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Multi-discipline research makes a big impact

Computer Science Professor Liz Bradley (left), meets with Rhonda Hoenigman (center) and their collaborator, Assistant Professor in Ecology & Evolutionary Biology Nichole Barger, to discuss an algorithm that determines where plants will grow efficiently.

Multi-discipline research makes a big impact

Liz Bradley is a great professor because she loved being a student. The computer science professor graduated from MIT with three degrees, a B.S., M.S., and Ph.D., in electrical engineering and computer science. And, while earning these degrees would be more than enough to earn bragging rights, Bradley earned her two graduate degrees while training as an Olympic rower. She took fifth place in the 1988 Olympic Games.

鈥淚 was lucky that I had a graduate advisor who understood that I had 11 Olympic workouts a week,鈥 she says of her graduate experience. 鈥淏ut, being at MIT was a fire hose of fabulous things to think about.鈥

Bradley acts as an advisor on the Biofrontiers Institute鈥檚graduate program because cross-discipline work is something she is passionate about. Computer science now plays a huge role in managing the massive data sets in the biosciences.

鈥淐omputers, by default, are cross-disciplinary. They are used everywhere in scientific discovery. We solve equations with computers because we can鈥檛 solve them with pencil and paper,鈥 she says. 鈥淎nd it is because I am open to working across disciplines that I tend to be the home in the department for the student projects nobody else will supervise.鈥

Rhonda Hoenigman is pursuing a Ph.D., and with Bradley鈥檚 encouragement and advice, she has created a computer algorithm that aids in the design of efficient landscapes: those that offer the best growth, with the most shade, using the least amount of water. This 鈥渁gent-based鈥 algorithm allows the plants to move themselves in a virtual world, and find the places they would grow the best. Hoenigman has a vision for the algorithm to help building planners save water while cooling structures with shade鈥攁 necessity for water-starved areas like the American Southwest.

Caleb Phillips, another student who works with Bradley, also created a new algorithm that addresses sustainability: one that can show us how to redistribute food waste.听 Phillips鈥 algorithm takes into account how much food is being thrown away across a given region, like Boulder County, and also calculates the cost of rescuing it and redistributing it to organizations in need across that region.

Most food rescue organizations use a warehouse model, which usually prevents them from handling fresh produce and other perishables. In addition, transportation costs are higher when trucks are needed to deliver food from a central warehouse.

With the help of this algorithm, the organization that Phillips founded,听, takes surplus foods from stores and restaurants, and delivers them immediately to organizations that will use them. The kicker: Boulder Food Rescue picks up and delivers food using bikes and trailers, keeping costs at their lowest.

鈥溍厶掖狡平獍嫦略 70 or 80 pounds a day is a normal delivery, but we rescued 950 pounds the day after Thanksgiving,鈥 says Phillips, who has to notch his belt a little tighter because of all the bike deliveries he now makes. On days where food donations are too heavy, or the snow is too deep, Phillips鈥 organization has access to trucks via Boulder鈥檚 CarShare program. 鈥淭here is definitely enough food in Boulder County to feed everyone,鈥 he says.

鈥淚t鈥檚 not about us faculty, it鈥檚 about them, the students,鈥 Bradley says. 鈥淭hat鈥檚 what grad school is about.鈥 And it must be that old Olympic discipline she has that allows her to mentor incredible students, while still producing amazing work of her own.

Bradley studies chaos theory and computer performance dynamics. In her work, dropping the last decimal place off of a number that has six places after the decimal may seem insignificant鈥攏ot even enough to worry about in a huge data set. But those insignificant numbers can have huge impacts across a large collection of data or across a long period of time. This theory is also known as the 鈥淏utterfly Effect,鈥 referring to the flapping of an insect鈥檚 wing that could cause enough atmospheric change, over time, to create a devastating hurricane. Bradley is using this theory to work toward learning to predict and manage how computers and data interact.

You don鈥檛 have to look too hard to see that there is another 鈥淏utterfly Effect鈥 going on in Bradley鈥檚 world. If chaos theory is predicting how a small change can equal a large effect, you only need to look as far as Bradley鈥檚 students to see how her interactions are exactly that: the butterfly鈥檚 wing creating a hurricane of change.