UMD and Underwriters Laboratories to Lead Worldwide Partnership to Improve Understanding of Wildfires and Fire Modeling
Each year, hundreds of thousands of people die in fires that cause economic damage equivalent to 2% of combined global income. With that toll expected to continue to increase, researchers from the University of Maryland will co-lead two new global initiatives designed to expand our knowledge and understanding of wildfires and fire modeling. Supported by $1 million in funding from Underwriters Laboratories (UL), the projects will involve scientists from across the International Fire Safety Consortium (IFSC) and UL’s Fire Safety Research Institute.
UMD Announces Recipients of Independent Scholarship, Research and Creativity Awards
The University of Maryland Office of the Provost and Office of the Vice President for Research have announced ten recipients of this year’s Independent Scholarship, Research and Creativity Awards (ISRCA). The grant funding will support a variety of research studies and scholarly explorations ranging from poetry and literature to the immigrant experience. “We are excited to support these projects, which embody faculty creativity and demonstrate the versatility and broad expertise of our researchers,” said Senior Vice President and Provost Jennifer King Rice.
UMD Researchers Invited to Participate in U21 Health Research Exchange on Jan. 12
The University of Maryland research community is invited to participate in the Universitas 21 Health Research Exchange Information Session on January 12, 2022 to engage in a conversation with international partners on healthcare research and practice.
START Team Identifies Key Contributors to Effective Influence Operations
Earlier this month, researchers from START’s Unconventional Weapons and Technology (UWT) division—Megan Rutter, Rhyner Washburn and UWT Director Dr.
Women's Work
Over 16,000 women served overseas during World War I. Yet as Armistice Day marked the war’s final chapter, the stories of women who sacrificed—in overseas hospitals or as wives and mothers back home—were destined to become footnotes. More than a century later, a University of Maryland graduate is rewriting that narrative, revealing the grassroots efforts spearheaded by women of the WWI generation to honor this service, not carved in marble statuary, but through community service and advocacy and in hospitals and respite houses.
Making Moves to Counter Misinformation
While the world contended with a pandemic, social media platforms and other sources spewed billions of misleading health messages at users—more than 3.8 billion times on Facebook over the course of a year, according to one study—a dynamic that University of Maryland researchers and their colleagues say can lead to adverse public health outcomes ranging from mistrust in reliable information sources to deaths from disease.
Can You Bank Happiness?
Can you revel in happy moments now, to soak them in and store them up to help you through future sadness? New research from Maryland Smith’s Ali Faraji-Rad finds that many people actively try to bank their happiness so they can draw on it later to cope with a sad event.
$1.14M from the State of Maryland will Match Private Donation to Establish Two Brendan Iribe Endowed Professorships at UMD
The University of Maryland will receive $1.14 million from the Maryland E-Nnovation Initiative (MEI) to fully match a private donation establishing the Brendan Iribe Endowed Professorship in Computer Science and the Brendan Iribe Endowed Professorship in Electrical and Computer Engineering. These new endowed professorships, made possible by the generosity of alum Brendan Iribe (ee-REEB’), will be held by experts in robotics, autonomy, artificial intelligence (AI) and machine learning.
When Helping Hurts the Helper
Helping out a co-worker—hard to find fault with that, right? In fact, depending on the source and kind of help being offered, it might be perceived more like a threat than a relief, according to new University of Maryland research.
Humans vs. Machines: Examining the Effectiveness of Automated Topic Modeling Evaluations
Topic modeling—a machine learning technique originally developed as a text mining tool for computer scientists—is now widely used by historians, journalists and analysts to make sense of large collections of text. These probabilistic models produce various lists of related words, and each list corresponds to a subject in the collection. But despite their popularity, there are flaws in the way that topic models are evaluated for their accuracy, which ultimately affects how useful they are to the people that rely on them.