Folsom, California, United States Contact Info
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About

Embedded Software/Firmware Architect working at Solidigm (formerly Intel memory division,…

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Experience & Education

  • Solidigm

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Courses

  • Advanced Computer Architecture

    CSCI 5593

  • An Introduction To Artificial Intelligence by Prof. Peter Norvig & Prof. Sebastian Thrun (an online Stanford University course)

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  • Design and Analysis of Algorithms

    CSCI 5454

  • Embedded System & Design

    ECEN 5613

  • Independent Study I

    ECEN 5840

  • Independent Study II

    ECEN 5840

  • Introduction to Engineering Management

    EMEN 5010

  • Network Systems

    CSCI 5723

  • Real Time Digital Media

    ECEN 5653

  • Real Time Embedded Systems

    ECEN 5623

  • UNIX System Administration

    TLEN 5833

Projects

  • GPU Kernel modification for implementation of Vector Reduction & Image Filtering

    Implemented atomic support operations on the Tesla C2075 GPU (448 Cores) and documented & analysed the profiled results based on six benchmarks

  • Two-level Adaptive Training Hybrid Branch Predictor

    Implemented a two-level adaptive training branch predictor. The accuracy levels observed were 93.67% (bzip2) and 91.30% (456hmmer)

  • Accelerometer Controlled USB Wireless Mouse (using Bluetooth)

    This project was submitted in partial fulfillment for the award of the degree of 'Bachelor of Engineering' in Electronics Engineering as a part of the mandatory final year project. A computer mouse that has its motion controlled by the two 2-axis accelerometers mounted on a glove. The accelerometer values are fed to the ATmega8 micro-controller, which in turn segregates the data by forming report descriptors as per the USB-HID Profile. This data is transmitted wirelessly using a Bluetooth HC05…

    This project was submitted in partial fulfillment for the award of the degree of 'Bachelor of Engineering' in Electronics Engineering as a part of the mandatory final year project. A computer mouse that has its motion controlled by the two 2-axis accelerometers mounted on a glove. The accelerometer values are fed to the ATmega8 micro-controller, which in turn segregates the data by forming report descriptors as per the USB-HID Profile. This data is transmitted wirelessly using a Bluetooth HC05 transmitter to the Bluetooth receiver (inbuilt or otherwise) plugged into the USB port of the computer. Coding done in Embedded-C language using AVR-gcc compiler. Compatible with Windows and OS X. Can be operated using a PS/2 cable by using a USB-PS/2 Converter.

  • Wall-E (Advanced Multitasking Wall Follower)

    An advanced multitasking wall following robot employing the Proportional-Integral-Derivative Control alongside the Pulse-width modulation technique. It included the simultaneously monitoring of a total of 8 sensors,viz. HC-SR04 Ultrasonic Sensors, TSOP-IR Sensor, conventional IR sensors, etc.

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  • Line-Intellect (An Advanced Multitasking Line Following Robot)

    Submitted the 'Line-Intellect' assigned as a part of the internship. Secured an 'A' grade by the Embedded Systems Head based on its performance, test & efficiency.

  • Affine Transformation and Sobel Filter using OpenCV for MPEG2 video

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    1. Simulated a post-production environment for digital media remake and enhancement and achieved color filtered and transformed motion picture.
    2. Used Affine transformation and Sobel filter on uncompressed MPEG2 video frames for transformation.
    3. Used FFMpeg for extracting image frames out of video and to implement video out of transformed frames.
    4. Wrote code for OpenCV filters and modified affine filter algorithm for custom 360 degree rotation effect.
    5. Provided execution…

    1. Simulated a post-production environment for digital media remake and enhancement and achieved color filtered and transformed motion picture.
    2. Used Affine transformation and Sobel filter on uncompressed MPEG2 video frames for transformation.
    3. Used FFMpeg for extracting image frames out of video and to implement video out of transformed frames.
    4. Wrote code for OpenCV filters and modified affine filter algorithm for custom 360 degree rotation effect.
    5. Provided execution speed-up using POSIX pthreads and attempted OpenCV GPU module for the same.

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  • Autonomous Air-Hockey table

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    This Real-time Embedded Systems project was an autonomous play-along air-hockey table based on the ARM BeagleBone Black running Ångström Embedded Linux distribution.
    Each of the two Logitech C920 cameras monitored one half of the table (limited visibility), detecting the red puck and, using the stepper motor belt, moving the solenoid ‘kicker and pulley mechanism’ to hit the puck on to the other side of the table with precise timing and accuracy.
    Source Code:…

    This Real-time Embedded Systems project was an autonomous play-along air-hockey table based on the ARM BeagleBone Black running Ångström Embedded Linux distribution.
    Each of the two Logitech C920 cameras monitored one half of the table (limited visibility), detecting the red puck and, using the stepper motor belt, moving the solenoid ‘kicker and pulley mechanism’ to hit the puck on to the other side of the table with precise timing and accuracy.
    Source Code: http://code.google.com/p/rtes-group-7/
    Major algorithms implemented:
    1. The centroid detection algorithm for puck detection
    2. The trajectory planning algorithm for estimating the exact co-ordinates of the puck in advance, so that the kicker can start moving in that direction.
    ARM AM335x GPIO Memory Mapping Implementation: http://github.com/VinitVyas
    Coding Platform: Eclipse IDE used for C code development (using the POSIX API library) using Subversion in combination with Google Code and Doxygen documentation
    Challenges included: Camera device drivers, RT patch for BeagleBone Black embedded Linux distributions (Xenomai), FIFO scheduling with thread priorities, fast GPIO responses, limited area image processing, grid mapping, trajectory and path detection for moving object, etc.

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    See project
  • CUDA Implementation of Block Matching Algorithm for Motion Estimation

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    In this project we used Beagle Bone Black(BBB) to acquire the frames at 1FPS, which are used to determine the motion vectors for two adjacent frames using full search based block matching algorithm implemented in CUDA and tested on 'Tesla C2075' Graphical Processing Unit (GPU).

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Languages

  • English

    Native or bilingual proficiency

  • Hindi

    Native or bilingual proficiency

  • Marathi

    Native or bilingual proficiency

  • Marwari

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