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  • Salman Avestimehr

High School Apprenticeship!


There are two exciting high-school apprenticeship positions, funded by a generous support from Army Research Office, available in our lab this summer!


  • The projects will focus on some problems on machine learning and AI over edge networks.

  • The program is 10 weeks long, starts on June 14th, 2021

  • The link to the program is here, and the projects are listed here. (the code for our project is H448).

  • The selected participants will also receive a stipend of $3000!

  • If you are interested, apply soon!

FLYER

A high level description of the program is also as follows:


Topic: Information Theory and Machine Learning over Tactical Edge Networks


High-level description: The use of compute-intensive machine learning and big-data analytics for processing a collection of raw data streams from distributed sources to enhance awareness of an environment and act on it is on the increase as smart things – devices capable of a combination of sensing, communication, computation, storage, and actuation – are becoming increasingly more prevalent, even on tactical battlefields. Unlike traditional cloud computing environments, however, tactical battlefield networks are characterized by significant challenges with respect to scalability due to (1) severe constraints on bandwidth and other resources including storage and energy; (2) high dynamics due to mobility and disruptions due to jamming and battle conditions.


Professor Avestimehr and his team have pioneered the development of a transformative approach, named Coded Computing, to overcome these barriers in tactical edge computing. The core idea of Coded Computing is to exploit coding theory to optimally inject and leverage computation redundancy in tactical edge computing systems to overcome communication, resiliency, and security bottlenecks. The proposed project will focus on two important problems in Coded Computing that are appropriate for high-school students. These problems are designed with three goals in mind: (1) being at a right level of difficulty for high-school students who have a strong background in mathematics and programming; (2) introducing students to several exciting fields, including information theory, machine learning, and edge computing; (3) attracting and encouraging strong and diverse students to pursue careers in science and engineering, in particular data science, electrical engineering, and computer science.


Mentor: Professor Salman Avestimehr


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