We are very happy to welcome a new MCL member, Yijin Chen. Here is a quick interview with Yijin:
1. Could you briefly introduce yourself and your research interests?
My name is Yijin Chen. I joined MCL this summer. My main research interest is image recognition based on Green Learning, building mathematically interpretable visual recognition algorithms that can surpass the performance of deep networks without relying on backpropagation. Before joining MCL, I mainly focused on applications of artificial intelligence, as well as some work related to hardware, such as embedded systems and FPGA.
2. What is your impression of MCL and USC?
My first impression of MCL is that it is a very principled lab. Its emphasis on mathematical clarity, reproducible hard metrics, and the requirement that every module can be explained from beginning to end is very different from the “tune until it works” atmosphere I had encountered before. The USC campus itself is also beautiful, and the school’s culture is very appealing. I feel extremely proud to become a member of MCL and of USC.
3. What is your future expectation and plan in MCL?
MCL is a lab that places great emphasis on mathematical thinking, and I hope I can strengthen my own mathematical thinking here. Deep learning and Green Learning are two very different things, and I hope I can approach research on Green Learning from a more rational, more mathematically grounded perspective. We are currently working on advancing Green Learning into its next stage. In the long run, I hope I can make contributions to this work, and grow into a researcher who can explain every design choice from first principles.
