I’m “Tony” Runzhe Yang (杨闰哲), currently a third-year Ph.D. student at Computer Science Department and Neuroscience Institute at Princeton University. Previously, I worked as a research intern at Cornell University. I received my Bachelor Degree in Computer Science from ACM Honors Class, Zhiyuan College, SJTU.
As a junior researcher in the field of Artificial Intelligence, I am enthusiastic about all kinds of puzzles about human intelligence. My research interests include Reinforcement Learning, Deep Learning and Neuro-Inspired Machine learning, Bayesian Inference and Graphical Models, Game Theory and Multi-Agent Systems, as well as their application in Dialogue Systems, Linguistics, Robotics and Scientific Discoveries, especially Neuroscience.
During my childhood days, mathematical axioms, physical laws, and philosophical propositions sketched my initial imagination of this vast universe. They built my faith in the search for truth, and brought me a dream of rationalizing the weird existence. However, the weirdest existence in this universe is undoubtedly nothing else than ourselves – the group of beings which lay down the axioms, sum up the laws and put forward propositions. In this sense, any attempt to rationalize ourselves is easily trapped in circular reasoning or distant fantasy, and the unrevealed truth is probably beyond the limited expressive power of our language.
But fortunately, we are at the time close to the truth than ever. Computer Science and Neuroscience provide us with a bridge connecting philosophical fantasy and scientific reality. Nowadays, computers are empowered to recognize speech, classify images, drive cars, and defeat humans in strategic zero-sum games. The AI envisioned by Alan Turing, Marvin Minsky, John McCarthy, Herbert Simon and many other great thinkers and pioneers is gradually coming true in the context of massive competition with human cognition and reasoning, rewarding us with profound understanding of ourselves on both individual and social dimensions from a testable perspective, and leading us to explore even more challenging and essential problems:
- What are general mathematical models of perceiving, reasoning and learning?
- How does intelligence emerge from complicated structures?
- What should be the new paradigm of scientific research in this AI era?
- How do agents interact and cooperate to build things, interweave concepts and discover knowledge?
Our journey is not so long yet. I believe we will answer all the questions above eventually. And I know it is my great happiness to contribute towards it.