Electrical Engineer Software

Ashish Y. Rawat

*** **** **, ********* * Mountain View, California 469-***-**** adbywv@r.postjobfree.com www.linkedin.com/in/ashish-y-rawat/ Objective

Graduate Electrical Engineer (Signal Processing), Machine learning enthusiast, seeking Full-Time Position (OPT starting February 2020). Experienced in Machine Learning Algorithm implementation on Android Devices for Noise Classification and Reduction. Experienced in Audio DSP Algorithm development on MATLAB/Simulink. Experience

Samsung Research America CA August 2019 – December 2019 DSP Research Co-op / Think Tank Team

Designing DSP Algorithm App deployment system. App Deployment method using MATLAB, Simulink and Android Studio

• Implemented a system to: Develop, Test and Deploy DSP Algorithms on an Android Smartphone

• Developed DSP Modules (Hearing Aid Modules) on MATLAB and Simulink environments

• Deployed these modules on Android Smartphones using Android Studio

• Worked on prototypes of ideas on futuristic Samsung Products Bose Corporation MA January 2019 – July 2019

DSP Software Engineer Co-op / Automotive Systems Division

• Implemented tuning algorithms for speakers in cars on Simulink

• Automated inhouse Bose Testing framework for Audio DSP development

• MIPS and Memory Profiled and Optimized Simulink models for Audio Processing Algorithm Education

The University of Texas at Dallas Dallas, TX August 2017 – December 2019 Master of Science in Electrical Engineering, GPA 3.2 Skills

Programming: C, C++, Java, Python

Hardware: ARM mbed microcontroller and IDE, FRDM KL25Z NXP Semiconductors Software: Android Studio, MATLAB, Simulink, NI LabVIEW Projects

Real-Time Implementation of Noise Signal Classification Using ART2 Clustering as a Smartphone App Spring 2018 Develop and evaluate a smartphone app for noise signal classification using Adaptive Resonance Theory Machine Learning algorithm.

• ART2 classification implemented on Sub-band features and Mel-Features of the sound frames

• Tested application successfully with a clustering accuracy of 95% for clustering using Sub-band feature and 98% for Mel-feature Spectral Shaping using Wiener Filter and NLMS Algorithm Spring 2018 Extract desired frequencies from a speech segment with Gaussian White Noise present in it and reduced MMSE.

• Performed qualitative analysis for three cases: Only Wiener filter, Only NLMS and Wiener Filter followed by NLMS Emotion Detection for Speech data of NASA - Apollo 11 Guide - Dr. John HL Hansen Spring 2018 Emotion Detection using Gaussian Mixture Models in MATLAB and Praat.

• Created a four-dimension plot of emotions classified as - Happy, Sad, Loud and Soft. IIR, FIR and Adaptive Filter Design on Android Studio Spring 2018 Real Time MMSE reduction using Adaptive filter designed as a Smartphone app.

• An adaptive FIR Filter is used to model the behavior of an IIR Filter Fixed Point and Floating-Point Arithmetic Calculator using Newton-Raphson Algorithm Spring 2018 Analysis of arithmetic operations using fixed point and floating-point numbers using Newton Raphson Algorithm.

• Implemented Newton Raphson Algorithm in Android Studio and optimized using NEON Coprocessor. Relevant Coursework

Digital Signal Processing (Basic and Advanced), Applied Digital Signal Processing, Algorithm Analysis and Data Structures, Speech and Speaker Recognition, Linear Systems, Wireless Communication, Random Variables and Statistics, Object Oriented Programming, Structural Programming Approach

Certifications

ARM University Training Program July 2016

Embedded Systems and Internet of Things - Grade: A July 2016 Idea 2 Entrepreneur by Institute of Engineering and Technology - Second Runners up March 2016

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