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Industry & Alumni

Alumni Spotlight: Fiete Krutein, Ph.D.

"My name is Fiete Krutein. I did my Masters and PhD at University of Washington ISE between 2017 and 2022. I currently work at Convoy, the country's leading freight market platform and digital freight brokerage. My current role is that of an Operations Research Scientist."


Fiete Krutein, Ph.D.

How did you first become interested in Industrial & Systems Engineering (ISE)?

I already did my undergrad degree in ISE, back in Germany, which is my home country. I was always interested in science-based decision making and the intersection of engineering and business.

What really motivated me to stay in the field and dive deeper, was an introductory course to Operations Research that I took during my semester abroad during undergrad at the University of Auckland in New Zealand. I could see how much power there is in making decisions based on modeling real world problems in terms of data and mathematics, and that fascinated me enough to focus on Operations Research and Data Science from that point on.

Why did you choose the University of Washington's ISE program?

I liked the flexibility that the program at UW offered. It was very attractive to me that I could easily take classes from around campus in fields like applied mathematics, statistics, computer science, engineering and business to complement my curriculum to my liking. It gave me the flexibility to choose my own path, based on what I wanted to learn and what I wanted to do research in. It was also very attractive to me how much interdisciplinary work is done in the research labs, which I see ISE being an ideal discipline for.

How has the ISE program at UW prepared you for your current position or field?

I would say that the core curriculum gave me a very solid and deep technical foundation in Data Science, Optimization, Statistics and Engineering that are very difficult to take the time to learn while working in industry. It may be possible to learn how to use a tool while working, but understanding the methods in depth and to the core is really difficult while working a full time job, as this takes a substantial amount of time and often gets deprioritized compared to other work items you may have. I harvest from this depth of knowledge daily, as it helps me a lot in making the right decisions in my current role around what kind of techniques we could use to solve different types of business problems, where potential problems will appear, and where to move the solutions to in the long term.

The research component of my PhD on the other hand taught me how to develop new solutions and drive progress of technical solutions by myself and transform an initial idea into a viable solution that can be used again and again to make decisions. I grew a lot personally and professionally through that journey at UW.

Were there any courses or projects at UW that you found particularly influential for your career?

I took a lot of very interesting classes, some very specialized. However, there were a few that I would say were particularly influential, especially in the beginning:

  1. Linear Optimization
  2. Integer Programming
  3. Data Analytics
  4. Inferential Statistics
  5. Machine Learning
  6. Global Optimization
  7. Data Structures and Algorithms

This is a mix of classes that give you both theoretical depth in OR and ML, and practical experience in how to implement solutions in programming languages. Combining these with classes in a discipline you want to dive deeper into is a great approach to gain depth and breath. For almost all of these classes programming skills will be very helpful.

I personally found most of the introductory programming classes at UW not very suitable for graduate students, as they were very dense and tailored towards undergraduate curriculums with limited flexibility to make meaningful progress on PhD research on the side. I would recommend self-paced programming classes and using programming languages to solve problems whenever you can to solve problems, even if it is not absolutely necessary. Practice is everything when it comes to programming.

Did you pursue any internships or co-ops during your time at UW? How did those experiences shape your career path?

Yes, I did an internship at the Tesla Gigafactory doing Material Planning for the battery production for the Model 3 electric vehicle during my Masters, and two internships at the Amazon Middle Mile Planning and Optimization Group during my PhD as a Research Scientist. Both of them shaped my career path substantially. The internship at Tesla helped me a lot in understanding the importance of creating a deep connection with operational teams when developing solutions for them and how to drive innovation in a high pace environment.

The internships at Amazon helped me to find my own path in my career and how to transform an initial idea into a viable product, even when there is a lot of ambiguity and many problems cannot be solved immediately. Learning how to make progress despite obstacles and imperfections, and staying persistent on the path to a finished solution was something I really took from that. In addition, I learned to not be afraid to learn things I knew very little about, e.g. through learning new programming languages or to work with new tools and new methods I had never used before. These helped me both in my academic research for my dissertation, and in my current job.

Tell us about a project or accomplishment in your current job that you’re particularly proud of.

I am the key scientist on an interdisciplinary team that develops new solutions for the fulfillment of truck shipments flexibly through multiple fulfillment channels. I developed the core routing algorithm that enables the company to build highly efficient schedules for trucks. This created and keeps creating high impact in the company and I am proud of how much impact that generates.

What is something about your work that may surprise students?

I work very interdisciplinary and a big part of my job is to educate and influence other team members and leaders with different backgrounds and to learn from them to make really good products together. You may be surprised to learn how much of my time is spent with that compared to how much time I actually spend data wrangling, modeling and coding.

Another thing that may be surprising is that I regularly have to reach beyond the boundaries of my core expertise to build good solutions quickly. Often this can mean a simplified solution that does not satisfy all text book conditions. In industry, we regularly look for a solution that provides us with the best return on our time and resource investment. Often, this means we do not need to engineer a solution all the way through to perfection to achieve the desired results. Often 20% of the effort deliver 80% of the result, and that is valuable to keep in mind when working in industry.

How do you continue to learn and grow in the field of ISE after graduation?

I stay involved through multiple ways. One is to keep staying informed about recent advances in research through keeping track of recent publications and to attend and present at conferences specific to my field. I also do research collaborations with academics and develop solutions together with them, that help me learn and grow and contribute to the field, while at the same time making impact in industry.

What message would you like to send to potential students considering the ISE program at UW?

UW ISE is a rather small ISE program in terms of size. This comes with pros and cons. While you may not find the same number of courses as you may find at a larger ISE program, you will be able to interact with professors and staff much more closely and build relationships that can help you to get what you want out of the program. I think I interacted with every professor and staff member in the department at some point and built good relationships with them.

The program also allows you easy access to take classes in other departments, and I would recommend not to be shy to take advantage of this and explore classes and projects outside of ISE and meet people in other fields. Interdisciplinary work is often more impactful than staying exclusively in your own discipline and UW is a fantastic place for that. Lastly, I would also consider where you want to live when making a decision on which school to choose. Seattle is a great city and the Pacific Northwest provides you with lots of activity options. There is really something for everyone and that is a benefit that you do not get everywhere.

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