Hannah received her Ph.D. in chemical physics from Harvard University under the supervision of Alan Aspuru-Guzik, specializing in algorithm development for near-term quantum computers. Hannah’s current research interest is in improving the performance of variational quantum algorithms to address industry-relevant problems. While there are several ways to think about boosting the performance, she is particularly interested in (1) better understanding and designing parameterized quantum circuits that are used in a number of these algorithms and (2) developing better strategies for tuning or optimizing the parameters of parameterized quantum circuits.
One thing I really like about the field of quantum computing is that it is highly interdisciplinary. Because there are so many unanswered questions and so many directions to explore, we often observe people from a wide variety of fields collaborating to answer research questions or come up with a quantum or quantum-inspired algorithm to approach an application. Through projects like these, everyone learns something new — whether it’s some new scientific concept or a new perspective towards a well-known problem.
Is there a problem I don’t dream of solving (with quantum)??
These aren’t really things, but I really value and appreciate relationships with other people, whether it’s family, friends, or colleagues. I learn so much from the people I meet and the conversations we share. But for things, I would list Legos, Korean food, and chocolate ice cream.
In college, if not chemistry, I would have pursued a major in history.