Niral
Shah

Machine Learning Engineer @ Apple

Passionate about Applied AI, ML Platforms & Technology

Intro

About Me

I'm Niral Shah, currently a Machine Learning Engineer at Apple! As someone with experience and skills in both Machine Learning & Software Engineering, my projects mostly focus around utlizing this combinations. Most recently, a Applied AI project I worked on at Apple, Handwashing Detection for the Apple Watch was announced. It is currently used by millions of Apple Watch users daily to maintain healthy habits while also helping to prevent the spread of sickness. In addition, I have been contributing to building up Apple's Machine Learning Platform, used daily by thousands of Apple Engineers to produce a variety of AI/ML projects.

Prior to joining Apple, I've built strong experience and skills, through internships at companies such as Apple Inc, Tesla Motors, The Boeing Company, and Verizon Wireless. In addition to working part-time at the Apple Store and as a Teaching Assistant at Rutgers & Duke University.

I completed my Master's in Engineering student at Duke University studying Computer Engineering with a focus in Machine Learning (Dec '18). Furthermore, I also graduated Rutgers Univeristy Magna Cum Laude in Electrical & Computer Engineering and Computer Science ('17').

I believe Machine Learning and Computer Vision in tandem with technologies like Augmented Reality are the future! Besides my passion for computer science, I also enjoy tennis, history, photography and traveling!

Python
Java
Application Development - Python Flask, React JS, Java Springboot, iOS Swift
Deep Learning/Machine Learning (e.g. TensorFlow)
Database Technologies (Postgres, Solr, Spark, Kafka, MongoDB)
C/C++

Experience

This section briefly summarizes my professional work experience.

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Apple Inc.

Machine Learning Engineer
Feb. 2019 - Present (Fulltime)
Summer 2018 (Internship)
Nov. 2013 - May 2015 (Apple Store Genius Bar)
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Tesla

Data Science/Software Intern
Summer 2017
Summer 2016

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Boeing

Software Engineering Intern
Summer 2015


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Verizon

UX & Front-End Dev. Intern
Summer 2014


Education

This section briefly summarizes my education.

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Duke University

Master of Engineering '18 (Dec)
M. Eng in Computer Engineering with focus on Machine Learning

  • Fellowship Recipient
  • Detecting Driveable Areas for Autonomous Vehicles (Arxiv)
  • Worked on creating Apparel Picking Robot for Dr. Kris Hauser (Duke Robotics) & Righthand Robotics
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    Rutgers University

    Bachelor of Science '17
    B.S. in Electrical & Computer Engineering with
    Double Major in Computer Science

  • Presidential Scholarship Recipient
  • Graduated Magna Cum Laude
  • President of Rutgers IEEE
  • Member of the Engineering Honors Academy
  • Rutgers ECE Capstone: Augmented Reality Cooking. Placed 4th place/55 teams
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    Stanford University

    Professional Development Program
    Graduate School Courses

  • Fall 2020: Deep Learning Course (CS 230)
  • Final Project: Generative Techniques for Voice Conversion
  • Projects

    I build the real value.

    Handwashing
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    Automatic Handwashing Detection

    Announced June 2020 (Apple WWDC)

    Developed various Machine Learning models to detect Handwashing. In addition to modeling, worked on streamlining machine learning pipelines to process, analyze, and evaluate vast amounts of data efficiently. Participated in the complete development process: Data Collection, Featurization/Experimentation, Model iteration and release. The feature is used daily by millions of users to track and improve their handwashing habits! The feature was a high priority effort for Apple and was featured in Apple's WWDC 2020 Keynote!

    Handwashing
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    Machine Learning Platforms

    Contributor to the Turi Machine Learning Platform at Apple

    Working on the Turi Machine Learning Platform at Apple to help build large scale Machine Learning Systems, including a federated serach engine and experiments tracking service using Java Spring Boot, Python Flask, Spark, Kafka and various other technologies. The platform is used directly and indirectly by thousands of Apple Engineers.

    Core ML
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    Detecting Driveable Areas for Autonomous Vehicles using the Berkeley Deep Drive Dataset

    Duke Master of Engineering Final Project

    Autonomous driving is a challenging problem where there is currently an intense focus on research and development. Human drivers are forced to make thousands of complex decisions in a short amount of time,quickly processing their surroundings and moving factors. One of these aspects, recognizing regions on the road that are driveable is vital to the success of any autonomous system. This problem can be addressed with deep learning framed as a region proposal problem. Utilizing a Mask R-CNN trained on the Berkeley Deep Drive (BDD100k) dataset, we aim to see if recognizing driveable areas, while also differentiating between the car's direct (current) lane and alternative lanes is feasible.

    driveable_area_results
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    Augmented Reality Cooking with Microsoft HoloLens

    Rutgers ECE Capstone Design, 4th Place Winner (out of 55+)
    Served as the Lead Computer Vision Engineer
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    Rutgers Bus Times

    An iOS & Watch OS App on the Apple App Store. Peak 77 Downloads
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    Voice Conversion with Generative Techniques

    Stanford CS 230 Final Project

    Adapting the techniques of Neural Style Transfer to enable Voice Conversion

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    President of Rutgers IEEE & Autonomous Quadcopter Team Lead

    President 2016-2017, Team Lead from 2015-2017

    As President, I led Rutgers' largest Electrical & Computer Engineering Organization, overseeing a budget over nearly $20k. Under my tenure, IEEE had four primary goals, expanding our presence on campus, promoting practical technical skills - accomplished through workshops, networking sessions, and tech meetups, and participating and winning competitions.

    As Autonomous Quadcopter Team Lead, I organized technical skill workshops and oversaw the development of an autonomous quadcopter that could travel across campus avoiding obstacles.

    Quadcopter Rutgers Team Leads
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    President of Future Business Leaders of America (HS)

    President 2012-2013

    FBLA after the our 3rd Annual Mission: Life Charity Basketball Game, raising $6500 for Fellowship in Serving Humanity (F.I.S.H) and promoting awareness about homelessness and hunger to over 800 attendees. (Top of Page) A banner from our exciting Basketball Game for Ronald McDonald House Charities. In 2012 we successfully raised $5000 and raised awareness about children with disabilities. Our efforts led to an addition at Ronald McDonald House that would allow them to support even more children!

    Swish for FISH

    Contact Info

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