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Related News for Yingzi Lin

$1.2M NSF Grant to Develop Objective Pain Assessment Sensing System

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.

Improving Emergency Response Wayfinding

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”.

PhD student wins Volpe Best Presentation Award

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.

2 ECE Professors Awarded NSF I-Corps Grants

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.

Yingzi Lin Featured in Mechanical Engineering magazine

MIE Associate Professor Yingzi Lin was featured in the Tech Buzz/Hot Labs section of the Mechanical Engineering magazine for "Nano-Scale Transducers".

Lin Awarded $235K NSF Grant

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 COE Award Winners

Congratulations to the recipients of this year's College of Engineering Faculty and Staff awards.

Lin Awarded NSF CAREER Grant

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”.