This year marks NYU Shanghai’s second annual series of N.E.T. Awards for Academic Excellence. The N.E.T. Award for academic excellence aims to stimulate students’ progress in academic research and recognize students who have made outstanding achievements in their work. From a competitive pool of talented applicants, 4 recipients were selected across disciplines.
The N.E.T. Program Award Committee is honored to announce ECNU PhD candidate Mingyang Xie as this year’s recipient of the new N.E.T. Award for Academic Excellence. According to Xie, the N.E.T. Award “will help to bring my research to more people and help me to obtain more resources for my work.”
What is the current focus of your research?
As a member of NYU Shanghai’s Perception and Action Lab, my current work seeks to understand how our brains interpret visual and non-visual information to help us perceive object motion during self-motion, a scenario frequently encountered in daily life. For example, when you are driving a car on the road, being able to quickly perceive the movement of other cars is crucial for avoiding accidents.
When we first had our enrollment, I found that Professor Li was doing some very interesting work with virtual reality (VR), and I really wanted to conduct experiments using this technology. VR has become a powerful tool in our studies, enabling us to simulate motion in ways that feel real, even though you’re not actually moving. This control over experimental variables allows us to explore the complex interplay between visual and non-visual sensory inputs. In our behavioral studies, we aim to uncover the essence of perception, and through VR, we can study how visual and non-visual information work together.
Can you describe the support and mentorship that you have received from your faculty advisors?
Over the past four years, my mentor Professor Li has been instrumental in helping me to grow as a researcher, and has helped me at each stage along the way, from experimental design to data collection and paper writing. In our lab, we draw our questions from previous papers. If we are curious about something in the brain, Professor Li’s expertise helps guide us to related papers for comparative studies. She has great skill at devising simple but efficient experiments to test hypotheses, and is excellent at uncovering innovative methods to quickly find solutions. What’s great about our lab is that we have ten members who are all doing work that we want to do. We all have different questions and focuses and Professor Li never asks us to restrict our interests.
What is the biggest challenge you’ve faced as a researcher and how did you meet it?
When you first start out doing research, you often encounter problems. Things go differently than planned. I think the biggest challenge was to learn how to fail. You might fail many times, but you come to understand that you can fail and recover and that’s the most important lesson that you must learn in order to improve.
When I made my first program, I was learning a lot about it as I went. When programming, if you make a small error in the code you will have a big problem later on. In my experiment, I entered the object's speed slightly faster than I meant to and this had big repercussions in my results. I had to read through the code line by line to debug it, which was torturous but it paid off. In my experience I won’t do everything right the first time–it will take time and often multiple attempts–but gradually I know that I’ve improved and achieved the results I set out to obtain.
What do you find unique about the N.E.T. Program? How has being a member of the N.E.T. community affected you and your research?
N.E.T. allows us to meet and consult with researchers in our community who have different methods for approaching their research and different experience and perspectives that can aid in our work. It’s easy to seek out and find other researchers by email or through connections with their students to ask them questions, or arrange a time to meet. The professors in N.E.T. are very nice and approachable and eager to help you find what you’re looking for. We always have weekly 1-2 hour lunchtime seminars that provide an amazing opportunity to understand how others are conducting their experiments. We also have had opportunities to speak with scholars from outside of China. Collaborating with other professors, we broaden our horizons by learning from experts who are doing experiments with different technologies like fMRI.