### 1. Please tell us a bit about yourself and what specifically motivates you. If you could do anything with your life, what do you imagine you’d do? The moment I understood what I wanted to do with my life was not in a laboratory. It was during the Wuhan lockdown, when a traditional trading business I was helping suddenly had to move online. There was no engineering team, no digital infrastructure, and no time to wait for someone else to solve the problem. So I built the system myself. Within 72 hours, I turned fragmented manual workflows into an online operating system that eventually processed more than 3,000 orders a day. That experience taught me something that has guided me ever since: when a system breaks, I want to be the person who figures out how to rebuild it. I am motivated by difficult problems that sit between technology and the real world. I enjoy understanding how something works, finding the bottleneck that prevents it from working better, and then building a solution that can scale beyond one person. If I could do anything with my life, I would build technologies that fundamentally expand what people and organizations can accomplish. I want to work at the frontier of AI, but I do not want to stop at research papers or prototypes. I want to build systems that people actually use—systems that transform industries, create opportunities, and eventually help intelligent machines understand and operate in the physical world. Ultimately, I want my career to follow one principle: turn impossible problems into working systems. ### 2. What excites you about STEM? How do you feel you could make a positive impact on the world through a job in information technology? What excites me most about STEM is that it turns curiosity into something tangible. An idea can begin as a question, become an algorithm, and eventually become a system capable of affecting thousands or even millions of people. I experienced this firsthand when I built digital infrastructure for a traditional business during the Wuhan lockdown. With no engineering team or external funding, I used simple technical tools to rebuild critical business workflows. The resulting system processed more than 3,000 orders per day, reduced manual errors by 95%, and helped move 85% of the company’s revenue online within six months. I learned that technology does not need to be complicated to be transformative; it needs to solve the right problem. Later, at Pika, I led a 12-person multimodal AI R&D team developing generative video products. I saw how quickly advances in machine learning could move from research ideas to products reaching a global audience. Today, I am exploring world models and embodied intelligence, with the goal of bringing AI beyond screens and into the physical world. Through information technology, I hope to make advanced capabilities more accessible and useful. I want to build tools that help small organizations operate more efficiently, enable people to accomplish tasks previously beyond their reach, and eventually allow intelligent systems to assist people in the physical environments where they live and work. For me, STEM is ultimately about leverage: using knowledge and technology to create impact far beyond the scale of one individual. ### 3. Please describe the greatest challenge you’ve had to overcome and how you managed to get past it. My greatest challenge was learning to take responsibility when there was no clear path forward. In 2020, during the Wuhan lockdown, the traditional trading business I was helping faced an existential problem. Offline operations had effectively stopped, customers needed to move online, and the company had no engineering team, digital infrastructure, or external funding. I was young, had never built a business operating system before, and had very little time to figure it out. My first reaction was to realize that waiting for the “right” resources was itself the problem. I broke the situation into the smallest solvable pieces: how orders entered the system, how inventory was tracked, how customers communicated, and how payments were settled. I learned what I did not know, built simple tools, tested them immediately, and kept replacing manual processes one by one. Within 72 hours, I had built the first functioning digital workflow. Over time, it grew into a system processing more than 3,000 orders per day, reducing manual errors by 95% and shortening the order-to-cash cycle by 60%. Within six months, 85% of revenue had moved online. The experience changed how I respond to uncertainty. I no longer see a lack of resources as a reason to stop. I see it as an engineering constraint. That mindset has stayed with me in research, entrepreneurship, and leadership: define the problem, build the first version, learn from reality, and keep moving.

When Wuhan went into lockdown in 2020, I learned that contributing to a community does not always mean volunteering in a visible way. Sometimes, it means making sure that an essential system continues to work when everyone else is struggling. My family operated a traditional food and supply-chain business in Wuhan. When the city shut down, our offline operations were suddenly disrupted, while supermarkets and local customers still depended on us for essential goods. There was no engineering team, no digital infrastructure, and no external funding. I realized that if we could not reorganize the business quickly, the consequences would extend beyond our company: employees could lose their livelihoods, customers could lose access to supplies, and local stores could face shortages. I decided to build the infrastructure myself. Within 72 hours, I rebuilt our core operations using Excel, lightweight automation, and custom scripts. I digitized order management, inventory tracking, customer communication, and settlement processes, allowing the business to continue operating despite the lockdown. The system eventually processed more than 3,000 orders per day, reduced manual errors by 95%, and enabled 85% of our revenue to move online within six months. More importantly to me, it helped keep our employees working and our customers supplied during an extraordinarily uncertain period. That experience changed how I think about technology and community. I realized that the most meaningful technology is not necessarily the most sophisticated technology. Its value comes from whether it makes people more resilient when circumstances become difficult. I also learned that I want to build systems that amplify the capacity of ordinary people rather than simply automate isolated tasks. Since then, I have pursued AI research and product development, working on multimodal generative systems and now exploring world models and embodied intelligence. I see these technologies as an opportunity to extend the lesson I learned in Wuhan: intelligent systems should ultimately operate in the real world and help people navigate uncertainty. In the future, I want to contribute by building AI systems that make critical real-world services more accessible, resilient, and responsive—particularly for communities and organizations that do not have the resources to build advanced technology themselves. I hope to combine engineering, entrepreneurship, and research to create tools that can move from laboratories into everyday life. The lockdown taught me that community contribution is not measured only by how many people you can reach directly. Sometimes it begins with one broken system, one urgent problem, and the decision to take responsibility for fixing it. I want to keep doing exactly that—building systems that allow people and communities to withstand disruption and create opportunities for others.