November 18, 2020
Doug Weber, a new faculty member in the Department of Mechanical Engineering, has built a multi-disciplinary research program combining neuroscience, engineering and medicine to develop neural prosthetic technologies to help people recover from stroke, spinal cord injury and limb loss. Prior to coming to CMU he spent 15 years at the Swanson School of Engineering at the University of Pittsburgh. “My research has always focused on studying how the brain senses and controls movement in our arms and legs — the simple act of reaching and grasping a cup of coffee engages dozens of muscles and millions of neurons that communicate with each other through the neural networks in our spinal cord and brain to generate smooth and efficient actions,” Weber said. His approach is to understand how the nervous system processes and communicates information about movement and what changes occur in these neural networks after disease or injury. Such knowledge is crucial for engineering new solutions to restore function to the arms and legs. At Carnegie Mellon, Weber plans to work closely with collaborators in neuroscience, computer science and engineering to build machines that can move like humans and also sense and reason, enabling them to work safely and effectively alongside humans or independently. He started his research at CMU this fall and will teach classes in the spring 2021 semester. Learn more about Weber’s work.
Alyssa Lawler, a Ph.D. student in biological sciences, and her CMU colleagues have developed a technique to isolate a type of brain cell associated with Parkinson's disease symptoms, allowing them to study that cell type in detail. The technique, which works only in specially bred mice, costs less than previous methods for isolating these brain cells. By using it, Lawler and her colleagues already have detected previously undiscovered changes to how the diseased neurons sense and use oxygen.The researchers describe the technique and their findings in a research paper published online by the journal JNeurosci. Find out more about the technique.
Justine Sherry, an assistant professor in the Computer Science Department and a member of CyLab, is part of a research team that's developed an intrusion-detection system that achieves speeds of 100 gigabits per second using a single server. Intrusion-detection systems are the invisible intelligence agencies in computer networks that scan every packet of data passed through the network, looking for signs of any one of the tens of thousands of cyberattack styles they recognize. "What was previously possible with 100-700 processor cores and a whole rack of machines, we can now do with five processor cores in a single server," Sherry said. Key to the researchers' success is using a field-programmable gate array (FPGA), an integrated circuit that users can program with customized code. The researchers programmed the FPGA specifically to detect intrusion, employing algorithms that are significantly faster than previous ones and that could not run on traditional processors. Learn more about the new intrusion-detection system.