Julia was born in Baku, Azerbaijan, on the banks of the Caspian Sea. The daughter of a Russian army officer, Julia toured the former Soviet Bloc extensively, spending half a decade each in Kazakhstan and Hungary, before settling in St Petersburg, Russia. At age 16, Julia entered Moscow State University, Russia’s premier institution of higher learning. She distinguished herself studying symbolic logic in the Philosophy department, and at the age of 18 won an International Scholars competition which allowed her to come to the US to study at the University of Alabama, where she earned a BA in Philosophy and a BS in Chemical Engineering. Julia spent the next five years working as a process engineer and a research scientist before realizing that the corporate world wasn’t her cup of tea. She returned to the University of Alabama, where she earned her Ph.D. in Pure Mathematics.
Julia’s current research interests lie in the rapidly-growing and fascinating field of Quantum Computation. Her publications include The Hidden Subgroup Problem for Generalized Quaternions in Proceedings of the Fourth International Conference on Quantum, Nano and Micro Technologies, ICQNM 2010.
Julia’s love of learning has always gone hand in hand with her desire to teach, and she has taught not only mathematics, but philosophy, German, and Russian as well, to a variety of students, from undergraduates to (as a Graduate Fellow on a National Science Foundation GK-12 grant) high school and middle school students.
My philosophy of teaching and learning, in simplified terms, is based on the duality of received knowledge and earned knowledge. My preferred method of teaching, whenever possible, is analogy. For instance, I might tell my students that the gas pedal is on the right, the brake is on the left and turn the big wheel whichever direction you wish to go. This is received knowledge that nearly everyone can understand. However, if I ask the same students to drive to the mall and back (safely), they need the earned knowledge of how to properly manipulate gas, brakes and steering. Mathematics is a lot like driving in this respect: they both require more than knowledge; they require skill. And focused practice is the only way to build and refine any skill.