Brian Keegan, Verrazano Class of 2019, completed major in Computer Science
Allow me to preface this by
saying that I was never a model student or at the top of my class, either
slacking off or becoming easily frustrated with the intensity of many of my
classes. In many ways, I’ve always thought of myself as the epitome of average.
I like to consider myself not necessarily intelligent, but incredibly lucky.
In the fall semester of 2017, I was taking Object Oriented Programming with Professor Natacha Gueorguieva. After submitting a few homework assignments, Professor Gueorguieva asked me if I wanted to do research with her because she was pleased with the quality of my homework (it just so happened that I preferred programming to math/science based classes). Knowing that I had to eventually complete my capstone project for Verrazano, I accepted. Little did I know what I was getting myself into.
In the first few weeks, my mentor introduced me to the topic of Deep Learning, something I have never heard of. Briefly explained, DL is a machine learning technique that uses artificial intelligence and algorithms inspired by the human brain to perform tasks that traditional computing is incapable of. It can perform predictions and recognition. Weather patterns, housing pricing, stock market prices, facial recognition, etc. are all examples of DLtasks.
Great, I thought. How hard could it be? Once 2018 came and the January winter break rolled around, I began spending most of my days off reading about DL and figuring out how to utilize the software. Luckily (luck is a recurring theme in this research journey of mine), I already had a gaming computer that I was able to utilize for deep learning research. My first challenge came with being able to get all of the software up and running. At the time, I was using the Linux operating system and the install process was so convoluted that I must’ve wiped my storage drive 6 or 7 times because I somehow kept destroying my Linux installations during the driver process (we needed to use special software to tell the graphics card in my computer how to do deep learning, essentially). Fast forward, and eventually I was able to mash together a research task in which I used deep learning to perform regression analysis, comparing different usable methods.
I presented this work at CSI’s Undergraduate Research Conference in February 2018. All done right? Wrong. My mentor saw potential in me and honestly, I thought she was crazy. Me? I used to sleep through my high school classes. I nearly failed Spanish. Yet here I was knee deep into graduate level research that I just barely comprehended. Fast forward to June after classes ended. My mentor presented to me an opportunity to write a 4-page IEEE research paper for MIT’s Undergraduate Research Conference in October 2018, where if it were to be accepted I would be published in the IEEE Xplore Digital Library and I would present my research at MIT. On top of it all, I only had about one month to do it. HA. I thought it was the biggest joke of my life. A delayed April Fool’s. I thought I should just play lotto in that moment and have better chances. After many sleepless nights and about 14 or 15 drafts, I submitted it, and the paper was accepted. I made my way to Cambridge, Massachusetts and presented my work on October 6th, 2018, never expecting to even step foot into MIT in my lifetime.
The College of Staten Island, the Verrazano Honors Program, and my mentor, Natacha Gueorguieva, helped to create the perfect environment for me to unlock hidden talents I didn’t even know I had. For that, I am eternally grateful. After all of this, I didn’t realize just how much I learned about DL until I actually sat down and thought about it. When you’re exposed to this research for a year, the knowledge definitely begins to accumulate. There are so many different applications of DL and it is a very new technology that will be relevant in our daily lives more than ever, so for me to have directly been a contributor to research into the field has undoubtedly been my greatest accomplishment. Since completing what I have done so far, I have passed on my research to new students and am currently exploring other opportunities outside of college. I hope that this anecdote inspires someone, whoever may be reading this, to achieve their goals.
In the fall semester of 2017, I was taking Object Oriented Programming with Professor Natacha Gueorguieva. After submitting a few homework assignments, Professor Gueorguieva asked me if I wanted to do research with her because she was pleased with the quality of my homework (it just so happened that I preferred programming to math/science based classes). Knowing that I had to eventually complete my capstone project for Verrazano, I accepted. Little did I know what I was getting myself into.
In the first few weeks, my mentor introduced me to the topic of Deep Learning, something I have never heard of. Briefly explained, DL is a machine learning technique that uses artificial intelligence and algorithms inspired by the human brain to perform tasks that traditional computing is incapable of. It can perform predictions and recognition. Weather patterns, housing pricing, stock market prices, facial recognition, etc. are all examples of DLtasks.
Great, I thought. How hard could it be? Once 2018 came and the January winter break rolled around, I began spending most of my days off reading about DL and figuring out how to utilize the software. Luckily (luck is a recurring theme in this research journey of mine), I already had a gaming computer that I was able to utilize for deep learning research. My first challenge came with being able to get all of the software up and running. At the time, I was using the Linux operating system and the install process was so convoluted that I must’ve wiped my storage drive 6 or 7 times because I somehow kept destroying my Linux installations during the driver process (we needed to use special software to tell the graphics card in my computer how to do deep learning, essentially). Fast forward, and eventually I was able to mash together a research task in which I used deep learning to perform regression analysis, comparing different usable methods.
I presented this work at CSI’s Undergraduate Research Conference in February 2018. All done right? Wrong. My mentor saw potential in me and honestly, I thought she was crazy. Me? I used to sleep through my high school classes. I nearly failed Spanish. Yet here I was knee deep into graduate level research that I just barely comprehended. Fast forward to June after classes ended. My mentor presented to me an opportunity to write a 4-page IEEE research paper for MIT’s Undergraduate Research Conference in October 2018, where if it were to be accepted I would be published in the IEEE Xplore Digital Library and I would present my research at MIT. On top of it all, I only had about one month to do it. HA. I thought it was the biggest joke of my life. A delayed April Fool’s. I thought I should just play lotto in that moment and have better chances. After many sleepless nights and about 14 or 15 drafts, I submitted it, and the paper was accepted. I made my way to Cambridge, Massachusetts and presented my work on October 6th, 2018, never expecting to even step foot into MIT in my lifetime.
The College of Staten Island, the Verrazano Honors Program, and my mentor, Natacha Gueorguieva, helped to create the perfect environment for me to unlock hidden talents I didn’t even know I had. For that, I am eternally grateful. After all of this, I didn’t realize just how much I learned about DL until I actually sat down and thought about it. When you’re exposed to this research for a year, the knowledge definitely begins to accumulate. There are so many different applications of DL and it is a very new technology that will be relevant in our daily lives more than ever, so for me to have directly been a contributor to research into the field has undoubtedly been my greatest accomplishment. Since completing what I have done so far, I have passed on my research to new students and am currently exploring other opportunities outside of college. I hope that this anecdote inspires someone, whoever may be reading this, to achieve their goals.
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