Recognition & Honors
Jakoah Brgoch (Chemistry) and members of his research group (Ziyan Zhang, Aria Mansouri Tehrani, Blake Day), in collaboration with a researcher at Manhattan College, have reported a machine learning model that can accurately predict the hardness of new materials, allowing scientists to more readily find compounds suitable for use in a variety of applications. The work was reported in Advanced Materials. Superhard materials are in high demand in industry, from energy production to aerospace, but up until now, finding suitable new materials has largely been a matter of trial and error based on classical materials such as diamonds. The researchers report finding more than 10 new and promising stable borocarbide phases; work is now underway to design and produce the materials so they can be tested in the lab.
Albert Cheng (Computer Science) was inducted as a Distinguished Member of the Association for Computing Machinery. In 2020, 64 distinguished members were named; recipients are longstanding ACM members who are selected by their peers for a range of accomplishments that move the computing field forward. Cheng was recognized for outstanding scientific contributions to computing.
Krešimir Josić and William Ott (Mathematics), former postdoc Bhargav Karamched, and mathematics student Megan Stickler, with collaborators from the Bernstein Center for Computational Neuroscience in Germany and University of Colorado Boulder, published a study that tackles how groups make decisions and the dynamics that make for fast and accurate decision making. The research, published in Physical Review Letters, found that networks that consisted of both impulsive and deliberate individuals made, on average, quicker and better decisions than a group with homogenous thinkers. Josić, senior author of the study, noted that the process works best when individuals in a group make the most of their varied backgrounds to collect the necessary materials and knowledge to make a final decision.
Mark Meier (Physics), director of UH’s Low Frequency Seismic Technologies Consortium, accepted the Licensing Executive Society’s 2020 Deal of Distinction Award in the Chemicals, Energy, Environment, and Materials Sector. In his acceptance speech, Meier noted that “the Low Frequency Seismic Technology License and Consortium Foundational Agreement between UH and the ExxonMobil Upstream Research Company licenses a valuable body of research developed by ExxonMobil to UH under terms that encourage both academic and industrial participation in furthering research and technological development, and eventual commercialization.” Part of the license agreement included the transfer of prototype experimental equipment to UH. Last year, the consortium received a 78,000-pound Counter Rotating Eccentric Mass Vibrator — eXperimental Prototype. It creates strong forces at low frequency, generating wavelengths four times greater than current capabilities.
Weiyi Peng (Biology & Biochemistry, Center for Nuclear Receptors and Cell Signaling) is part of a group of cancer and Parkinson’s research experts investigating whether the diseases are caused by similar gene alterations. The group is looking at why changes in the LRRK2 and Parkin genes can cause Parkinson’s and cancer. Peng, who is both an M.D. and Ph.D., is part of a national group who received nearly $6 million from Aligning Science Across Parkinson’s to study the similar pathogenesis of the two diseases. UH will receive about $1M of grant funds. Peng’s group will provide immunology expertise that could eventually help develop new, immune-based therapies for Parkinson’s.
Jonny Wu (Earth & Atmospheric Sciences) and graduate student Spencer Fuston’s recent work on reconstructing the vanished Resurrection plate offshore western Canada was featured as one of the “10 Geological Discoveries That Absolutely Rocked 2020” by Live Science. Wu and Fuston digitally reconstructed a tectonic plate and showed that its movement likely gave rise to an arc of volcanoes in Alaska and western Canada some 60 million years ago. The findings, published in October in the Geological Society of America Bulletin, could help geologists better predict volcanic hazards as well as mineral and hydrocarbon deposits.