Zhou Zang is awarded three grants for her work to develop machine-learning models and artificial-intelligence tools to increase agricultural productivity and sustainability. She is an assistant professor of biological systems engineering at the University of Wisconsin-Madison. Zhou Zhang, an assistant professor of biological systems engineering at the University of Wisconsin-Madison, recently was awarded three grants for her work to develop machine-learning models and artificial-intelligence tools to increase agricultural productivity and sustainability. The U.S. Department of Agriculture's National Institute of Food and Agriculture awarded the grants. Project Description: The research team is comprised of Zhang and Matthew Digman, both assistant professors of biological systems engineering, and Paul Mitchell, a professor of agricultural and applied economics – all at UW-Madison.

Our voices may convey subtle clues about our mood and psychological state. Now, scientists are using artificial intelligence to pick up these clues, with the aim of building voice-analyzing technologies that can identify individuals in need of mental-health care. But others caution they could do more harm than good. At the University of Alberta, computing science PhD student Mashrura Tasnim has developed a machine-learning model that can recognize the speech qualities of people with depression. Her goal is to create a smartphone application that would monitor users' conversations and alert their emergency contacts or mental-health professionals when it detects depression.

This year, for the first time, the Manhattan, Kan.-based company tapped an artificial-intelligence tool called Xander to analyze responses. Xander can determine whether an employee feels optimistic, confused or angry, and provide insights to help manage teams, the tool's developers at Ultimate Software Group Inc. said. From a block of text, the software analyzes answers to open-ended questions based on language and other data, assigning attitudes or opinions to employees. One top executive at SPS learned from recent survey analysis that he needed to work on his temper. "One of my lowest scoring items was maintaining my composure under stress," he said of the feedback from his direct reports.

This year, for the first time, the Manhattan, Kan.-based company tapped an artificial-intelligence tool called Xander to analyze responses. Xander can determine whether an employee feels optimistic, confused or angry, and provide insights to help manage teams, the tool's developers at Ultimate Software Group Inc. ULTI -1.88% said. From a block of text, the software analyzes answers to open-ended questions based on language and other data, assigning attitudes or opinions to employees. One top executive at SPS learned from recent survey analysis that he needed to work on his temper. "One of my lowest scoring items was maintaining my composure under stress," he said of the feedback from his direct reports.

This year, for the first time, the Manhattan, Kan.-based company tapped an artificial-intelligence tool called Xander to analyze responses. Xander can determine whether an employee feels optimistic, confused or angry, and provide insights to help manage teams, the tool's developers at Ultimate Software Group Inc. ULTI 2.55% said. From a block of text, the software analyzes answers to open-ended questions based on language and other data, assigning attitudes or opinions to employees. One top executive at SPS learned from recent survey analysis that he needed to work on his temper. "One of my lowest scoring items was maintaining my composure under stress," he said of the feedback from his direct reports.