Storm surge is often the most devastating part of a hurricane. Mathematical models used to predict surge must incorporate the effects of winds, atmospheric pressure, tides, waves and river flows, as well as the geometry and topography of the coastal ocean and the adjacent floodplain. Equations from fluid dynamics describe the movement of water, but most often such huge systems of equations need to be solved by numerical analysis in order to better forecast where potential flooding will occur. Much of the detailed geometry and topography on or near a coast require very fine precision to model, while other regions such as large open expanses of deep water can typically be solved with much coarser resolution. So using one scale throughout either has too much data to be feasible or is not very predictive in the area of greatest concern, the coastal floodplain. Researchers solve this problem by using an unstructured grid size that adapts to the relevant regions and allows for coupling of the information from the ocean to the coast and inland. The model was very accurate in tests of historical storms in southern Louisiana and is being used to design better and safer levees in the region and to evaluate the safety of all coastal regions. For More Information: A New Generation Hurricane Storm Surge Model for Southern Louisiana, by Joannes Westerink et al.

Mathematics and music have long been closely associated. Now a recent mathematical breakthrough uses topology (a generalization of geometry) to represent musical chords as points in a space called an orbifold, which twists and folds back on itself much like a Mobius strip does. This representation makes sense musically in that sounds that are far apart in one sense yet similar in another, such as two notes that are an octave apart, are identified in the space.This latest insight provides a way to analyze any type of music. In the case of Western music, pleasing chords lie near the center of the orbifolds and pleasing melodies are paths that link nearby chords. Yet despite the new connection between music and coordinate geometry, music is still more than a connect-the-dots exercise, just as mathematics is more than addition and multiplication. For More Information: The Geometry of Musical Chords, Dmitri Tymoczko, Science, July 7, 2006.

Origami paper-folding may not seem like a subject for mathematical investigation or one with sophisticated applications, yet anyone who has tried to fold a road map or wrap a present knows that origami is no trivial matter. Mathematicians, computer scientists, and engineers have recently discovered that this centuries-old subject can be used to solve many modern problems.The methods of origami are now used to fold objects such as automobile air bags and huge space telescopes efficiently, and may be related to how proteins fold. Manufacturers often want to make a product out of a single piece of material. The manufacturing problem then becomes one of deciding whether a shape can be folded and if so, is there an efficient way to find a good fold? Thus, many origami research problems have to do with algorithm complexity and optimization theory. A testament to the diversity of origami, as well as the power of mathematics, is its applicability to problems at the molecular level, in manufacturing, and in outer space. For More Information: http://db.uwaterloo.ca/~eddemain/papers/MapFolding/

The outcome of elections that offer more than two alternatives but with no preference by a majority, is determined more by the voting procedure used than by the votes themselves. Mathematicians have shown that in such elections, illogical results are more likely than not. For example, the majority of this group want to go to a warm place, but the South Pole is the group.s plurality winner. So if these people choose their group.s vacation destination in the same way most elections are conducted, they will all go to the South Pole and six people will be disappointed, if not frostbitten. Elections in which only the top preference of each voter is counted are equivalent to a school choosing its best student based only on the number of A.s earned. The inequity of such a situation has led to the development of other voting methods. In one method, points are assigned to choices, just as they are to grades. Using this procedure, these people will vacation in a warm place a more desirable conclusion for the group. Mathematicians study voting methods in hopes of finding equitable procedures, so that no one is unfairly left out in the cold. For more information: Chaotic Elections: A Mathematician Looks at Voting, Donald Saari

Invisibility is no longer confined to fiction. In a recent experiment, microwaves were bent around a cylinder and returned to their original trajectories, rendering the cylinder almost invisible at those wavelengths. This doesn't mean that we're ready for invisible humans (or spaceships), but by using Maxwell's equations, which are partial differential equations fundamental to electromagnetics, mathematicians have demonstrated that in some simple cases not seeing is believing, too. Part of this successful demonstration of invisibility is due to metamaterials electromagnetic materials that can be made to have highly unusual properties. Another ingredient is a mathematical transformation that stretches a point into a ball, "cloaking" whatever is inside. This transformation was discovered while researchers were pondering how a tumor could escape detection. Their attempts to improve visibility eventually led to the development of equations for invisibility. A more recent transformation creates an optical "wormhole," which tricks electromagnetic waves into behaving as if the topology of space has changed. We'll finish with this: For More Information: Metamaterial Electromagnetic Cloak at Microwave Frequencies, D. Schurig et al, Science, November 10, 2006.

The spools of wire below contain the only known live recording of the legendary folk singer Woody Guthrie. A mathematician, Kevin Short, was part of a team that used signal processing techniques associated with chaotic music compression to recapture the live performance, which was often completely unintelligible. The modern techniques employed, instead of resulting in a cold, digital output, actually retained the original concert.s warmth and depth. As a result, Short and the team received a Grammy Award for their remarkable restoration of the recording. To begin the restoration the wire had to be manually pulled through a playback device and converted to a digital format. Since the pulling speed wasn.t constant there was distortion in the sound, frequently quite considerable. Algorithms corrected for the speed variations and reconfigured the sound waves to their original shape by using a background noise with a known frequency as a "clock." This clever correction also relied on sampling the sound selectively, and reconstructing and resampling the music between samples. Mathematics did more than help recreate a performance lost for almost 60 years: These methods are used to digitize treasured tapes of audiophiles everywhere. For More Information: "The Grammy in Mathematics," Julie J. Rehmeyer, Science News Online, February 9, 2008.

The racing team is just as important to a car.s finish as the driver is. With little to separate competitors over hundreds of laps, teams search for any technological edge that will propel them to Victory Lane. Of special use today is computational fluid dynamics, which is used to predict airflow over a car, both alone and in relation to other cars (for example, when drafting). Engineers also rely on more basic subjects, such as calculus and geometry, to improve their cars. In fact, one racing team engineer said of his calculus and physics teachers, the classes they taught to this day were the most important classes I.ve ever taken.(1) Mathematics helps the performance and efficiency of non-NASCAR vehicles, as well. To improve engine performance, data must be collected and processed very rapidly so that control devices can make adjustments to significant quantities such as air/fuel ratios. Innovative sampling techniques make this real-time data collection and processing possible. This makes for lower emissions and improved fuel economy goals worthy of a checkered flag. For More Information: The Physics of NASCAR, Diandra Leslie-Pelecky, 2008.

Archimedes was one of the most brilliant people ever, on a par with Einstein and Newton. Yet very little of what he wrote still exists because of the passage of time, and because many copies of his works were erased and the cleaned pages were used again. One of those written-over works (called a palimpsest) has resurfaced, and advanced digital imaging techniques using statistics and linear algebra have revealed his previously unknown discoveries in combinatorics and calculus. This leads to a question that would stump even Archimedes: How much further would mathematics and science have progressed had these discoveries not been erased? One of the most dramatic revelations of Archimedes. work was done using X-ray fluorescence. A painting, forged in the 1940s by one of the book.s former owners, obscured the original text, but X-rays penetrated the painting and highlighted the iron in the ancient ink, revealing a page of Archimedes. treatise The Method of Mechanical Theorems. The entire process of uncovering this and his other ideas is made possible by modern mathematics and physics, which are built on his discoveries and techniques. This completion of a circle of progress is entirely appropriate since one of Archimedes. accomplishments that wasn.t lost is his approximation of pi. For More Information: The Archimedes Codex, Reviel Netz and William Noel, 2007.

Archimedes was one of the most brilliant people ever, on a par with Einstein and Newton. Yet very little of what he wrote still exists because of the passage of time, and because many copies of his works were erased and the cleaned pages were used again. One of those written-over works (called a palimpsest) has resurfaced, and advanced digital imaging techniques using statistics and linear algebra have revealed his previously unknown discoveries in combinatorics and calculus. This leads to a question that would stump even Archimedes: How much further would mathematics and science have progressed had these discoveries not been erased? One of the most dramatic revelations of Archimedes. work was done using X-ray fluorescence. A painting, forged in the 1940s by one of the book.s former owners, obscured the original text, but X-rays penetrated the painting and highlighted the iron in the ancient ink, revealing a page of Archimedes. treatise The Method of Mechanical Theorems. The entire process of uncovering this and his other ideas is made possible by modern mathematics and physics, which are built on his discoveries and techniques. This completion of a circle of progress is entirely appropriate since one of Archimedes. accomplishments that wasn.t lost is his approximation of pi. For More Information: The Archimedes Codex, Reviel Netz and William Noel, 2007.

With 468 stops served by 26 lines, the New York subway system can make visitors feel lucky when they successfully negotiate one planned trip in a day. Yet these two New Yorkers, Chris Solarz and Matt Ferrisi, took on the task of breaking a world record by visiting every stop in the system in less than 24 hours. They used mathematics, especially graph theory, to narrow down the possible routes to a manageable number and subdivided the problem to find the best routes in smaller groups of stations. Then they paired their mathematical work with practice runs and crucial observations (the next-to-last car stops closest to the stairs) to shatter the world record by more than two hours!

Although Chris and Matt.s success may not have huge ramifications in other fields, their work does have a lot in common with how people do modern mathematics research

* They worked together, frequently using computers and often asking experts for advice;
* They devoted considerable time and effort to meet their goal; and
* They continually refined their algorithm until arriving at a solution that was nearly optimal.
Finally, they also experienced the same feeling that researchers do that despite all the hours and intense preparation, the project .felt more like fun than work.
For More Information: Math whizzes shoot to set record for traversing subway system,. Sergey Kadinsky and Rich Schapiro, New York Daily News, January 22, 2009.
Photo by Elizabeth Ferrisi.
Map New York Metropolitan Transit Authority.
The Mathematical Moments program promotes appreciation and understanding of the role mathematics plays in science, nature, technology, and human culture.

A person needing a kidney transplant may have a friend or relative who volunteers to be a living donor, but whose kidney is incompatible, forcing the person to wait for a transplant from a deceased donor. In the U.S. alone, thousands of people die each year without ever finding a suitable kidney. A new technique applies graph theory to groups of incompatible patient-donor pairs to create the largest possible number of paired-donation exchanges. These exchanges, in which a donor paired with Patient A gives a kidney to Patient B while a donor paired with Patient B gives to Patient A, will dramatically increase transplants from living donors. Since transplantation is less expensive than dialysis, this mathematical algorithm, in addition to saving lives, will also save hundreds of millions of dollars annually. Naturally there can be more transplants if matches along longer patient-donor cycles are considered (e.g., A.s donor to B, B.s donor to C, and C.s donor to A). The problem is that the possible number of longer cycles grows so fast hundreds of millions of A >B>C>A matches in just 5000 donor-patient pairs that to search through all the possibilities is impossible. An ingenious use of random walks and integer programming now makes searching through all three-way matches feasible, even in a database large enough to include all incompatible patient-donor pairs. For More Information: Matchmaking for Kidneys, Dana Mackenzie, SIAM News, December 2008. Image of suboptimal two-way matching (in purple) and an optimal matching (in green), courtesy of Sommer Gentry.

What.s in store for our climate and us? It.s an extraordinarily complex question whose answer requires physics, chemistry, earth science, and mathematics (among other subjects) along with massive computing power. Mathematicians use partial differential equations to model the movement of the atmosphere; dynamical systems to describe the feedback between land, ocean, air, and ice; and statistics to quantify the uncertainty of current projections. Although there is some discrepancy among different climate forecasts, researchers all agree on the tremendous need for people to join this effort and create new approaches to help understand our climate. It.s impossible to predict the weather even two weeks in advance, because almost identical sets of temperature, pressure, etc. can in just a few days result in drastically different weather. So how can anyone make a prediction about long-term climate? The answer is that climate is an average of weather conditions. In the same way that good predictions about the average height of 100 people can be made without knowing the height of any one person, forecasts of climate years into the future are feasible without being able to predict the conditions on a particular day. The challenge now is to gather more data and use subjects such as fluid dynamics and numerical methods to extend today.s 20-year projections forward to the next 100 years. For More Information: Mathematics of Climate Change: A New Discipline for an Uncertain Century, Dana Mackenzie, 2007.

What.s in store for our climate and us? It.s an extraordinarily complex question whose answer requires physics, chemistry, earth science, and mathematics (among other subjects) along with massive computing power. Mathematicians use partial differential equations to model the movement of the atmosphere; dynamical systems to describe the feedback between land, ocean, air, and ice; and statistics to quantify the uncertainty of current projections. Although there is some discrepancy among different climate forecasts, researchers all agree on the tremendous need for people to join this effort and create new approaches to help understand our climate. It.s impossible to predict the weather even two weeks in advance, because almost identical sets of temperature, pressure, etc. can in just a few days result in drastically different weather. So how can anyone make a prediction about long-term climate? The answer is that climate is an average of weather conditions. In the same way that good predictions about the average height of 100 people can be made without knowing the height of any one person, forecasts of climate years into the future are feasible without being able to predict the conditions on a particular day. The challenge now is to gather more data and use subjects such as fluid dynamics and numerical methods to extend today.s 20-year projections forward to the next 100 years. For More Information: Mathematics of Climate Change: A New Discipline for an Uncertain Century, Dana Mackenzie, 2007.

Normally when creating a digital file, such as a picture, much more information is recorded than necessary-even before storing or sending. The image on the right was created with compressed (or compressive) sensing, a breakthrough technique based on probability and linear algebra. Rather than recording excess information and discarding what is not needed, sensors collect the most significant information at the time of creation, which saves power, time, and memory. The potential increase in efficiency has led researchers to investigate employing compressed sensing in applications ranging from missions in space, where minimizing power consumption is important, to MRIs, for which faster image creation would allow for better scans and happier patients. Just as a word has different representations in different languages, signals (such as images or audio) can be represented many different ways. Compressed sensing relies on using the representation for the given class of signals that requires the fewest bits. Linear programming applied to that representation finds the most likely candidate fitting the particular low-information signal. Mathematicians have proved that in all but the very rarest case that candidate-often constructed from less than a tiny fraction of the data traditionally collected-matches the original. The ability to locate and capture only the most important components without any loss of quality is so unexpected that even the mathematicians who discovered compressed sensing found it hard to believe. For More Information: "Compressed Sensing Makes Every Pixel Count," What's Happening in the Mathematical Sciences, Vol. 7, Dana Mackenzie.

A triple cork is a spinning jump in which the snowboarder is parallel to the ground three times while in the air. Such a jump had never been performed in a competition before 2011, which prompted ESPN.s Sport Science program to ask math professor Tim Chartier if it could be done under certain conditions. Originally doubtful, he and a recent math major graduate used differential equations, vector analysis, and calculus to discover that yes, a triple cork was indeed possible. A few days later, boarder Torstein Horgmo landed a successful triple cork at the X-Games (which presumably are named for everyone.s favorite variable). Snowboarding is not the only sport in which modern athletes and coaches seek answers from mathematics. Swimming and bobsledding research involves computational fluid dynamics to analyze fluid flow so as to decrease drag. Soccer and basketball analysts employ graph and network theory to chart passes and quantify team performance. And coaches in the NFL apply statistics and game theory to focus on the expected value of a play instead of sticking with the traditional Square root of 9 yards and a cloud of dust.

A triple cork is a spinning jump in which the snowboarder is parallel to the ground three times while in the air. Such a jump had never been performed in a competition before 2011, which prompted ESPN.s Sport Science program to ask math professor Tim Chartier if it could be done under certain conditions. Originally doubtful, he and a recent math major graduate used differential equations, vector analysis, and calculus to discover that yes, a triple cork was indeed possible. A few days later, boarder Torstein Horgmo landed a successful triple cork at the X-Games (which presumably are named for everyone.s favorite variable). Snowboarding is not the only sport in which modern athletes and coaches seek answers from mathematics. Swimming and bobsledding research involves computational fluid dynamics to analyze fluid flow so as to decrease drag. Soccer and basketball analysts employ graph and network theory to chart passes and quantify team performance. And coaches in the NFL apply statistics and game theory to focus on the expected value of a play instead of sticking with the traditional Square root of 9 yards and a cloud of dust.

Experts are adept at answering questions in their fields, but even the most knowledgeable authority can.t be expected to keep up with all the data generated today. Computers can handle data, but until now, they were inept at understanding questions posed in conversational language. Watson, the IBM computer that won the Jeopardy! Challenge, is an example of a computer that can answer questions using informal, nuanced, even pun-filled, phrases. Graph theory, formal logic, and statistics help create the algorithms used for answering questions in a timely manner.not at all elementary. Watson.s creators are working to create technology that can do much more than win a TV game show. Programmers are aiming for systems that will soon respond quickly with expert answers to real-world problems.from the fairly straightforward, such as providing technical support, to the more complex, such as responding to queries from doctors in search of the correct medical diagnosis. Most of the research involves computer science, but mathematics will help to expand applications to other industries and to scale down the size and cost of the hardware that makes up these modern question-answering systems. For More Information: Final Jeopardy: Man vs. Machine and the Quest to Know Everything, Stephen Baker, 2011.

It.s often a challenge to get from Point A to Point B in normal circumstances, but after a disaster it can be almost impossible to transport food, water, and clothing from the usual supply points to the people in desperate need. A new mathematical model employs probability and nonlinear programming to design supply chains that have the best chance of functioning after a disaster. For each region or country, the model generates a robust chain of supply and delivery points that can respond to the combination of disruptions in the network and increased needs of the population. Math also helps medical agencies operate more efficiently during emergencies, such as an infectious outbreak. Fluid dynamics and combinatorial optimization are applied to facility layout and epidemiological models to allocate resources and improve operations while minimizing total infection within dispensing facilities. This helps ensure fast, effective administering of vaccines and other medicines. Furthermore, solution times are fast enough that officials can input up-to-the-minute data specific to their situation and make any necessary redistribution of supplies or staff in real time. For More Information: Supply Chain Network Economics: Dynamics of Prices, Flows, and Profits, Anna Nagurney, 2006.

Some of the simplest and most well-known curves parabolas and ellipses, which can be traced back to ancient Greece are also among the most useful. Parabolas have a reflective property that is employed in many of today.s solar power technologies. Mirrors with a parabolic shape reflect all entering light to a single point called the focus, where the solar power is converted into usable energy. Ellipses, which have two foci, have a similar reflecting property that is exploited in a medical procedure called lithotripsy. Patients with kidney stones and gallstones are positioned in a tank shaped like half an ellipse so that the stones are at one focus. Acoustic waves sent from the other focus concentrate all their energy on the stones, pulverizing them without surgery. Math can sometimes throw you a curve, but that.s not necessarily a bad thing. Parabolas and ellipses are curves called conic sections. Another curve in this category is the hyperbola, which may have the most profound application of all the nature of the universe. In plane geometry, points that are a given distance from a fixed point form a circle. In space, points that are a given spacetime distance from a fixed point form one branch of a hyperbola. This is not an arbitrary mandate but instead a natural conclusion from the equations that result when the principle of relativity is reconciled with our notions of distance and causality. And although a great deal of time has elapsed since the discovery of conic sections, they continue to reap benefits today. For More Information: Practical Conic Sections: The Geometric Properties of Ellipses, Parabolas and Hyperbolas, J. W. Downs, 2010.

Cutters of diamonds and other gemstones have a high-pressure job with conflicting demands: Flaws must be removed from rough stones to maximize brilliance but done so in a way that yields the greatest weight possible. Because diamonds are often cut to a standard shape, cutting them is far less complex than cutting other gemstones, such as rubies or sapphires, which can have hundreds of different shapes. By coupling geometry and multivariable calculus with optimization techniques, mathematicians have been able to devise algorithms that automatically generate precise cutting plans that maximize brilliance and yield. The goal is to find the final shape within a rough stone. There are an endless number of candidates, positions, and orientations, so finding the shape amounts to a maximization problem with a large number of variables subject to an infinite number of constraints, a technique called semi-infinite optimization. Experienced human cutters create finished gems that average about 1/3 of the weight of the original rough stone. Cutting with this automated algorithm improved the yield to well above 40%, which, given the value of the stones, is a tremendous improvement. Without a doubt, semi-infinite optimization is a girl.s (or boy.s) best friend.

No one can predict who will commit a crime but in some cities math is helping detect areas where crimes have the greatest chance of occurring. Police then increase patrols in these "hot spots" in order to prevent crime. This innovative practice, called predictive policing, is based on large amounts of data collected from previous crimes, but it involves more than just maps and push pins. Predictive policing identifies hot spots by using algorithms similar to those used to predict aftershocks after major earthquakes. Just as aftershocks are more likely near a recent earthquake.s epicenter, so too are crimes, as criminals do indeed return to, or very close to, the scene of a crime. Cities employing this approach have seen crime rates drop and studies are underway to measure predictive policing.s part in that drop. One fact that has been determined concerns the nature of hot spots. Researchers using partial differential equations and bifurcation theory have discovered two types of hot spots, which respond quite differently to increased patrols. One type will shift to another area of the city while the other will disappear entirely. Unfortunately the two appear the same on the surface, so mathematicians and others are working to help police find ways to differentiate between the two so as to best allocate their resources.

Imagine trying to describe the circulation and temperatures across the vast expanse of our oceans. Good models of our oceans not only benefit fishermen on our coasts but farmers inland as well. Until recently, there were neither adequate tools nor enough data to construct models. Now with new data and new mathematics, short-range climate forecasting for example, of an upcoming El Nino is possible.There is still much work to be done in long-term climate forecasting, however, and we only barely understand the oceans. Existing equations describe ocean dynamics, but solutions to the equations are currently out of reach. No computer can accommodate the data required to approximate a good solution to these equations. Researchers therefore make simplifying assumptions in order to solve the equations. New data are used to test the accuracy of models derived from these assumptions. This research is essential because we cannot understand our climate until we understand the oceans. For More Information: What.s Happening in the Mathematical Sciences, Vol 1, Barry Cipra.

There.s more mathematics involved in juggling than just trying to make sure that the number of balls (or chainsaws) that hits the ground stays at zero. Subjects such as combinatorics and abstract algebra help jugglers answer important questions, such as whether a particular juggling pattern can actually be juggled. For example, can balls be juggled so that the time period that each ball stays aloft alternates between five counts and one? The answer is Yes. Math also tells you that the number of balls needed for such a juggling pattern is the average of the counts, in this case three. Once a pattern is shown to be juggleable and the number of balls needed is known, equations of motion determine the speed with which each ball must be thrown and the maximum height it will attain. Obviously the harder a juggler throws, the faster and higher an object will go. Unfortunately hang time increases proportionally to the square root of the height, so the difficulty of keeping many objects in the air increases very quickly. Both math and juggling have been around for millennia yet questions still remain in both subjects. As two juggling mathematicians wrote, .A juggler, like a mathematician, is never finished: there is always another great unsolved problem.

There.s more mathematics involved in juggling than just trying to make sure that the number of balls (or chainsaws) that hits the ground stays at zero. Subjects such as combinatorics and abstract algebra help jugglers answer important questions, such as whether a particular juggling pattern can actually be juggled. For example, can balls be juggled so that the time period that each ball stays aloft alternates between five counts and one? The answer is Yes. Math also tells you that the number of balls needed for such a juggling pattern is the average of the counts, in this case three. Once a pattern is shown to be juggleable and the number of balls needed is known, equations of motion determine the speed with which each ball must be thrown and the maximum height it will attain. Obviously the harder a juggler throws, the faster and higher an object will go. Unfortunately hang time increases proportionally to the square root of the height, so the difficulty of keeping many objects in the air increases very quickly. Both math and juggling have been around for millennia yet questions still remain in both subjects. As two juggling mathematicians wrote, .A juggler, like a mathematician, is never finished: there is always another great unsolved problem.

Many of today.s most striking buildings are nontraditional freeform shapes. A new field of mathematics, discrete differential geometry, makes it possible to construct these complex shapes that begin as designers. digital creations. Since it.s impossible to fashion a large structure out of a single piece of glass or metal, the design is realized using smaller pieces that best fit the original smooth surface. Triangles would appear to be a natural choice to represent a shape, but it turns out that using quadrilaterals.which would seem to be more difficult.saves material and money and makes the structure easier to build. One of the primary goals of researchers is to create an efficient, streamlined process that integrates design and construction parameters so that early on architects can assess the feasibility of a given idea. Currently, implementing a plan involves extensive (and often expensive) interplay on computers between subdivision.breaking up the entire structure into manageable manufacturable pieces.and optimization.solving nonlinear equations in high-dimensional spaces to get as close as possible to the desired shape. Designers and engineers are seeking new mathematics to improve that process. Thus, in what might be characterized as a spiral with each field enriching the other, their needs will lead to new mathematics, which makes the shapes possible in the first place. For More Information: .Geometric computing for freeform architecture,. J. Wallner and H. Pottmann. Journal of Mathematics in Industry, Vol. 1, No. 4, 2011.

Muthu Alagappan explains how topology and analytics are bringing a new look to basketball.

Van Wedeen talks about the geometry of the brain's communication pathways.

Despite the considerable variety among cities, researchers have identified common mathematical properties that hold around the world, regardless of a city.s population, location or even time.

Michael Trick talks about creating schedules for leagues.

Lydia Bourouiba talks about surface tension and the transmission of disease

Edward Witten talks about math and physics.

Researcher: Meredith Greer, Bates College. Going Over the Top Description: Meredith Greer talks about math and roller coasters.

Researcher: Sidney Redner, Santa Fe Institute
Moment: Moment Title: Holding the Lead Description: Sidney Redner talks about how random walks relate to leads in basketball.

Researcher: Norbert Stoop, MIT
Title: Adding a New Wrinkle
Description: Norbert Stoop talks about new research on the formation of wrinkles.

Researcher: Jackson Cothren, University of Arkansas
Moment Title: Scanning Ancient Sites
Description: Jackson Cothren talks about creating three-dimensional scans of ancient sites.

Researcher: Thomas Snitch, University of Maryland
Description: Thomas Snitch talks about nabbing poachers with math.
Audio files: podcast-mom-poaching-1.mp3 and podcast-mom-poaching-2.mp3

Researcher: Daniel Rothman, MIT. Dan Rothman talks about how math helped understand a mass extinction.

Researcher: Jim Papadopoulos, Northeastern University
Description: Jim Papadopoulos talks about his years of research analyzing bicycles.

Researcher: Andy Andres, Boston University Moment: http://www.ams.org/samplings/mathmoments/mm136-baseball.pdf Andy Andres on baseball analytics.

Researcher: Christine Darden, NASA (retired) Description: Christine Darden on working at NASA.

Researchers: Vikash V. Gayah and S. Ilgin Guler, Pennsylvania State University Description: Gayah and Guler talk about mitigating the clustering of buses on a route.

Researcher: Jordan Hashemi, Duke University Description: Jordan Hashemi talks about an easy-to-use app to screen for autism.

Rob Schneiderman talks about the metaphorical connections between math and music

Fumie Tazaki talks about creating the first image of a black hole and its shadow, which relied on Fourier transforms. About the work to make the image, she says, "Our collaboration has 200 members and we did it with all of our efforts."