Several undergraduate students recently attended the SAMSI Undergraduate Workshop focusing on Computational Neuroscience. Here is Suzanna Mostaghim’s impressions of the workshop. Suzanna attends Virginia Tech. She has a wonderful blog you should check out called Inklings and Tea.
The Statistical and Applied Mathematical Sciences Institute (SAMSI) holds a two day undergraduate workshop in the fall and spring as well as a week-long one in the summer.
This year, the fall workshop from October 19-20th focused on computational neuroscience. Over one and a half days there were seven scientific talks, which was incredibly intense. I personally have over six pages of notes.
I got in on Sunday night, a lot of other participants got in in the morning and afternoon due to flights and better planning than myself. As I was the only girl from Virginia Tech I was paired with a random roommate (who is in fact an awesome triple major, check out her blog here).
SAMSI was great and paid for our hotel rooms so we wouldn’t have to worry about waiting to get reimbursement for the room for a few weeks. We were staying only about 10 minutes from NISS and about 25 minutes from Duke.
Our first day started early, we shuttled over to SAMSI at 8:15, registered, and began talks at 9:00.
The first talk was by Ciprian Crainiceanu from John Hopkins University; he talked about clinical brain imaging from a statistical view, pointing out that data scientists and electrical engineers would use different techniques and names. Look out for his MOOC on Coursera early next year.
For me, I recognized this area as image deblurring – the data science point of view. This was something I had touched on in a Computer Modeling and Data Analytics course at Virginia Tech taught by Julianne Chung whose research is in image deblurring.
We sped through the first slideshow he showed on Neurohacking and moved onto Data Structures and Operations which was based on classification typing. It was intense to go through so many slides in less than two hours and absorb as much information as I possibly could.
I don’t think I ever wrote so many notes on a singular lecture outside my classes until that point. She brought down the information to the level that an undergraduate would understand and expanded upon it to show us how to approach the problems she faced while analyzing diffusion anisotropy.
When she finished we broke for lunch and traveled to the Center for Neuroimaging at Duke and did an overview of the facilities and once again listened to a talk. I won’t go into detail, but I’ll admit you should definitely visit them for grad school if you’re interested in biostats and psychological disorders.
In full disclosure, I think that it could have been organized a little better for the field trip. However, it was still a wonderful experience and good break in between intense scientific talks
Next we had an R tutorial from Benjamin Risk, who works at SAMSI. He sped through and gave a thorough tutorial. However, due to the faulty internet connection a lot of students weren’t able to follow completely.
After R, we got to one of my favorite talks by Sarah Vallelian. Which was about computed tomography using MATLAB and Python; something I’ve covered at Virginia Tech. But, I won’t expound upon the details. She showed us the equations for attenuation and how to use Radon Transforms when doing compute tomography.
When the talks for the day were over we attended a panel discussion hosted by postdocs and graduate students about graduate school. One in particular was very sarcastic and, while amusing, it got a bit tiring after a while. However, overall they were very helpful and gave a good amount of advice for graduate school considerations.
We then shuttled back to the hotel and groups of us conglomerated together and bonded, exchanging contact information in order to keep in contact after the workshop ended the next day.
The second day started just as early as the first and we started with a talk on models for muscle activation by Lauren Miller from UNC – Chapel Hill. She covered the simplistic models and moved onto more complex ones such as the Three-Element Hill Model, explaining on a level that we understood.
Our very last talk was on Topology for Statistical Analysis of Brain Artery Images by Ezra Miller. I knew very little about topology, and when he was done I understood a lot more than I had ever learned prior to that talk.
He was incredibly engaging and broke down topology to the point where I believe almost anyone could understand. I honestly am considering applying to Duke just to have him as a professor one day.
With the end of the Ezra’s talk, the workshop came to an end. I had to go back to Blacksburg and part ways with my new found friends. But, it was definitely an experience I will never forget.