Math, Machines, and Metacognition
The Stanford Intelligent Systems Lab (SISL) conducts research on decisions under uncertainty and optimization problems with applications to autonomous vehicles.
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The Stanford Intelligent Systems Lab (SISL) conducts research on decisions under uncertainty and optimization problems with applications to autonomous vehicles.
In this student project, students are given a research experience designed to closely mimic those in academia or industry. Their research task is to use smartphone sensors to develop the core algorithm for an accurate, reliable pedometer app which counts a user’s steps.
The goal of this ETP is to introduce students to computer programming in MATLAB that is heavily used in scientific and engineering research, especially in a university research facility like Stanford.
The goal of this ETP is to engage students in an engineering experience much like the engineers at Synopsys go through.
Computer science students will learn about the following: 1)The importance of software and web software quality testing and 2)The importance and usage of two types of tools for analyzing and testing websites which include type A tools such as FireFly with Firepath on the Firefox browser, or the G
Students will work in small teams to research a common type of sensor and how to use an Arduino microcontroller to read its values, creating a video and written tutorial summarizing the key concepts and practical steps required to use their sensor.
This lesson supports students’ understanding of functions, algebraic manipulation with variables and constants, and collaboration through computer programming.
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