Tag Archives: podcast and video

podcasts on women in math and engineering

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:


decision quality and baseball strategy

Miss baseball? Love operations research and analytics? Watch Eric Bickel’s 46-minute webinar called “Play Ball! Decision Quality and Baseball Strategy” here:

husband-and-wife team matches kidney donors to patients in a documentary

Last week I blogged about the husband and wife team that created Major League Baseball schedules for more than two decades [Link]. I discovered another operations research collaboration between a husband and wife team.

Math professor Sommer Gentry and her surgeon husband Dorry Segev discuss how to match kidney donors with those in need of a transplant using networks and integer programming. Their collaboration is featured in the documentary “The Right Match” (below).

In the documentary, they mention how administrators in a single hospital could match up the pairs locally, where there were just a few patients. Integer programming models were needed when considering patients across multiple hospitals, where there are hundreds of patients in need of a transplant. Jump ahead to about seven minutes in to see their discussion of the the network structure of the problem and its similarity to max cardinality matching.

This is a nice video that would be suitable to undergraduate and graduate students studying optimizations. It might be particularly motivating for undergraduates who have learned about less useful applications like the diet problem and optimal mix problems in a linear programming course.

Watch the video here:

Visit their web site: http://www.optimizedmatch.com/

See some of the press their research has received here.

For more reading, I recommend reading more about it on Hari Balasubramanian’s blog here.

the craft of major league baseball scheduling – a journey from 1982 until now

Grantland and ESPN has a short video [12:25] on the couple who created the major league baseball schedules in the pre-Mike Trick era (1982-2004). The husband-and-wife team of Henry and Holly Stephenson used scheduling algorithms to set about 80% of the schedule. They found that the their algorithm could not come up with the entire schedule because the list of scheduling requirements led to infeasibility:

“It couldn’t do the whole schedule. That was where the big companies were falling apart. We analyzed the old schedules and found that none of them met the written requirements that the league gave to us. It turns out it was impossible to meet all of the requirements. So the secret was to really know how to break the rules.”

Watch the video here. The end of the video acknowledges how scheduling has evolved such that the entire schedules can be computer generated using combinatorial optimization software (the Stephensons even mention having to compete with a scheduling team from CMU). The video uses baseball scheduling as an avenue to illustrate how decision making and optimization has evolved in the past 30 years. I would highly recommend the video to operations research and optimization students.


operations research radio

Yesterday, Matt Saltzman, Mary Beth Kurz, and Doug Shier were on Clemson University’s radio program “Your Day.” It is an excellent and fun discussion about operations research. The program was archived and is available here:

Here is the program abstract:

Peter Kent is joined by Mary Beth Kurz, Associate Professor in Industrial Engineering, Matthew Saltzman, Associate Professor in Mathematical Sciences, and Doug Shier, Professor of Mathematical Sciences and Associate Dean in the School of Engineering and Science, all from Clemson University.  The discussion will focus on the practical application of quantitative methods in rational decision making to solve a wide range of problems arising in business and government, such as locating industrial plants, allocating emergency facilities, planning capital investments, designing communication systems, and scheduling production in factories

The show’s host discovered operations research through the Car Talk Puzzle TSP challenge (Mike Trick blogged about this challenge). Other OR applications discussed included circuit board manufacturing, finding the optimal number of check out lines to open, and whether single-queue/multiple-server models (e.g., bank tellers. Oh wait, no one does that any more. Let’s go with the DMV or going through customs) are better than multiple queue/multiple servers (e.g., the grocery store).

the forecasting models behind the power outages forecasts for Hurricane Sandy

I’m thrilled to have interviewed Seth Guikema about his forecasting models for hurricane power outages between his gigs on Good Morning America and Bloomberg. Seth is a professor at Johns Hopkins University, and he is the rock star of hurricane power outage forecasts. I wrote about a Baltimore Sun article about his research not too long ago. On the podcast, he and I chat about the methodologies he uses in his models as well as how news sources like to turn scientific research into digestible sound bites.

Listen here: (or go directly to the mp3 here)

You can listen to the episode below or you can go to the podcast web page (where you can download to iTunes, etc.) and feed. I recommend subscribing to the feed or going directly to the Punk Rock OR Podcast iTunes page, but you can also find the podcast episodes on this blog by clicking on “Podcast” under “Categories” in the left column.

Seth’s models have gotten a lot of coverage. Here are a few places where you can see Seth’s work translated for a general lay audience:

Seth’s forecasts as of 6am on 10/29:

Total prediction: 11 million without power
MD: 2 million
DC: 300,000
NJ: 3.4 million
DE: 425,000
PA: nearly 4 million
Here is an image of where the power outages will occur:

Power outage forecasts for Hurricane Sandy (courtesy of Seth Guikema)

new podcast interview with an undergraduate researcher

I published a new podcast, an interview with my undergraduate research assistant Taylor Richard from Oberlin College. He worked on an REU funded by the National Science Foundation. He did a wonderful job this summer. In the podcast, he talks about what he worked on this summer, the lessons he learned from doing research, and his love of horror movies.

This podcast should appeal to those of us in OR/MS and more broadly to undergraduates in the sciences who are thinking about graduate school. Please forward this to students who might be interested.

You can listen to the episode below or you can go to the podcast web page (where you can download to iTunes, etc.) and feed. I recommend subscribing to the feed or going directly to the Punk Rock OR Podcast iTunes page, but you can also find the podcast episodes on this blog by clicking on “Podcast” under “Categories” in the left column.