approaches. Nicole Vasilevsky and I (both former Reedies) each gave talks, about our experience developing materials for Data Science and giving data science workshops to undergraduates.

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I gave a talk for the Portland State University Systems Science seminar called How are Data Science and Systems Science Connected?. In this talk, I was highlighting current blind spots in Data Science that I think Systems Science approaches can address, especially that of interactions between features. I talked a little about my dissertation research (surrogate oncogenes), and the problem of black-box interpretability of predictive models. If you’re interested in listening to the recording, the playback is available here: https://us.

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I just gave a workshop teaching the basics of Shiny (the interactive web visualization framework) for a group of PDX R users. We had 10 people attend, and most of the attendees managed to get through the material and had lots of good questions. I really enjoyed talking with everyone and I hope everyone learned something. We’re planning to give the workshop again to the larger PDX R user community, and some of the attendees last night have volunteered to be TAs.

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Well, the week of teaching our Python Bootcamp for Neuroscientists is over. I had the pleasure of working with a great group of students, professors and instructors in developing the material, and had a great time teaching complete beginners to programming and Python. We had the overall goal of introducting 21 Neuroscience Graduate Program students at OHSU to the basics of programming in Python using data that they were interested in: electrophysiology data, and confocal microscopy data.

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Note: I have come to believe that this post is way too harsh and unwelcoming to people interested in data science. I will post an update to this, and a FAQ for those who want informational interviews. But in the spirit of showing my mistakes, I’ll leave this up here. I have had many people who have asked me for informational interviews. They tell me that they are interested in Data Science and want to hear about what I do on a day to day basis.

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Note: after posting this, I heard back from Roberto Tyley, the creator of the BFG. I’d like to note that the BFG actually does its job really well. I was mostly really frustrated about how Git/GitHub doesn’t prevent a user from doing something that’s hard to undo. So my frustration is really about that, not really about the BFG. This post has been edited to reflect that. Greg Wilson first said it, but I’ve come to agree.

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Have you ever had something that no matter how many times someone explained it, you really had no idea what it was for? For me, that was Non Standard Evaluation (NSE) in R, and its newer cousin Tidy Evaluation, or tidyeval. I had a real learning block about it. I really wanted to understand it, but for some reason I just really wasn’t getting the general concepts. What is evaluation, really?

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