The UC Berkeley team consists of William, Phillip, Piyush, and James, and is the only fully undergraduate team in the competition.
Under the advisement of Professor John DeNero, the team members first met through Machine Learning at Berkeley. They plan on training their socialbot by using techniques from a branch of AI research called reinforcement learning. The team believes that humans produce engaging conversation by understanding the motivation of the people with whom they communicate, and imparting that idea algorithmically onto the Alexa socialbot may be the key to achieving human-level conversation.
William G. - Team leader
William is majoring in Pure Mathematics and EECS with a focus on deep reinforcement learning and theoretical neural network research. During his time at Berkeley, William cofounded Machine Learning at Berkeley, a graduate and undergraduate organization devoted to bridging the gap between existing ML and AI curriculum as well as between industry and research.William is majoring in Pure Mathematics and EECS with a focus on deep reinforcement learning and theoretical neural network research. During his time at Berkeley, William cofounded Machine Learning at Berkeley, a graduate and undergraduate organization devoted to bridging the gap between existing ML and AI curriculum as well as between industry and research.
I am an undergraduate EECS major with a primary interest in machine learning, particularly deep learning. I am a member of the Machine Learning @ Berkeley, OpenBrain team. Through this team, I have become well acquainted with state of the art reinforcement learning algorithms. I also have a background in robotics, through the FIRST robotics competition. As a part of that competition, I built a computer vision Android app to find a target and provide information to be able to autonomously aim at said target.
Phillip is a Junior in Electrical Engineering and Computer Science. He was introduced to machine learning in high school through a project implementing neural networks from scratch. At UC Berkeley, he co-founded Machine Learning at Berkeley, which offers students the opportunity to engage in research and industry projects that utilize machine learning. Additionally, he developed a DeCal (student-led course) teaching data science and machine learning through the Kaggle competition platform.
I'm an undergrad pursuing degrees in Electrical Engineering and Computer Science (EECS) and mathematics. I've been drawn to machine learning and data science, which lie at the intersection of computer science and mathematics, and have elements of philosophy and neuroscience. After graduating, I hope to work towards the goal of making machines consciously think. In my free time I enjoy hiking, reading, and hanging out with friends.
John Denero - Faculty advisor
John joined the UC Berkeley CS division faculty in 2014 to focus on undergraduate education in computer science. He received his Master's in Philosophy from Stanford University and his PhD in Electrical Engineering and Computer Science from UC Berkeley in 2010. His research focuses both on natural language processing and computer science education. Prior to Berkeley, John was a senior research scientist at Google working primarily on Google Translate and natural language processing.