4/17/2018 - Research led by Lydia Sohn, professor of mechanical engineering, could greatly improve the speed and accuracy of cancer diagnosis by exploiting the different speeds with which cancerous and healthy cells move through micropores.
4/16/2018 Berkeley Lab - New research from Berkeley Lab, co-led by materials science and engineering Ph.D. candidate Shuren Lin, finds useful new information-handling potential in tin sulfide, a candidate “valleytronics” transistor material that might one day enable chipmakers to pack more computing power onto microchips.
4/16/2018 - Nearly 70 percent of the energy produced in the United States is wasted as heat — from exhaust pipes, high-speed electronics and other sources. Now Berkeley engineers have developed a thin-film system that can produce energy from these waste sources at unprecedented levels.
4/11/2018 - A research team led by Gerbrand Ceder, professor of materials science and engineering, has devised a way to build lithium battery cathodes using materials that have greater capacity, and a far lower price, than the traditional cobalt.
4/10/2018 - Berkeley engineers, led by EECS professors Rikky Muller and Michel Maharbiz, have taken implanted neural dust sensors forward by building the smallest, most efficient wireless nerve stimulator ever.
3/15/2018 The Atlantic - Popular mapping and routing apps may make overall traffic conditions worse in some areas, new research by Alexandre Bayen and the Institute of Transportation Studies suggests.
3/15/2018 - Berkeley researchers led by Ting Xu, professor of materials science and engineering and chemistry, have found a unique way to keep proteins active in synthetic environments, using this breakthrough technology to create fiber mats that can trap chemical pollution.
3/6/2018 Berkeley Lab - In an effort to teach computers to guide science, researchers at Berkeley Lab and UC Berkeley have come up with a novel machine learning method, which they call "iterative Random Forests," that enables scientists to derive insights from systems of previously intractable complexity in record time.
3/5/2018 - Berkeley researchers are using machine learning to encourage people to get more exercise. They have developed an algorithm for an exercise app that automatically adjusts goals to keep them within reach and to keep users motivated.
3/1/2018 - Neuroscientists, including Berkeley EECS professor Jose Carmena, have demonstrated the astounding flexibility of the brain by training neurons that normally process input from the eyes to develop new skills, in this case, to control a computer-generated tone.