“For me, it is really exciting to do research in cooperation with industry”, Qing Zhao says. “My work is theoretical in nature and focuses on fundamental research problems. Now I have the opportunity to take a step further and explore how theories and algorithms from my research can be applied to real-world problems. Chalmers is well-known for its close and fruitful relations with the industrial companies in the region, and I am glad to be involved in this.”
Qing Zhao´s research interests include sequential decision theory, stochastic optimization, machine learning, and algorithmic theory with applications in infrastructure, communications, and social economic networks.
A great deal of this will be of use in the MoRE2020 project ”Active Learning for event detection in large-scale information networks”. In short, the project aims at teaching a safety system in a vehicle, connected to the cloud, to detect rare events in the surrounding traffic environment as quickly and as reliably as possible. The challenge lies in the large number of hypotheses, the noisy observations, and the limited prior knowledge on the rare events.
“Using data sharing, where information is extracted from massive data streams, a collective learning in large complex networks is being built up”, Qing Zhao explains.
”Qing Zhao adds vital complementary knowledge to Chalmers and our department in the field of machine learning and reinforcement learning”, says Professor Tomas McKelvey, who is the leader of the signal processing research group. “We strive for expanding our research in that direction, and therefore I am pleased that we managed to enroll her for quite a long time, thanks to the jubilee professorship.”
Understanding fascinates her
A scientific problem that keeps fascinating her, and many more researchers over decades, is the so-called multi-armed bandit problem. It is a classic mathematical framework for online learning and sequential decision making under unknown models. The problem can be likened to gambling on a slot machine with multiple arms, where the player faces the dilemma of staying on a seemingly good arm (exploitation) versus trying out a less observed arm (exploration).
“The problem, first considered in 1933, fascinated the research community for many years, while the answer eluded them until early 1970s. Legend has it that the problem, formulated during World War Two, so sapped the energies and minds of Allied analysts that a suggestion was made to have the problem dropped over Germany as the ultimate instrument of intellectual sabotage”, Qing Zhao says with a smile. ”After the breakthrough in early 1970s, researchers continued to search for the simplest proof and understanding of the optimal solution, until an ingenious proof, expressible in a single paragraph of verbal reasoning, was given in 1992.”
“I find this type of research, this pursuit of understanding, most inspiring. To me, it is not only about solving a problem, it is about really understanding a problem and finding the pieces that, as simple as possible, comprise the solution. The task is not complete until one understands the underlying causes. I like unwinding the complexity of a problem. I find it most satisfying when simple solutions emerge from a morass of complications.
This was also one of Qing Zhao´s statements when she was an invited speaker at a well-attended seminar at Chalmers arranged by the network Women in science, WiSE
. She also shared some advice for young female researchers who are in the beginning of their academic careers.
“Play to your strengths rather than compensating for your weaknesses. If you are really good at something, let that be your focus. To establish yourself as a prominent researcher, you need to concentrate your effort rather than spreading too thin. Choose a topic, choose a research community, and generate results of critical mass.”
A tough start in life
No doubt, Qing Zhao is an eminent scientist with an impressive career record. Her start in life was however not very favourable.
“It could have been me”, that was the headline of the last slide from her WiSE seminar, showing young girls worn down with household chores in rural villages in China.
A couple months old, Qing Zhao was brought by her aunt to a small village in northern China and grew up there. The village had no electricity or running water. Her aunt was illiterate, there were no books in her home, and the village school was very poor with a single teacher teaching all subjects to all kids of all ages in the village.
“When I was seven I moved back to live with my parents, my older sister and younger brother”, Qing Zhao says. “At age seven, I was not able to count to ten. If I had stayed in the village, I probably would be living my life like those girls in the picture, without much education. Thinking back, now being a mother myself, I realise what a difference it makes to give children the right opportunities in life in terms of a nourishing environment, intellectual stimulation, education and encouragement. You never know what they will accomplish!”