By New faculty member Jiawei Zhang comes to UW-Madison from a postdoc at MIT. He “has always been fascinated by mathematics and its application to real-world problems,” and he focuses on “developing methods to train AI systems.” Zhang is looking forward to spending time outside around Madison’s lakes and meeting new people.
Hometown:
My hometown is Guangdong Province, China.
Educational/professional background:
I received my PhD in Computer and Information Engineering from The Chinese University of Hong Kong, Shenzhen, under the supervision of Prof. Zhi-Quan Luo. After that, I worked as a postdoctoral associate at the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology, advised by Profs. Asuman Özdaglar and Saurabh Amin.
How did you get into your field of research?
I have always been fascinated by mathematics and its applications to real-world problems, such as those in artificial intelligence and engineering. Designing efficient optimization algorithms is a crucial step in solving these problems, and I find that optimization also provides a powerful lens for understanding many practical challenges. This naturally led me to pursue research in optimization.
What are your areas of focus?
My research focuses on optimization theory and algorithms, as well as understanding real-world problems from the perspective of optimization. I aim to design efficient, scalable, generalizable, and robust algorithms to address challenges in artificial intelligence and engineering applications.
What main issue do you address or problem do you seek to solve in your work?
I focus on developing methods to train AI systems and make decisions in engineering applications under complex constraints and limited resources.
Please describe your work for people without a background in computer science:
For example, today’s generative models, such as diffusion models, can produce very high-quality images — like realistic pictures of cats. However, in many cases, we need to generate images that satisfy specific constraints, such as a certain size, color, or type of cat. My research focuses on how to “steer” diffusion models to generate images that meet these constraints while still preserving the essential characteristics of the cat. More broadly, this represents the challenge of solving generative problems under complex constraints.
What’s one thing you hope students who take a class with you will come away with?
I hope students will gain a solid grasp of theoretical tools and be able to apply what they have learned to real-world problems. My goal is for them to develop the ability to understand complex challenges through theory and propose effective algorithms to solve them.
What attracted you to UW-Madison?
I was drawn to UW–Madison by its excellent academic environment and strong research culture. Additionally, I find Madison to be a beautiful, friendly, and highly livable city, which makes it an ideal place to work and live.
What was your first visit to campus like?
The campus was beautiful, and I was impressed by the welcoming and vibrant atmosphere.
What are you looking forward to doing or experiencing in Madison?
I’m looking forward to enjoying outdoor activities around the lakes, meeting more friends in Madison, and exploring fun nearby attractions such as water parks, skiing areas, and local big cat rescue centers.
Do you feel your work relates in any way to the Wisconsin Idea? If so, please describe how.
My research focuses on making artificial intelligence and engineering systems more reliable and efficient, enabling them to serve people more safely, stably, and effectively.
Hobbies/other interests:
I enjoy boating, hiking, reading, spending time with friends, and playing with my cat.