I was honored to give the Omega Rho keynote lecture at the 2021 INFORMS Annual Meeting. My talked was entitled “A journey through public sector operations research.” My presentation was recorded and can be viewed on YouTube.
I do not believe teaching is confined by the walls of the classroom or the boundaries of the university. I am passionate about talking to the public about science, engineering, operations research, and analytics. I especially enjoy talking about my research. Operations researchers and industrial engineers make important contributions to basic science and important applications, yet what we do has been a well kept secret. This is why I agree to give public talks about my research whenever I can. Doing so gives me an opportunity to educate the general public and improve scientific literacy. I have always hypothesized that most people would appreciate the work we do if they knew more about it. My experiences suggest that my hypothesis is true.
Advanced Analytics: From Emergency Response to Brackets
University of Wisconsin-Madison Industrial and Systems Engineering professor Laura Albert will talk about how engineers use math models and analytics to solve problems and design systems. She will provide an overview her discipline of operations research and advanced analytics and will discuss its wide ranging applications, focusing on examples from her research that addresses problems in emergency response and bracketology.
I gave an earlier version of this talk at the Middleton Public Library for their “Scholar’d for Life” lecture series. The lecture series is in partnership with the UW Madison Speaker’s Bureau (my profile is here). Taking the “Wisconsin Idea” as its starting point, this series aims to promote lifelong learning, intellectual curiosity, and engagement between academics and the community as a whole.
The organizers at the library asked me to speak about applications of industrial engineering. I thought that no one would show up for a talk marketed like that. I was wrong. About 100 people showed up for my talk. It was a packed house! The attendees were really engaged and asked me many questions after the talk.
I was thrilled that a few kids in middle school and high school came to my Middleton Public Library talk, including girls. I try to embody the spirit of the #ILookLikeAnEngineer movement in my public engagements to challenge stereotypes about engineering. One of the girls who attended the talk told me I reminded her of Lucy Wilde from Despicable Me 2 and showed me this picture:
I’m not sure if Lucy is my doppelganger, but I certainly like her hair and style 🙂
One of my blog posts about starting a fire at a gas station was featured on the math podcast The Other Half called “The Road Trip” by podcasters and professors Dr. Annie Rorem and Dr. Anna Haensch [Listen here] The podcast is about taking an optimal road trip (the Traveling Salesman Problem (TSP)) and rare risks associated with travel.
In The Road Trip, Anna and Annie look into the math that undergirds the great American summertime tradition of rolling down the windows, turning up the stereo, and touring the countryside by automobile.
Randy Olson has made the planning part easy by computing the optimal road trip across the U.S. His work to minimize the miles between landmarks in the lower 48 has been featured in the Washington Post and on Discovery News. In fact, Tracy Staedter of Discovery News can be credited not only with encouraging Olson to tackle this problem, but also with determining the list of landmarks he used. If you have a road trip you’d like to optimize, check out his code here.
And, because cars don’t run on math alone, we also consider the necessity of refueling on the road. In particular, we ask Laura McLay to weigh in on gas station safety, as she computes the conditional probability of blowing yourself up while you’re pumping gas.
“The Road Trip” is n excellent podcast! Thanks to Annie and Anna for doing such a great job and for being math ambassadors. I look forward to future episodes.
The Other Half is part of ACME Science, which offers several other math and science podcasts.
One thing I would like to add to the podcast is that there are real applications of the TSP and risk analysis. We academics don’t always sit up in our ivory towers coming up with silly problems to solve that are divorced from the real world. We need to be able to characterize rare risks for numerous applications (e.g., nuclear power risks) and then communicate those risks to others for managing rare but potentially catastrophic risks. I have a few links to related blog posts at the bottom of this post. Likewise, the TSP isn’t just used to plan summer road trips. It’s used by trucking and delivery companies to plan routes, in gene sequencing, for meals-on-wheels deliveries, and in emergency response after a disaster.
A second point is that we really can optimally solve many instances of the TSP, and certainly the ones used for planning road trips. We do not always have to settle for a solution that is “good enough.” It’s true that there are more feasible solutions to many problems than there are stars in the galaxy, but we don’t solve the problems by brute force. We more intelligently solve the problems using optimization algorithms such as the simplex algorithm (a linear programming algorithm) and cutting planes (an integer programming method). Optimization algorithms traverse through the search space and find the single optimal solution among trillions of possibilities sometimes in mere seconds or minutes. It’s truly astonishing and a great contribution to basic science.
I am very excited about a new project by Banafsheh Behzad (@banafsheh_b) and David Morrison (@drmorr0) promoting operations research. Their project is a YouTube channel called ORiginals: outstanding research in everyday language. I may be a bit biased because their first episode is about my research (Thanks Banafsheh and David!), but I think you will agree that the final product is gorgeous and leaves me anxious more.
Both Banafsheh and David are young OR professionals and both are already movers and shakers in our field. Banafsheh is a Professor of Information Systems at California State University, Long Beach and David is a Research Scientist and Director at a small startup. Banafsheh’s research is in healthcare and David was a finalist in the Doing Good with Good OR competition a couple of years ago. Both are very familiar with talking about OR with a societal impact, and that really comes through in their project. Their YouTube channel is brilliant, and it is great for our field! Please subscribe (do so here) and help spread the word.
If everyone in Dane County plays the lottery every day (unrealistic!) then we would expect 3+ people to win in a single day to happen every 0.71 years.
If half of everyone in Dane County plays the lottery every day (almost all the adults, still unrealistic!) then we would expect 3+ people to win in a single day to happen every 5.12 years.
If 1 in 10 people in Dane County play the lottery every day (in the ballpark of reality) then we would expect 3+ people to win in a single day to happen every 584 years.
If 1 in 20 people in Dane County play the lottery every day (in the ballpark of reality) then we would expect 3+ people to win in a single day to happen every 4620 years.
I am having trouble embedding the video, but you can go here to see it.
Area nerd explains the probability of winning the lottery, compares the likelihood of winning the lottery to being eaten by a bear.
Tips for working with the media:
You can overthink it. “Make things as simple as possible, but not simpler.” Except in this case, even simpler is good. You don’t have a couple of minutes to break apart a concept. Insightful comments that can fit in a tweet are good.
News moves fast. I was recorded 2 hours after getting the call for the story. In that two hours, I had to take care of things at work, pick up my daughters, and go home. There was very little time for research.
Crunch some numbers ahead of time to put things into perspective. You may only have time for back of the envelope calculations. If you don’t have all the information (like how many people play the lottery every day), make an assumption and test a few values.
I find it helpful to explain probabilities in terms of odds (1 in 1.6 million) and expected time to observe the event (every 584 years).
If you’re dealing with rare events, be prepared to compare the rare event to other rare events. Someone will definitely ask about the odds of getting struck by lightning.
Former INFORMS President Anne Robinson recently talked about operations research and analytics in a YouTube video. As President of INFORMS, she did a lot of work to promote analytics in the OR/MS community and to understand perceptions of analytics vs. operations research. I really appreciate what Anne has done for our field. Her research efforts found that people perceived operations research is a toolbox whereas analytics was perceived as an end-to-end process for data discovery, problem formulation, implementation, execution, and value delivery. This is an interesting finding.
This is Anne’s answer to the question: What is the role of OR in analytics?
“Operations research is on the top of the food chain when it comes to analytic capabilities and potential game changing results.”
I love this.
Anne’s challenge is for us to make decision-makers understand that OR is as vital and necessary as analytics. Evangelize early and often. Given the popularity of analytics, we should be able to make some inroads in educating our peers in STEM about OR, but in the long run this may be tough to do. Analytics is the new kid on the block, and it already seems to have reached widespread adoption, whereas operations research–while being at the top of the food chain–is still somewhat of a mystery to those outside of our fairly small field. Operations research has had an identity crisis for a long time, and I don’t see that coming to an end.
One of the podcasts I regularly listen to (“Stuff Mom Never Told you“) recently has a series of four podcasts on women in STEM (one each for the S, T, E, and M). The engineering and math podcasts were the most interesting. Both podcasts covered many topics, so I’ll just highlight a couple of the topics discussed here.
The math podcast [Link] covered the history of women in math and focused on gender differences in math achievement (and sometimes, the lack thereof).
The engineering podcast [Link] covered pipeline issues in engineering (recruiting and retaining women). They discussed the success of industrial engineering in attracting women. This podcast will be of particular interest to readers of this blog. High school students (both girls and boys) are often unaware of what engineering is, and as a result, students who are good at math choose majors like math and physics instead of engineering. Increasingly, medicine and forensic science are attractive career options to high school students thanks to television programming. This podcast will resonate with those of us in operations research, which is even less known as a field than engineering (Many know that engineering exists, few know what engineers do. Fewer know that operations research exists(!) ).
Here are a few of my posts about women in math, science, and computing: