Embedded Systems/Firmware Engineer

Shrividhyaa Sankar Raman

Chicago, Illinois

646-***-**** www.linkedin.com/in/shrividhyaas ***********.******@*****.*** PROFILE

Hard-working quick learner with a passion to learn & grow. A disciplined engineer with profound knowledge in the areas of Computer Engineering which includes Embedded Systems, Firmware Engineering, Computer Architecture and Internet of Things (IoT). Have been associated with various academic projects as well as professional experience in fields of Embedded Systems, Signal Processing and Image Processing.

EDUCATION

University of Illinois at Chicago (UIC) May 2019

Master of Science in Electrical and Computer Engineering CGPA: 3.6/4.0 Sri Venkateswara College of Engineering May 2017

Bachelor of Engineering in Electronics and Communication Engineering CGPA: 7.84/10 TECHNICAL SKILLS

• Packages: MATLAB, Pspice, Xilinx ISE, Quartus

Prime Lite II, USIMM

• Platforms: Beaglebone Black,Arduino, Raspberry Pi

• Programming Languages: C, C++, Embedded C,

ALP, Python and SystemVerilog

• Tools and Database: MS-Office and SQL

• Controllers: ATmega, PIC, ARM, 8051

• Protocols: I2C, SPI, CAN, TCP, UDP

• Technology: Bluetooth, Wi-Fi, IoT, 802.11

• Certifications: Python for Everybody, Machine

Learning

• Version Control: Git, Redmine

PROFESSIONAL EXPERIENCE

Fermi National Accelerator Laboratory, Illinois, USA Embedded Software and Firmware Engineer July 2019 – Present

• Developed a C++ code to interact with ARM processors. This also enables data transfer between GUI and the FPGA

• Involved in projects with socket programming, multithreaded programming and basic LabVIEW UIC–Department of Physical Therapy, USA Graduate Research/Teaching Assistant May 2018 –April 2019

• Biological signal processing using MATLAB (which includes curve fitting, time-frequency signal analyses)

• Maintaining lab equipment and preparing paperwork and related documents for research studies ChipTest Engineering Ltd, Chennai, India Student Intern January 2017 – April 2017

• Accomplished, an efficient method for the detection of defective nails and their automatic disposal, using Image Processing with MATLAB and Arduino (ATmega328P)

Lema Labs, Chennai, India Robotics Engineer December 2014 – March 2015

• Built a robot that avoids obstacles, and slows down when in a tunnel using UART Programming and PWM

• Built a Gesture Controlled Pick & Place Robot which uses Wireless Communication and MEMS Accelerometer (ATmega16) ACADEMIC PROJECTS

Autonomous Vehicle Robot

January 2019 – May 2019

• Built an Autonomous Vehicle Robot which follows a lane and follows traffic signs and signals using

Raspberry Pi (ARM Cortex-A53) and ROS

An Implementation of Modified Lightweight Advanced Encryption Standard in Synopsys VCS

August 2018 – December 2018

• Reduced the latency of the AES algorithm, by 3%, running the sub-steps in parallel and implemented

project on Synopsys VCS 2014.10

Implementation of Dense Parallel Algorithm in UIC Extreme August 2018 – December 2018

• Developed a parallel execution mechanism, to find the determinant of an n x n matrix after performing LU decomposition using the processors present on the UIC Extreme High-Performance Cluster and MPI-2

programming (best result achieved for 16 processes, and matrix of size 8, computation time < 2 )

Sonar Echolocation Navigation Device (S.E.N.D.)

March 2017 – June 2017

• Constructed a navigation device to help provide the visually challenged with a virtual view of their surroundings using HC-SR04 Ultrasonic sensor module and Embedded C

programming on ATmega328P

• Provided an audio feedback based on data acquired from the surroundings

Implementation of SPEC2000 Benchmark on SimpleScalar August 2017 – December 2017

• Devised a pseudo-LRU cache replacement policy to improve the performance of the processors and compared its performance with that of the true LRU policy using Cygwin

(a virtual LINUX machine) Reduced Miss Rate by 8%. Automated Weighing Scale

September 2016 – December 2016

• Engineered a smart weighing scale to automate

weighing process for industrial usage and sent data to an android app over Wi-Fi as well as to a cloud server to track the readings and provide analysis

Contact this candidate