Milton Student wins Award at Broadcom MASTERS

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Milton Student wins Award at Broadcom MASTERS

Asmi Kumar demonstrates her project

Asmi Kumar demonstrates her project

Asmi Kumar demonstrates her project

Asmi Kumar demonstrates her project

Faiza Shaikh, Staff Memeber

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Asmi Kumar recently competed in the Broadcom MASTERS science fair competition. Students participate at school, regional and state science fair level, and then top 10% of the selected science fair participants are eligible to apply for the Broadcom MASTERS national finals, organized by Society for Science & Public annually at Washington, DC. Beginning with 80,000 science fair participants, the SSP first announces its top 300 as semifinalists and then the top 30 finalists nationwide.

 

MASTERS is a once-in-a-lifetime experience, and Kumar’s project, ““Developing a Device to Predict Autistic Meltdowns,” earned her a top 30 spot at the competition. The 30 national finalists competed in  Washington from Oct. 19 to 24, collaborated with and presented their work to researchers, the science media, diplomats and engaged in on-site challenges.

 

In an interview with Georgia Public Broadcasting, Kumar says,”The purpose was to build a prototype of a wearable wrist device that tracks the heart rate of autistic users to predict the heart rates at which the user is likely experience a meltdown.”

Kumar says her project taught her more than just technology,”Presenting my project helped me improve my management, creative thinking, and presentation skills.” She expresses that science fairs have helped her become more confident in her work, and in herself.

 

Kumar won the second-place prize for the Mathematics category, an iPad and a $2,500 stipend to be used for a STEM summer camp. “This summer, I hope to attend the Canada/USA Mathcamp,” says Kumar. It is an intensive five-week summer program for students who are mathematically gifted.

 

“I’ve seen the need for a predictive device for autism-induced meltdowns firsthand,” Kumar explains.” I look forward to refining the device and the underlying predictive modeling and anomaly detection logic over future iterations.”