Juliane Mueller, Ph.D.

Julianne Mueller - Luis Alvarez Fellowship participants - August 25, 2015.

Computational Science Postdoctoral Fellow

Computational Research


Juliane Mueller received her Master's degree in applied mathematics from TU Freiberg in Germany in 2008. For her Master's thesis, she developed an optimization algorithm for solving the vehicle routing problem with time windows which is an important application problem where goods must be delivered to customers within certain time windows at minimal cost. During her Master's, she participated in the ERASMUS exchange program and visited Tampere University of Technology in Finland for one year. Juliane decided to continue her education and do a PhD in Applied Mathematics in Finland where she continued working on algorithm development for optimization problems. Part of her PhD research was done at Cornell University in New York. After graduating in 2012, she did a postdoc at Cornell for a year and a half. In 2014 she was selected as the Alvarez Fellow at Berkeley Lab.

1. What inspires you to work in STEM?

My research focuses on developing optimization algorithms. Optimization problems arise in many application areas, such as environmental engineering, climate modeling, and transportation research. Every application problem has its own characteristics and off-the-shelf optimization algorithms are often not applicable. I learn from the application engineers what features are needed in the optimization algorithm and this drives my research. Thus, I can help the domain scientist, for example, to improve their climate simulation codes. On the other hand, by closely working together with a domain scientist, I learn about the applications and their importance in every day life.

2. What excites you about your work at the Energy Department/Berkeley Lab?

A big part of my research is driven by optimization problems encountered in applications. At Berkeley Lab, we do research in a huge variety of application areas, for example, in combustion where we want to improve simulation codes. Thus, it is easy for me to find application problems which I can use to show that my algorithms work in practice. I really like that the scientists at the lab are easily approachable and very respectful.

3. How can our country engage more women, girls, and other underrepresented groups in STEM?

I believe that everyone has to figure out for themselves whether or not STEM fields are a career option. While school is an important place where underrepresented groups should be encouraged to stay in STEM fields, extra-curricular activities such as programming bootcamps led by members of the underrepresented groups could help to foster the interest in the filed. On the other hand, parents' encouragement plays the most important role in my opinion. The parents' task should be to expose the kids to all types of science equally and give their kids the option to choose what they are most interested in without biasing them towards non-STEM fields. Obviously, as a kid, it is hard to make a decision about the future. But the grades from school are one indicator of what the kid's talents are. Recognizing these talents and encouraging the kids to stick with STEM should be a task of both parents and teachers regardless of the kid's gender. The lab's participation in events such as the Solano Stroll where children and parents can learn together about the cool science that we do at the lab are a great way to arouse the kids' curiosity.

4. Do you have tips you would recommend for someone looking to enter your field of work?

My work is very application driven. Some basic understanding of the various applications is necessary in order to actually communicate with the application engineer. Hence, one important part is to be open to learning about the applications and the associated jargon. A major difficulty is often the formulation of the optimization problem. Sometimes information that does not seem to be important to the engineer is essential for developing an optimization algorithm. My focus is in particular on computationally expensive optimization problems. After having developed a suitable algorithm that can be used to tackle the optimization problem, it takes a lot of time to obtain the optimal solution due to the computational expense associated with the simulation models. Thus, it may at times be frustrating if there suddenly comes up an additional constraint that renders your solution infeasible. Hence, in my particular field, patience seems to be an asset.

5. When you have free time, what are your hobbies?

At the moment, my favorite pastime is climbing. The possibilities of climbing outdoors are vast in California (Yosemite, Bishop, Sonoma Coast, Tahoe, etc). There is a huge climbing community in the Bay Area and I am a member of the Bay Area Climbers Coalition. Occasionally, we spend weekends cleaning up popular climbing areas, improving access trails to control erosion. If I don't climb, I run. Animals are an important part of my life. I brought my kitty Gaussi from Finland and at the moment I have three foster kittens. I also read a lot, the topics range from history to fiction to nutrition.