Are Professors Really People Too or Just Three Lizards in a Trench-coat?

As a student it is not infrequent to be advised to remember that “professors are people too” and they want you to approach them when you need assistance.  Although I certainly understood this intellectually, for someone shy as me, emotionally this advice was difficult to put in motion.  During my freshman year, I was always nervous to approach them to ask for homework help, or talk about research, or really anything, in a way I had never felt around my high school teachers.

It’s not hard to see what makes professors intimidating. They’re experts in their fields, with years’ worth of experience and knowledge. In class the professors are lecturing in front of a hall full of students they don’t know, and to students who don’t know them. It can be the recipe for nothing but an impersonal experience. I was terrified that if I messed up or misspoke the professor would think I wasn’t worth their time. However, it didn’t take long for that perception to change.

I think that doing research and working under the guidance of postdocs and professors was the only way I was going to overcome those fears. It is difficult to be too intimidated by the people you discuss movies and exchange funny stories with over lunch. Slowly, but surely I grew more comfortable around my coworkers. Coworkers! – How weird it is to work in the same place as people who are normally your mentors, teachers, a part of a different world.

Now that I’m not quite so fear-filled at the very thought of interacting with them, the grad students, post-docs, and professors I’ve worked with this summer have taught me so much, merely by sharing their experiences. I’ve learned about the process of getting published and all its intricacies and difficulties. I’ve learned about why coding is important and how much we can learn from other disciplines. I’ve also learned about how important it is to stay focused on the big picture and not get lost in the little details.

Now, that is a lot to learn in one summer, let alone cover in one post, so I’ll focus on the last point. It’s easy to get bogged down in the details you deal with daily when you’ve been working on a project all summer. You get focused on the problem that you are currently working on and forget the end-goal, the purpose of the project overall. This can be dangerous. It makes it difficult to stay mentally engaged in the project and it makes it easy to go down the wrong path.

First you need to actually understand the big picture in order to remember it. When I first started I just had vague idea and set about accomplishing my goal one step at a time. That quickly went downhill as I consistently got stuck on problems with no idea how to move forward, and spent time on the wrong things with no good understanding of what I was trying to accomplish. Going back and reading papers and talking to my mentors helped solidify what they were looking for from my project.

I’ve found the best way to keep the big picture in mind is to talk to people who know nothing about my research. From the advice of my mentors and the reactions of friends and the people I meet at my internship events, I’ve realized that people aren’t all that interested in the simulations I work on daily. They’re not interested in hearing about the bug I solved today in my code. They want to hear the cool stuff about stars exploding and black holes. The things that can excite really anyone about space. What you tell them may only be 5% of what you actually spend time on, but it often illustrates the overarching goals of your research.

Overall, I’ve found that there is a lot to be learned from those with more experience. You’ll find many who are willing to teach you, not just about the subject you’re researching, but all the other knowledge they gained in getting where they are today.

The Robot Revolution – Astronomy and Computers

For thousands of years humans have stared at the night sky, naming constellations, telling stories, and making observations about the light of distant stars. Yet, for the majority of that time, astronomers were reliant on what they could glean with their unaided eye. Without a telescope, only about 6,000 stars can be seen from Earth, and from one spot you could only see about a third of those (Bryson).  This is a small fraction of the 1×1024 stars that are estimated to exist. Since the invention of the telescope in the early 1600s, technological advances have gone hand-in-hand with observational astronomy, paving the way for astronomers to look further and create a clearer picture of our universe.

Before this summer, I had thought that observational astronomy consisted of a lone astronomer, or perhaps a team, travelling to be on site with a telescope and staying up all night to adjust the telescopes position and do their observations. Not too long ago, this wasn’t far from the truth. I’d seen images from the Hubble Space Telescope and some other photographs made by professionals and amateurs alike, yet I had no sense of the magnitude of technological advances that had been made in the field.

This summer I began work with the Supernova Group at Las Cumbres Observatory. Amazingly, Las Cumbres Observatory doesn’t actually do any observing on-site. Instead, they manage robotic telescopes around the world that don’t even require a scientist on-site to operate them. This came as a complete shock to me. As far as my role in all of this, I’m not sure quite what I expected, but it certainly wasn’t 8+ hours a day in front of a computer. For interested readers, my daily work schedule looks something like this:

8:30 am: Bike to work

9-5: Work at my computer

5:00 pm: Bike home

Exciting right? The first few days were grueling and frustrating. I had limited experience with programming and working at a computer all day was a big shift from attending classes and doing homework. Yet, the experience has grown on me. It is amazing how much we humans are capable of with a computer at hand.

My current job at the observatory is to create simulations for the new Large Synoptic Survey Telescope (LSST). The LSST will be one of the biggest telescopes in the world, with an aperture of 8.2 meters. (For some suggested names of future large telescopes see In addition, LSST is completely automated, with preprogrammed directions of where to look during its 10 year survey. The telescope will take in 30 terabytes of data nightly (Lerner). In comparison, the entire NASA data set from 1955 to 2000 consisted of only 1 terabyte. There are not enough scientists in the world to sort through all this data manually (and I’m certainly glad they didn’t just decide to leave this job to the interns).

My goal is to take a known supernovae and pretend that if it were at a certain point in the sky on a certain day of the LSST’s survey. Then, try to answer the question of whether we would be able to find it again. The process of getting this code up and running has been an ordeal during which I’ve learned a lot about programming along with the science behind supernovae and the LSST. In the end I would like to be able to run 100,000 simulations for each kind of supernovae, totaling to nearly a million. Even my computer gets a bit tired out after that kind of task!

Supernova are notoriously difficult to spot, lasting only a short time, and nearly impossible to spot with the naked eye. In 1980, only one or two supernovae were discovered each year. With the advent of advanced telescopes and digital photography to record more than the human eye, this number increased to nearly 200 by 2000. As of 2012, astronomers are finding over 1000 supernovae per year (O’Brien).

Thankfully, with the billions of stars there are out there, astronomers are no strangers to big data. In fact, big data and astronomy have been going steady for a while now. However, we’re still looking for ways to improve how we can store and analyze this excess of data. Sometimes, new technology leads to great improvements in astronomy, and sometimes astronomy must push the advancement of technology.


Bryson, Bill. “The Reverend Evans’s Universe.” A Short History of Nearly Everything. New York: Broadway, 2003. 33. Print.

O’Brien, Author Tim. “Supernova 2014J and the Upcoming Deluge of Discoveries.” Professor Tim O’Brien. N.p., 10 May 2014. Web. 08 July 2017.

Lerner, Preston. “July/August 2017.” Discover Magazine. Discover Magazine, 19 July 2011. Web. 08 July 2017.