Pursuing Undergraduate Research

Or: How I Learned to Stop Worrying and Love the Chaos

Are you tired of manageable workloads?

Do you have too much free time during summer?

If only there was a solution!

Hi, I’m Michael Meneses, and I’m here to tell you about Undergraduate Research Opportunities, the fast and easy way to add some science to your life! As a Gorman Scholar and proud intern of the Hofmann lab, I want to share my experiences to hopefully convince some of you to give research a shot. Surely there must be some payoff to this whole interning thing, right?

A Sneak Peak

I’m going to say it now: there’s a good chance you have little to no experience in your major. And that’s totally fine. But it definitely brings up a weird and somewhat uncomfortable question: will I even like my major in the future? I spent my whole childhood wanting to be a marine biologist, but every now and then I’d wonder that same question and start to doubt. What if I end up not liking marine research? What will I do then?

Luckily, my time in the Hofmann lab changed that. Yes, research was much harder than I thought it would be. Yes, there’s a lot of reading and mistakes and frustration. Yes, my desk looks like a landfill and I send now more emails than a spambot. BUT, I realized that despite all the stress of the job, I only feel more and more excited about what our next project will be. Maybe you’ll realize just how passionate you are about your major, and an internship will help cement your future. Or maybe you’ll find that your major just isn’t for you, and you’re not looking forward to committing to it. An internship can let you test the waters before you decide to dive in. Which brings me to:

Exploring New Fields

Sticking to a major can be hard. We all know plenty of people who suddenly realized that their major just isn’t working out for them. Maybe their whole life has been dedicated to majoring in this one specific (and probably impacted) field. Or maybe they just don’t have a plan for their future yet. Wherever you fit in within this spectrum, taking advantage of a research opportunity can help you find a new direction for your future, even if that direction points far, far away from research. 

I’ve been gung-ho about studying marine biology my whole life, but I didn’t really have any concrete plans beyond “doing research”. Honestly, I was kind of hoping that things would sort themselves out after college and I’d go with the flow. My time with Gorman and the Hofmann lab have changed that for the better by exposing me to the active and chaotic communities in research and giving me the professional and lab skills needed to carve my own place in it. Taking an internship can spark a new passion in you, or open a new door into a field you thought you knew inside and out. Even if you decide you don’t like this new field or decide not to pursue a research degree, an internship is a great way to explore any wild scientific fantasies you might have.

And More!

I’m only grazing the tip of the iceberg here. I unfortunately don’t have the time or space in this post to tell you all the different ways you can benefit from an internship. Even if I listed off all the ways my internship has helped me, I couldn’t guarantee that they’d all apply to you. Every lab will have their own problems, approaches and procedures, as well as different people suffering through all of them. Each experience during an internship will be unique and could end up taking you in a new, exciting direction you might not find otherwise.

We’re Cuckoo for Copepods

The alarm goes off on my phone. I simultaneously acknowledge and try to ignore it. Try. It’s 4 am and too early to be alive, and yet here I am, trying to calculate how many times I can press snooze and still be on time.

Today is sample day.

I eventually dredge myself out of bed and get ready. Now that my brain is booting up, I start to feel excited again. After all, this is the first time I’ve ever done fieldwork for my major, so it doesn’t matter that it’s just a sample collection. My phone buzzes: they’re here. After a final check to be sure I have everything, I hurry outside and get into our sketchy looking lab van.

Location: Point Dume
Date:  July 3, 2019
Party: Sam the man, they call me Logan, and Asher pod catcher.
Objective: collect all the samples, disturb some ecosystems, protect UCSB

After a short drive, we finally reach Point Dume state beach, where we unload our weapons of choice: tupperware and turkey basters. We prowl the edges of the rocky beach, flashing our lights into the various tide pools hidden within the craggy boulders. Our target: Tigriopus californicus, sometimes known as the tiger copepod. Although they’re small, tigs have a remarkable tolerance to conditions that would kill many other creatures, such as low pH, high temperatures, and low levels of oxygen. Furthermore, many scientific papers show that these tolerances vary based on the climate and location of where the tigs live. Our research project aims to find what role, if any, genetics plays in these differences. But before we can get to that, we first need to awaken our inner pokemon fan and catch some tigs.

100% skill and precision.


Back at UCSB, we began the process of labeling our samples and testing the range of tolerances of our tigs. For this experiment, we specifically focus on thermal tolerances to explore how different populations will be able to handle increasing ocean temperatures. To do this, we calculate the lethal temperature 50% (LT50) by putting our tigs through an almost-literal trial by fire. The most accurate way to determine a population’s LT50 is by slowly increasing the temperature of the tig’s environment up to a high temperature, then maintaining that temperature for a while. Luckily, a thermal cycler can do just that, and tigs are small enough that we can comfortably fit 5 of them into a PCR well. We do this through the incredible and highly competitive process known as tig loading.

The set-up is a dream. The prep work is a nightmare.


Thermal Tolerance Testing

12    8-well PCR tube strips
480    T. californicus (if doing a complete 96 well plate)
1    Micropipette, set at 24 microliters
1    Thermal cycler
∞    Amounts of patience

Start by preheating programming your cycler with a temperature gradient of 36-38°C.

Contemplate your life choices as you meticulously fish out 480 tigs using the micropipette as an inefficient vacuum.

Catching multiple tigs at once gives you bonus points.

Panic when you realize you lost your place loading the wells.

Place loaded wells into your cycler for 3 hours total: two to slowly bring the temperature up, then one hour at that temperature.

Remove and serve hot.

We then fully accept our fate as hunchbacks and use a dissecting microscope to look for survivors in each well. By counting the number of fatalities, we can calculate the proportion of survival at each individual temperature. This gives us survivor proportion as a dependant variable with respect to temperature, which can be easily plotted onto a graph using RStudio. The best part about using RStudio is that the different thermal tolerance graphs we plot can be combined with each other into a single graph, giving us an easy-to-read visual comparison between populations.

Pretending that you know how to use R is an important step.

And that’s a wrap! Between the early morning collecting and giving myself nearsighted blindness, I think I’m ready to call it a day. This was definitely one of the more eventful days I’ve had in the lab, but I really enjoyed it. It’s really starting to feel like I’m contributing to the lab and project. Tomorrow will be another busy day setting up cultures for out tigs, and a few days later will be another sampling trip. I can hardly wait!

How to Teach Yourself Image Processing

1. Context

This summer I have been asked to write a program that will take the following picture of transistors…

…and measure lengths and angles of the gray shapes inside of each box. The scope of this writing is image processing so we’re not going to talk about what a transistor is or where the gray shapes come from. Just accept the fact that they exist and I’m trying to measure it. On to the image processing where the program I am using is MATLAB.

2. Binary Image

The entire process starts with edge detection: letting the computer decide where lines are. Googling edge detection tells you to start with converting the image into a binary image. Binary Images are the foundation of edge detection because there is a white pixel were a line is and a black pixel where there is not a line. To make a binary image simply type edge(image) into MATLAB and-


So it’s the first step and I have already come across an issue. The images I am working with are too noisy and produce real nasty looking pictures. So step 1 a) is to filter an image to reduce noise. There are multiple filters that can be applied and multiple methods for creating binary images and photos of these multiple iterations are below:

The best and most consistent thing that worked was the use if the ‘canny’ method for binary image creation and applying one filter.

So after all that, step one is completed on to step two.

3. Line detection

MATLAB has a built-in method for detecting lines called the Hough transform. It’s a popular method for line detection used in most computer vision programs today.


The graph is in terms of the length of the line (rho) and the angle it is at (theta). The brightest points are where the computer believes there is a line. Applying this to the current binary images I have yields…


An incomplete method for finding lines. Turns out the images I have are too pixelated to give clean lines to the program so MATLAB only finds the lines it is only 100% exist and anything else is left unnoticed. This led to a rabbit hole for finding other methods of line detection such as the Radon transform, and nothing worked. So eventually, I decided to tell the computer of multiple pixels are in a vertical or horizontal line then say it is a line.

Now I can find lots more lines. My next step was to make an outline of the transistor using the furthest outward line. As you may have guessed, there is a lot of room for error using this method.

This is an error I plan to fix later in the project because this does work on most samples I have. From this point I moved on to my next Step.

4. Meaningful Measurements

I currently have measurements in pixels, but pixels mean nothing to the Lab, so I decided to implement a method for recording the measurements in nm. There is a scale bar on every picture I receive so the easy approach is to use the scale bar to create a pixel to nm conversion.

Ahh yes, clearly defined lines in this scale will make this step trivial compared to everything I have done up to this poi-

Yeah this is an issue, being unable to consistently measure the scale bar leads to many issues as you may have guessed. So on to plan B. I noticed by this point that all photos gathered are in exactly two resolutions, and the magnification is consistent across each photo. Below are data points that show the best fit curve to describe the relationship between magnification and pixel to nm conversions.

MATLAB has a built-in word detector called the OCR which is a simple tool to use. I can find the phrase ‘mag’ and read the number underneath to find the magnification of the photo and use the trendlines from above to find the approximate conversion for pixels to nm. So now I have a consistent form of real -world measurements and my next step from here takes an exciting turn.

5. Object Detection

My next step is to use object detection to take a full photo of transistors and locate each one individually and perform all the steps described above without the need of the user to locate each one at a time. This is the meat and potatoes of computer vison you brag to everyone about and feel real cool about it. So how hard is it? Step 1: type imagelabeler into MATLAB. Step 2: draw boxes around what you want to find like so.

Step 3: repeat step 2 until mouse breaks. Step 4: run program and the result is…

Easy. All it takes is a premade algorithm and your sanity to do object detection. This is the progress I have made so far in my task but there is still more to do. So how do you learn image processing? The answer is to google everything and see what works for you. Hint: if your subject is really small then most things are not going to work on the first try.

Experiment, try something new: but most importantly learn when to move on

The wide variety of majors available at UC Santa Barbara gives every student a chance to study whatever it is they are most interested in. This study can be applied by performing research and other activities that enhance the learning process. It is important, however, that students are able to balance experimenting and learning when to move on.

Being a second year Computer Engineering student, I knew that my interests for a variety of fields were in development. When I talked to my digital design professor about his research, I found out that he does research on improved drug delivery systems. In other words, his team was trying to target cancer cells and attack them directly instead of destroying other healthy cells in the process of treating the bad ones. This, to me, seemed like an incredible opportunity. A chance to apply my Electrical Engineering and Computer Science background to something more than computers. But I also learned the variety of research that goes in under his lab, and this really motivated me to be involved as I saw myself being able to explore different opportunities.

So, when I first started my Gorman Scholar internship, I started by researching how proteins interact with osmolytes under different conditions. I first learned how to use programs such as VMD, which is used to build the protein structure, and NAMD which performs the simulations. After working on these programs and reading research papers I found myself not being very productive. Knowing myself, I knew this was because my interest in the subject has dulled. After spending two weeks, I decided that it was more beneficial and more appropriate for my future to work on different project. That is when I first learned about the Two-Photon Microscopy that my lab works to build in collaboration with other departments.

This device will be unique in such that they want to enhance it with a wireless technology that is able to conduct real life experiments. And my part will be to help write a code that is able to process and reconstruct an image from the data flowing from the device. So, for the past week I have been experimenting with CUDA programming. This is an NVidia technology that uses the computer’s graphics card instead of the CPU to execute the code. It has been really interesting and an interactive process, and I hope to accomplish something by the end of these next 5 weeks.

I had kept thinking that I wasted time, and that I didn’t learn anything. But I was wrong. By spending time doing something I didn’t like I was able to learn something about myself. I was also able to make a constructive decision at a critical time which I felt took a lot out of me to do. Either way, my advice for anyone reading this post, pretty much the only thing I recommend you take out of this is to Experiment, try something new, but know when to move on and that will come with practice.

A Sense of Fresh Air

The stress of school is a heavy, dense sort of fog that follows me and several of my UCSB peers from one point of campus to another with each progression of any given quarter. Ultimately, this creates an atmosphere that is easy to suffocate in. Just recently, a mass email was sent to every undergraduate Chemistry/Biochemisty major and minor that attend UCSB, and likely several faculty members. The purpose of this email was a Major Progress Check to an individual in the department who had earned a GPA under 2.0 for the year. The email “highlighted the benefits of maintaining a 2.0 GPA”, basically a reminder of being dismissed from the major if the GPA is not brought up, the email told an entire community about our fellow Chemistry Major’s struggles. For me, this situation filled my lungs with that dense fog and I felt embarrassed, upset, in utter amazement of such carelessness. I also felt a significant sense of hope for my peer, still believing in this stranger’s academic career. Following this email there was another, apologizing and asking the hundreds of people to please delete an inappropriate mistake made by one academic advisor. This mistake reminded me of the skill and fuel of opportunity and how in academia, the ranks are clear and opportunity must be gathered the same way one might gather pieces of a puzzle, with patience and intent. It took me a while to understand that your opportunities do not have to derive from your GPA, but can be from any place of passion, background, and individuality. There was a time here at UCSB where I received this same email and following this grief, I raised my GPA, and told myself that I would never let a number keep me from the experiencing of technique and the artform of working in a lab.

Applying for a program was my way of putting puzzle pieces together towards an opportunity like the Gorman Scholars program. A program that allows me to explore my own research project and to completely immerse myself in a research setting specifically in a Polymer Chemistry lab. Going into this, I was prepared to be surrounded in that dense fog but surprisingly I feel a sense of fresh air. The experiments, notes, papers, presentation, these factors that come together to ultimately provide me tools towards becoming skillful and creative, all without worrying about grades or GPA’s. The purpose of my work has many delightful intricacies and I can diverge down the various rabbit holes in which my project leads me into, all without having to center around dull topics that a class setting provides from day 1 in the syllabus to day 45 during that impossible final. Research is not a class. Presentations are not exams. Lab work is not school work. I think it is important for all students to remind themselves that the opportunity is there for you to grab. Even if you are barely scraping by for whatever reason, an opportunity will be open for you to gather the tools you DO have to go get that opportunity. So far, I have had a very positive research experience, with a great mentor and steady pace in the lab. Although I do not care to work in academia, I do want a career where I can have a creative voice in my research and continue to collect skills in which I can help optimize the world around me as a Chemist.