Related News for Yingzi Lin
MIE Professor Yingzi Lin developed a Continuous Objective Multimodal Pain Assessment Sensing System (COMPASS) to allow patients to more accurately describe the level of pain they are in. A whole new way to measure pain Main picture caption: Yingzi LiYingzi Lin, a professor of mechanical and industrial engineering, measures a subject’s pain sensation by dipping […]
Yingzi Lin, MIE associate professor and director of the Intelligent Human-Machine Systems Lab, to lead $1.2M NSF grant to develop a Continuous Objective Multimodal Pain Assessment Sensing System (COMPASS) that improves pain assessment and management, reduces opioid dependency and advances the field of pain management research and patient safety.
CEE Assistant Professor Qi “Ryan” Wang (PI) and MIE Associate Professor Yingzi Lin (co-PI) were awarded a $200K NSF grant for “Personalized Systems for Wayfinding for First Responders”.
IE PhD student Jing Xu won the "Volpe Best Presentation Award" at the 2017 New England Chapter Human Factors and Ergonomics Society student research conference.
ECE Associate Professors Denis Erdogmus and Yingzi Lin were each awarded $50K NSF I-Corps grants, which allow for the commercialization of technology previously supported by NSF.
MIE Associate Professor Yingzi Lin was featured in the Tech Buzz/Hot Labs section of the Mechanical Engineering magazine for "Nano-Scale Transducers".
MIE Associate Professor Yingzi Lin was awarded a $235K National Science Foundation grant to determine how to integrate human factors such as emotion, mental workload and attention into a Driver Assistance System. Dr. Lin's research interests include human-machine interactions, human friendly mechatronics and human factors in transportation and healthcare. She is also the director of […]
Congratulations to the recipients of this year's College of Engineering Faculty and Staff awards.
Yingzi Lin, Assistant Professor of Mechanical & Industrial Engineering, has received a $400K NSF CAREER for “Bridging Cognitive Science and Sensor Technology: Non-intrusive and Multi-modality Sensing in Human-Machine Interactions”.