EECS Undergrad Eli Cohen Wins 2nd Annual Poster Award for Excellence in Science at The Obesity Society's Annual Scientific Meeting

The research presentation, titled, "Random Forest Detects Eating in Neck-worn Sensor" was well received and further expanded the role of passive sensing in obesity-related research.

Eli Cohen

EECS Undergraduate student Eli Cohen (CS 17') has been named the winner of the 2nd Annual Poster Award for Excellence in Science at The Obesity Society's Annual Scientific Meeting (TOS) in the e/Health/mHealth Section (EMS) category, presented on Wednesday, November 2, 2016 in New Orleans, LA.

The achievement was an effort in collaboration between the EECS Dept. and Preventive Medicine, including co-authors from Health Aware bits (HAbits) Lab: Rawan Alharbi, Kevin Moran, Angela F. Pfammatter, Bonnie Spring, and Prof. Nabil Alshurafa. Their research presentation, titled, "Random Forest Detects Eating in Neck-worn Sensor" was well received and further expanded the role of passive sensing in obesity-related research.

Cohen is a Research Assistant in The Health Aware Bits Lab, where he has contributed to multiple projects, such as Prototyping the “Nutrition Monitoring Necklace” to gather data from multiple sensors for use in laboratory health studies and commercial applications, and leading the submission of a paper to a premier conference on wireless body sensors. His research specializes in circuit design and sensors data acquisition. He was also a Product Development Intern for the Ford Motor Company during the Summer of 2016 and has been named the recipient of the Ford Blue Oval Award and a Slivka Undergraduate Fellow.

The Health Aware bits (HAbits) Lab designs, builds and analyzes end-to-end mHealth systems, while focusing on processing its data to help answer health-related questions. The lab focuses on signal processing and machine learning techniques to process time-series data generated from passive sensors. To advance existing sensing techniques, a part of the lab focuses on the design of embedded systems.