Aspiring to make an impact and learning how to do better everyday.
I’m interested in various aspects of Artificial Intelligence and Deep Learning, as well as the intersection of those domains. My passions first developed after hearing Dr. William Edward Hahn explain the premise of deep learning in a reasearch meeting on synthetic drug design. Instantly captivated by this “new-to-me” technology, I had to know more. I soon found myself spending most of my spare time in the Machine Perception and Cognitive Robotics Lab where I not only made close friends, but found my love for computational science. Ready to graduate with an undergraduate degree in biology, I hadn’t the slightest clue how to code or even how to open a terminal. Slowly, with dedication and encouragement from the lab, I learned some secrets of the trade (made an even closer friend: search engine). As I explored the interworkings of neural networks and software development, I began to understand the vast capacity this technology had on the biomedical field and eventually many other fields. Enchanted by deep learning, I forged several projects from worm detection and degradomics to visual augmentation. Quite frankly, all my gust and enthusiasm had prohibited me from saying “no” to any problem I thought could be solved with neural networks. Eventually I learned this is the curse of deep learning; it can help so many facets of human life it sometimes seems anything is possible and even if anything is possible, everything isn’t, not with only 24 hours.
Eventually, I learned. Simply put by the good words of Jeffery Hammerbacher, “The best minds of my generation are thinking about how to make people click ads.” The desire to make an impact grew and I somehow learned how to say no more. I also learned how to manage projects with teams that could help solve problems together, giving me more time to persue deeper interest. As deep as deep learning is, it’s not hard to argue we have a long way to go to get Data on the team. Data is iconic, not because he’s from arguably the best TV show of all time, Star Trek The Next Generation, but because he eximplifies a stationary target of artificial general intelligence. He does so in a way that compliments mankind, in a way that helps humanity explore the best parts of ourselves and in a way that is often integrating the best parts of machines with the worst parts of humans. These features are an ideal encapsulation of my hope for artificial general intelligences’ role in the evolution of mankind.
As we continuing developing the field of deep learning and artificial intelligence, I hope to aid in this viewpoint and offer viable applications of such work to our world.