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Berrydal Moshe is listed as Computer Science and Engineering Student at Battery Workforce Challenge, based in Pleasanton, California, United States. AeroLeads shows a matched LinkedIn profile for Berrydal Moshe.
Berrydal Moshe previously worked as Team Leed at Battery Workforce Challenge and Deputy Project Manager at Battery Workforce Challenge. Berrydal Moshe holds Bachelor'S Student, Computer Science And Engineering from University Of California, Merced.
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Computer Science and Engineering student at the University of California, Merced. Previously completed three Associate degrees in Computer Science, Physics, and Mathematics. Is extremely passionate about technological advancements and has participated in upper-division undergraduate research with the goal of expanding the field of electric vehicle batteries. Additionally, completed projects independently related to the amalgamation of software and hardware.
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- Sponsored by the DOE, Stellantis, Argonne National Labs, led a team of engineering students in the design anddevelopment of a central control module for an electric vehicle battery pack- Defined operational and safety protocols for the battery disconnect unit to prevent malfunctions such as overcurrent and thermal runaway- Implemented advanced data.
Deputy project manager of a club aiming to develop and build an electric vehicle batteryInitially worked as thermal management subteam lead
Assisted in the software development of a haptic tactile feedback system meant to track and respond to movements in a VR interfaceAble to convey feeling of different textures utilizing different stimuli
Developed and implemented embedded systems for use in an autonomous robot.Utilized various communication protocols, including CAN, SPI, and UART, to ensure efficient and reliable data exchange between components.
Developed a machine learning model that processes data from electrocardiograms looking for ventricular arrhythmias to help physicians identify heart diseases with more accuracyUtilized Pytorch and Pandas to analyze ECG data with multiple algorithms such as Logistic Regression, Random Forest and XG Boost for binary and multiclass classification. Corrected.
Engineered a fully functioning robotic hand using 3D printing, servo motors, and an Arduino controllerMimicked live human hand functions using the data acquiredUtilized artificial intelligence and machine learning software to analyze live hand motions which are then converted into transmittable data
Tel Aviv, Israel
Applied Vue.js and Tailwind CSS framework to develop a user-friendly front-end interface, including beneficial dashboard featuresImplemented TypeScript for back-end development of the company webpage, retrieved and sent crucial user information to the MongoDB database
Activities and Societies: Competitive computer science club Math club
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Berrydal Moshe works for Battery Workforce Challenge.
Berrydal Moshe is listed as Computer Science and Engineering Student at Battery Workforce Challenge.
Berrydal Moshe is based in Pleasanton, California, United States while working with Battery Workforce Challenge.
Berrydal Moshe has worked for Battery Workforce Challenge, University Of California, Merced, Lawrence Livermore National Laboratory, Robotic Hand (Personal Project), and Datalead Ai.
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Berrydal Moshe holds Bachelor'S Student, Computer Science And Engineering from University Of California, Merced.
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