Day 3 – Less Statistics?

Today’s schedule was much, much quieter. We began by meeting one of Dr. Laber’s colleagues, Dr. Ana-Maria Staicu, a Romanian professor who has several degrees in the math/statistics area, who also happens to be the mother of one of my good friends from tennis tournaments. I knew she worked in some professional setting, but I had no idea she was working only two doors down from Dr. Laber – small world, huh? She introduced us to a few of her projects, including statistical analyses of marathon runners at the Olympic trials and the caloric intake of lactating pigs. One particularly interesting project she was working on related to the diseased white matter involved in multiple sclerosis (a brain disease that inhibits logical thought and motor control). After showing us multiple complex diagrams about a specific area of affected tissue, she explained that statistical algorithms could help predict future affected areas and allow the doctor to prescribe more accurate medicine. As Dr. Staicu said herself, statistics is one of the most applicable fields in the world- using data to draw conclusions helps in absolutely any field. Her obvious passion for her work was admirable, and she kept trying to get us to consider it as a college major (still not so sure). After speaking with her for a couple hours, we visited BOM to see what a different grad student was up to (we’re slowly meeting each person in the lab). Eric, a statistics major for undergrad, had hooked up several TVs to train an intelligent AI in the popular football video game Madden. He explained (in very basic terms) how each successive run would gradually increase the computer’s ability to choose the most optimal play, much like Nona, the chess robot. Tomorrow, we’ll be meeting with the team’s graphic designer, Lisa, to work with some 3D modeling software.

Eric and his 3 monitors, each controlled by a separate AI

Day 2 – Take Me Out To The Ball Game!!

As I walked into Bavarian Nordic this morning, I was quickly swept into a conference room. There, I took my seat and observed the Skype call that Ms. Handelsman and Janelle were conducting. They often have early morning meetings because the other part of the company is housed in Europe and there is a time difference. This meeting was a Brachyury core team meeting. They discussed various updates and ideas for the upcoming phases of the clinical trial. They might as well have been speaking in Danish because I didn’t understand much of it! All the employees in Denmark and Germany are fluent in English so there is not a communication barrier. After the meeting concluded, I stayed behind and asked Ms. Handelsman some questions that occurred to me during the meeting.

After Ms. Handelsman had to leave to attend another meeting, Erika shuttled me and Kaitlin into another conference room where we learned about statistics through a video and practice problems. We also went through a very long lecture about biostatistics for beginners. I noticed that Erika really loves her job! I hope that I will fall in love with whatever job I have in the future. Once we finished our lectures and practice, we moved into a real-world example. Erika printed copies of the Brachyury statistical analysis plan for us to study. It was so thick it must have taken a whole tree to print! After some hardcore reading, we decided it was time for lunch.

Kaitlin and I ate our lunch in the very luxurious break room and talked. She is going to graduating in December and is excited to be working in the clinical trials industry. She also gave me some good advice about college (i.e. visit the college you want to go to before you decide (she did not)).

We picked a very good week to come because today was the company’s annual outing to the Durham Bull’s game. Janelle, Kaitlin, and I all piled into Erika’s van and headed to Durham. We were met with TONS of traffic and a deficit of parking spaces. We had to park very far away so we were a little late to the game. We talked and watched the game and munched on nachos and French fries. After a fun couple hours, it was time to head back to Bavarian Nordic. We were lucky enough to be given free parking since we were so far away! Once again, we got into Erika’s van and started the drive. When we got back, I thanked Erika for driving and headed home. The morning was very informative and the afternoon was very fun! All in all, it was a great day.

We watched Ninjago while sitting in traffic!
Gr8 Day for a Game!
We HATE traffic

 

Day 2 – More and More and More Statistics

The second day began with a nice 10:30am start, but the late wake-up time still didn’t prepare me enough for that day’s statistics lesson. Today, Dr. Laber introduced us to the programming language R, and gave us several examples of how it can be used. We first looked at a massive spreadsheet of data taken from about 20 different dogs suffering from induced paralysis (from a getting hit by a car, falling, etc.), with cells including the time since incident, presentation, gender, breed, location of source, and biomarker proteins such as pNHFP and S100B that were measured. Dr. Laber asked Suki and I to find the primary causal factor that would determine a dog’s ability to walk after both 6 weeks and 6 months before setting a timer to 5 minutes and stepping out of the room. While a little daunting and stressful, we were able to deduce that if the average level of protein GFAPP exceeded a level of 0.31, the dog would have roughly a 92% chance of remaining paralyzed. He agreed, then showed us how R could be used to come across the same conclusion by comparing statistical algorithms of recovered vs. non-recovered dogs. He continued with these short exercises where he’d give us time to converse before explaining it in code, with examples such as latent states of depression of terrorists vs. non-terrorists, as well as methods of finding demographics of a population with just a small sample. It was quite the hour-and-a-half long hyper-speed presentation of applications, but our work felt important and our conclusions felt meaningful. Later that day, we went to the Laber Labs at BOM to meet with the team’s graphic designer, Lisa, to speak with her about a potential project for Friday using 3D imaging before we helped train the chess-bot Nona through about 600 more actions. Our time today felt pretty long, but the lab is full of so many interesting people and projects that each day is something completely new.

Dr. Laber’s morning presentation – on the pages are just lines and lines of code
Lisa’s sketch ideas for Nona, the chess robot

Day 1 – Lots and Lots and Lots of Statistics

First day in the books! After struggling with parking for well beyond the 10 min we had given ourselves as a buffer, Suki and I arrived at the 5th floor of NCSU’s Statistics Department. We met with Dr. Eric Laber, a statistics professor who is involved in so many interesting endeavors on and off campus. He led us to a conference room where he gave a presentation on what we’d be doing for the next couple weeks and the vast amounts of applications for statistics, specifically adaptive algorithms (computer programs that learn from each previous run/action and can compile that data and be able to decide more optimal actions), with projects such as chess-playing robots whose code could be cross-applied to identifying individuals involved human trafficking, fighting the AIDS/HIV and Ebola crises through precision medicine (providing the right treatment at the right time to the right patient at the right dose to maximize resource potential), and so many other crazy complicated schemes that I couldn’t wrap my head around. It wasn’t even midday and I was already mentally exhausted. He gave us a tour of campus before taking us to BOM (Bureau of Mines) where his research facility, Laber Labs, works out of. There we met Alison Wu, a graduate student from China who will be working at Apple starting September. We helped her manually program Nona, the chess-playing robot we’d heard so much about, by replicating the actions given by a program on a physical chess set to 100 actions and taking pictures of each specific move. She explained this would help Nona compile a library of images to develop a clearer grasp of each chess piece, rather than just working with online 3D models. In total, Suki and I completed almost 800 actions – phew. While tedious, we understood how important the work was- plus, we were rewarded with ice cream from NCSU’s famous Howling Cow! I’m excited to learn more about the rest of the team which consists of people from statistics to industrial design majors and helping them out with their respective projects. On to the next day…

Alison’s Chess-Playing Robot, Nona
Our Top-Notch Programming Workspace

 

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