Experts in the News

Brandon Pries is a graduate student in the School of Physics who researches computational astrophysics with Professor John Wise, using machine learning to study the formation and evolution of supermassive black holes in the early universe. Pries has also done extensive research with the NSF IceCube Collaboration. Pries recently shared a deep dive on neutrinos with astrobites, a daily literature journal (an "astro-ph reader's digest") supported by the AAS.

In a warming climate, meltwater from Antarctica is expected to contribute significantly to rising seas. For the most part, though, research has been focused on West Antarctica, in places like the Thwaites Glacier, which has seen significant melt in recent decades. In a paper published Jan. 19 in Geophysical Research Letters, researchers at Stanford have shown that the Wilkes Subglacial Basin in East Antarctica, which holds enough ice to raise global sea levels by more than 10 feet, could be closer to runaway melting than anyone realized. One of the study's co-authors is Winnie Chu, assistant professor in the School of Earth and Atmospheric Sciences. 

In the world of competitive speed puzzling, where an eye for detail and fast handiwork can impact completion time — down to the second — the ability to assemble hundreds of pieces quickly no matter where players stand gives them an edge. They are part of a growing group of jigsaw puzzle enthusiasts who participate in the sport — a fast-moving, hyper-focused variant of the relaxing pastime that has seen a resurgence in popularity. Faith Lindell-Taylor, Research Grants and Operations Manager in the College of Sciences, is quoted in this Washington Post story, and for good reason: she is a co-founder and current treasurer of the USA Jigsaw Puzzle Association. Lindell-Taylor told the Post that speed-puzzling organizers try to pick unreleased images to avoid giving any competitors an advantage.

Evolution can perform spectacular makeovers: today's airborne songbirds descended from the wingless, earthbound dinosaurs that roamed millions of years ago, for example. But some organisms seem to change very little, even over eons. Scientists have long wondered how these species withstand the pressures of natural selection. The prevailing hypothesis for this “stasis paradox” has been that natural selection keeps some species unchanged by selecting for moderate or average traits (so-called stabilizing selection) rather than selecting for more extreme traits that would cause a species to change (directional selection). But a study published in the Proceedings of the National Academy of Sciences USA contradicts this idea, showing that evolution constantly favors different traits in seemingly unchanging animals that improve short-term survival. In the long term, though, “all that evolution cancels out and leads to no change,” says the study's lead author, James Stroud, assistant professor and Elizabeth Smithgall-Watts Endowed Faculty in the School of Biological Sciences. 

Researchers from University of California San Diego, as part of a large collaboration with scientists around the world, have developed a new search tool to help researchers better understand the metabolism of microorganisms. Microbes are key players in virtually all biological and environmental systems, yet limitations in current techniques used to study microbial metabolism make it difficult to decode their interactions and activities.The new research, published in Nature Microbiology, directly addresses these limitations, which could ultimately transform understanding of both human health and the environment. Two of the many co-authors of the study are from the School of Chemistry and Biochemistry — Neha Garg, assistant professor, and Nicole Aiosa, graduate scholar.  

Eighteen-year-old Anu Iyer, a recent Little Rock, Ark., high school graduate now studying for her bachelor's degree at the School of Biological Sciences, has collaborated with a University of Arkansas for Medical Sciences (UAMS) research team and is the lead author for a research study in Scientific Reports, part of the Nature portfolio journals. The publication stems from Iyer’s work with other researchers using machine learning to detect Parkinson’s disease. Iyer was able to confirm the reliability of telephone voice recordings to detect Parkinson’s. The UAMS study team collected telephone voice samples from 50 people diagnosed with Parkinson’s and 50 healthy control participants, then applied machine learning classification with voice features related to phonation.

Integer linear programming can help find the answer to a variety of real-world problems. Now researchers have found a much faster way to do it. It's for when you need to optimize for problems involving whole-number amounts. What good is a factory optimization plan that manufactures 500.7 couches? For this, researchers often turn to a variant of linear programming called integer linear programming (ILP). It’s popular in applications that involve discrete decisions, including production planning, airline crew scheduling, and vehicle routing. “Basically, ILP is the bread and butter of operations research both in theory and practice,” said Santosh Vempala, adjunct professor in the School of Mathematics and the H. Milton Stewart School of Industrial and Systems Engineering, and Frederick G. Storey Chair in Computing and professor in the College of Computing.

Atlanta Science Festival (ASF) presented by Delta Air Lines, the city’s ultimate celebration of all things science and one of the largest of its kind in the country, returns March 9-23. All ages can experience more than 100 interactive and educational events. The Exploration Expo, a giant science bash in Piedmont Park, returns as the grand finale of the Festival. The Festival will kickstart with the Science and Engineering Day at Georgia Tech. An array of hands-on STEAM activities, exhibits, and demonstrations will feature robotics, brains, biology, space, art, nanotechnology, paper, computer science, wearable tech, bioengineering, chemical engineering, systems engineering, and more. 

Atlanta’s Snowmageddon, or Snowpocalypse, was 10 years ago this weekend. The winter storm brought the metro area to a complete halt. It also changed the way many in Georgia looked at winter weather. About two-and-a-half inches of snow fell on January 28, 2014, but it was enough to turn interstates across the metro into parking lots. Everyone tried to get home all at once as the snow fell. Slush froze on the roadways, trapping drivers. Children were forced to sleep at schools and some drivers chose to abandon their cars and walk instead. "The air was so cold. I think forecast models struggled to completely estimate correctly the type of wintery precipitation that was about to happen," Zachary Handlos, senior academic professional in the School of Earth and Atmospheric Sciences, explained. (This story was reprinted at AOL.com)

A major bottleneck in early detection is the molecular heterogeneity between ovarian cancer (OC) patients, which limits the likelihood of identifying individual biomarkers that are shared among patients. In a new study “A personalized probabilistic approach to ovarian cancer diagnostics,” published in Gynecologic Oncology, researchers from Georgia Tech have addressed this challenge by applying machine learning (ML) on patient metabolic profiles to identify biomarker patterns for personalized OC diagnosis. The Georgia Tech researchers include John McDonald, Professor Emeritus, School of Biological Sciences; Dongjo Ban, a Bioinformatics Ph.D. student in McDonald’s lab; Research Scientists Stephen N. Housley, Lilya V. Matyunina, and L.DeEtte (Walker) McDonald; and Regents’ Professor Jeffrey Skolnick, who also serves as Mary and Maisie Gibson Chair in the School of Biological Sciences and Georgia Research Alliance Eminent Scholar in Computational Systems Biology. (The study was also covered at The New York Post, Technology Networks, Medical Xpress, News-Medical.net, Medscape and Diagnostics World.)

Joe Mendelson, adjunct professor in the School of Biological Sciences and director of research at Zoo Atlanta, writes about a study currently underway at the zoo on play behavior in diamondback terrapins. Play behavior is exactly the way someone would interpret it as a human — something that’s fun and silly and sometimes is for a purpose, and sometimes the purpose seems to be simply fun. Students from Georgia Tech and Georgia State University are helping Mendelson in making these observations, and they're hoping to make the case soon that they've documented purposeless play behavior in a turtle. 

Yeast is maybe the best-understood microorganism in the world. Humans have leveraged yeasts' biochemical abilities to produce bread, alcohol, and fermented milk products since the dawn of civilization. Yeasts are also one of the most common organism “models” in biology laboratories. And important bio-factories for plenty of medicines and useful biomolecules. Still, yeasts need to be fed with sugar or other compounds to stay alive. At least, that was true until Anthony Burnetti, a research scientist working in the lab of William Ratcliff’s, associate professor in the School of Biological Sciences, managed to make yeast able to harvest the energy of light. The story highlights the potential impact of the research on biofuel production.