Category Archives: People

We Are Hiring! Tenure-Track Position in Business Analytics, University of Miami

I’m excited to announce that my department at the University of Miami’s School of Business is hiring this year. Check out the job description below and please help me spread the word!

Tenure-Track Position in Business Analytics

The Department of Management Science in the School of Business at the University of Miami invites applications for a tenure-track Assistant Professor position in Business Analytics to start in the fall of 2018.

Applicants with research and teaching interests in all areas of business analytics or data science will be considered. The Management Science Department is home to a diverse group of faculty with expertise in data analytics and operations research, and offers a Master of Science program in Business Analytics, in addition to participating in the undergraduate, MBA, and Ph.D. programs of the School. The position affords the successful candidate the opportunity to have an immediate impact in a dynamic department that is rapidly growing in the area of business analytics. Duties will include research and teaching at both the graduate and undergraduate levels. Salary is competitive and commensurate with background and experience.

Applicants should possess, or be close to completing, a Ph.D. in a discipline related to business analytics or data science by the start date of employment. Applications should be submitted by e-mail to, and should include the following: a curriculum vitae, up to three representative publications, brief research and teaching statements, an official graduate transcript, information about teaching experience and performance evaluations (if available), and three letters of recommendation. All applications completed by December 1, 2017 will receive full consideration, but candidates are urged to submit all required material as soon as possible. Applications will be accepted until the position is filled.

The University of Miami offers a comprehensive benefits package including medical and dental benefits, tuition remission, and much more.

The University is an equal opportunity employer and encourages candidates regardless of gender, race, color, ethnicity, age, disability status or sexual orientation to apply.


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Filed under Analytics, People

Portuguese Pronunciation and Language Tips

I’ll be taking a group of 34 MBA students on an international business immersion trip to my native Brazil this Spring. We’ll be visiting about a dozen companies in the cities of São Paulo and Rio de Janeiro. This is an initiative created by the awesome Center for International Business Education and Research (CIBER) at the University of Miami.

I’d like my students to be able to pronounce some of the main sounds in Portuguese correctly because I know Brazilians pay attention and really enjoy when foreigners make an effort to say things properly. Therefore, I created a video in which I go over what I consider to be some of the most important things to know when speaking Portuguese (there are others, but I didn’t want the video to be too long).

You can access it on my YouTube channel here:

Moreover, the 2016 Olympic Games are coming, so I figured these tips could be useful for a larger audience as well. I wish American sports casters would watch this video because they murdered the pronunciation of everything during the World Cup in 2014.

Bonus material: My daughter, Lavinia Lilith, a.k.a. #LLCoolBaby, makes a short appearance at around the halfway mark.


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Filed under Brazil, People, Teaching, Tips and Tricks, Travel, Videos, YouTube

The Evil Twin and Other Fun Stories

Today marks Paul Rubin‘s retirement. To celebrate this special day in O.R.’s history, a few of us put together a nice collection of stories at (very special thanks to go Mary Leszczynski). My personal contribution is here. If you know Paul, make sure to check it out! If you don’t know Paul…nah, everyone knows Paul.

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The “Real” Reason Bill Cook Created the TSP App

By now, most people are aware of the latest Internet meme Texts from Hillary which is, by the way, hilarious. You’re also probably aware that Bill Cook created an iPhone App that allows one to solve traveling salesman problems (TSP) on a mobile phone! If you like optimization, you have to give this App a try; and make sure to check out the Traveling Salesman book too!

Inspired by Texts from Hillary I finally figured out the “real” reason why Bill Cook created the App. Here it is:

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Filed under Applications, Books, iPhone, Meme, People, Promoting OR, Traveling Salesman Problem

An O.R. Vocabulary Test for Non-Experts

I was talking to my wife the other day recalling how much fun she has while overhearing words from some of my research-related phone calls. We started to think about what comes to people’s minds when they hear an OR-related term whose definition is not obvious to them. I’m not talking about obscure and technical mathematical terms such as a “contrapolymatroid“, but terms at which a non-expert would actually be able to take an educated guess, such as “large-neighborhood search“. So I made a list of ten such terms and asked three friends (named A, B, and C) to define them to the best of their ability. The only rule was that they had to do it on the spot, off the top of their heads; no Googling allowed. Because none of them have training in OR, some of the answers turned out to be pretty interesting.

1. A global constraint.

A) All the stuff in the world that’s holding us back.

B) All the factors that prevent the open market from being truly open: laws, politics, foreign/domestic policy, national borders, etc.

C) Gravity.

2. Complementary slackness.

A) A dude who hangs out in a bar with no job, but complements the decor and vibe perfectly.

B) An equal and opposite reaction to whatever sectors are experiencing growth in the marketplace.

C) Time off from performing a task or responsibility granted by a superior or by oneself.

3. An odd cycle.

A) When you get your period unexpectedly; or that cycle on the washing machine that no one ever uses.

B) An economic cycle (quarter, fiscal year, etc.) which displays characteristics unlike the ones that preceded or succeeded it. In other words, in a sustained period of economic growth, it’s the one segment that shows recession.

C) A phenomenon with awkward tendencies and characteristics that is repeated every so often.

4. A spanning tree.

A) A tree that creeps from your neighbor’s yard to yours. Usually makes a huge mess in yours.

B) Has something to do with Ethernet networks.

C) A rather large plant with either a long branch span or time span on planet Earth.

5. A cutting plane.

A) A wood working tool that both cuts and planes.

B) No freaking clue.

C) A slice that intersects a 3D object in order to provide another viewpoint.

6. A shadow price.

A) The hidden cost of owning things. Like the extra cost of owning and maintaining a house or a luxury car.

B) The true representative value of goods and services, compared to the value dictated by the supply/demand of the marketplace.

C) A value for an item or service which can be obtained but that requires the buyer to perform an extensive search.

7. A comb inequality.

A) When you have a better comb than I do.

B) huh?

C) Inadequacies that persist despite efforts to eliminate them.

8. Duality gap.

A) The gap between personalities in someone with multiple personality disorder.

B) Again no idea.

C) A two-faced abyss. In other words, an alternative that may seem unfortunate but that possesses some advantages.

9. A feasible region.

A) The region where it is possible for you to live given your income, wants, and available houses.

B) Sounds like agriculture. Sorry, I got nothing.

C) An area or scope which could be a viable alternative for several purposes.

10. The first-fail principle.

A) When you get to repeat a class the first time you fail it, if approved by your high-school principal.

B) The idea that early adopters in a new sector of the market who fail will provide secondary adopters guidance through their failure. Not literal guidance, of course, but the secondary adopters will come into the marketplace and make decisions based upon others’ prior failures.

C) If you fail miserably the first time, don’t try again.

The first lesson I learned from this very non-scientific experiment is: if you’re at a party and somebody asks you what you do, you’re probably better off using an example. For instance: “Do you ever wonder how hurricane paths are estimated? That’s what I do.” You’d of course replace “hurricane paths” with your favorite problem. If the example comes before “scary” words, I believe the end result will be much better. If things go well, the ideal reaction by other person will be: “That’s so cool! What kind of training do you need to do that?” From that point on, you proceed to convince them that math is cool.

Secondly, the amusing nature of the answers above notwithstanding, this experiment got me thinking about how to make OR more visible and accessible to the general audience. That’s one of the goals of the INFORMS Public Information Committee (PIC), of which I’ve recently become a member. We already have some ideas and initiatives lined up, but I’m open to your comments and suggestions. Feel free to send me your thoughts by e-mail or via the comments section below. By the way, if you feel like doing this experiment with your own friends, feel free to send me their answers and I’ll add them to the bunch.


Filed under INFORMS Public Information Committee, People, Promoting OR

Can We Use Social Networks to Identify Poor Decision Making?

While suffering through the usual air travel woes recently, I felt compelled to tweet my feelings:

I was pleasantly surprised to see that Paul Rubin and Matthew Saltzman followed up with an interesting exchange:

Although I tend to agree with Paul that an outsider probably does not have enough information to decide whether or not the actions he/she sees are reasonably good given the situation (especially when it comes to the incredibly complex world or airline operations), I like Matthew’s general idea of an experiment to identify whether or not the outcome of a black-box decision making process is “good”.

Can that be done? Can we observe a black-box situation (or process) long enough to be able to tell whether the analytic machine inside the box could do better?

A large number of people carry smart phones these days, with constant connectivity to the internet. Twitter, Facebook, and FourSquare (to name a few) can determine our location, and there are other Apps that tell us which of our friends (and even non-friends) are close by. With all of this connectivity and location awareness, we can think of human beings as sophisticated sensors that collect and share information. We see a fire, a car accident, a traffic jam, an arrest, a fight, and immediately share that information with our network. In addition, human sensors are much better than electronic sensors because they can detect and interpret many other things, such as: the mood in a room (after the airline changes your gate for the third time), the meaning of an image, and so on.

Consider a hypothetical situation in which a crowded venue has to be evacuated for whatever reason. Perhaps some exits will be blocked and people will be directed to go certain places, or act a certain way. Human observers may notice a problem with the way security is handling the situation from multiple locations inside the venue, and from multiple points of view. The collection of such impressions (be they tweets, Facebook status updates, or something else) may contain clues to what’s wrong with the black-box evacuation procedure devised for that venue. For example, “avoid using the south exit because people exiting through there bump into those coming down the stairs from the second floor and everyone has to slow down quite a bit.”

In a world where Analytics and OR specialists struggle to convince companies to try new ideas, could this kind of evidence/data be used to foster collaboration? “I noticed that you did X when Y happened. It turns out that if you had done Z, you’d have achieved a better outcome, and here’s why…”

Is the airline example really too complicated to be amenable to this kind of analysis? I’m not sure. But even if it is, there may be other situations in which a social network of human sensors can collect enough information to motivate someone to open that black box and tinker with its inner workings a little bit. Those of you working in the area of social networks might be aware of something along the lines of what I (with inspiration from Matthew) have proposed above. If that’s the case, I’d love to read more about it. Please let me know in the comments.

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Filed under Applications, INFORMS Monthly Blog Challenge, People, Social Networks, Travel

There and Back Again: A Thank You Note

There were sub-freezing temperatures, there were snow flurries, there was a hail storm, and there was a tornado watch. No, I’m not claiming that my visit to Pittsburgh last week was as full of adventures as Bilbo Baggins’s journey, but it was very nice indeed.

I had the great pleasure of being invited by John Hooker and Willem-Jan van Hoeve to give a talk at the Operations Research seminar at the Tepper School of Business. Since John, André Ciré, and I are working together on some interesting things, I took the opportunity to spend the entire week (Mon-Fri) at CMU; and what a joy it was.

The Tepper School was kind enough to have a limo service pick me up from, and take me back to, the airport. I guess this is how the top business schools roll. It’s a great way to make a speaker feel welcome. Besides, my driver turned out to be an extremely friendly and easy-to-talk-to fellow. Thanks to him (and his knowledge of off-the-beaten-path roads), I managed to catch my return flight. Otherwise, a cab driver would have sat through miles of Friday rush hour, and I’d certainly have missed the flight.

I walked to campus every day and actually enjoyed the few minutes of cold weather (wow! I can’t believe I just said that!). Stopping at the Kiva Han to grab an almond biscotto and a small coffee, right across the street from Starbucks, was a daily treat. Walking around campus brought back great memories from my PhD-student days. It’s nice to see all the improvements, and all the good things that remain good. Upon leaving Miami, I had the goal of having Indian food for 10 out of my 10 meals (excluding breakfast). Although I managed to do it only 4 times, I’m pretty happy with my gastronomic adventures in Pittsburgh. The delicious semolina gnocchi served at Eleven is definitely praiseworthy.

Work-wise, it was a very productive week. We had interesting ideas and conversations. I’m very grateful to all of those who took time off their busy schedules to meet with me, be it to catch up on life, talk about research (including some excellent feedback on my talk), or both. Thank you (in no particular order) to Alan Scheller-Wolf, Javier Peña, Michael Trick, Egon Balas, Sridhar Tayur, Masha Shunko, Valerie Tardif, Lawrence Rapp, and of course John and Willem. Many thanks also go to André, David, and all the other PhD students who joined me for lunch on Friday. I really enjoyed meeting all of you and learning a bit about your current projects.

I noticed that John got rid of his chalk board and painted two of his office walls with some kind of glossy white-board paint. It’s pretty cool because it allows you to literally write on your wall and erase everything with a regular white-board eraser. Now I want to do the same in my office! (My white board is pretty small.) But I’m not sure if they’ll let me. Gotta check on that!

Overall, it was an awesome week and I hope I can do this again some time.

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Filed under People, Research, Travel