Nitish Natarajan

Student   |   Software Engineer   |   Data Scientist

About

Myself

Hi there! I’m Nitish Natarajan, a Junior majoring in Computer Science and Statistics with a Business minor at the University of Illinois at Urbana-Champaign. I love thinking out of the box and utilizing technology to solve challenging problems. Ever since I started programming, I was instantly drawn to the problem-solving and creative process that’s involved in software engineering. Additionally, I’m equally passionate about working with, and leveraging diverse types of data to extract meaningful information and build predictive models. During my free time, you can find me working on art, biking across campus, playing chess, or watching T.V shows.

Interests

My passion, interests and skills

Software Engineering

I enjoy the creative process and problem-solving involved in software development. I’ve gained experience in the field through college courses, personal projects and internships. I’m looking to explore different opportunities and go beyond my comfort zone and grow as a software developer.

Data Science

I like working with data on a large-scale to extract meaningful information through building predictive models. I’ve also developed a passion for building data pipelines and ML infrastructure as it lets me combines my passion for software engineering with my love for data.

Product/Project Management

I’m passionate about project and product management as I can apply my technical and business skills to deliver product solutions. Working as a product manager at a startup and a project manager at two clubs on campus, has enhanced my management and leadership skills.

Technologies and Tools

Languages:
Tools & Libraries:

Education

Here's an overview of my coursework at UIUC

University of Illinois at Urbana-Champaign (2018-2022)
Major: Computer Science and Statistics
Minor: Business
GPA: 3.83

Computer Science
  • Data Structures
  • Algorithms & Models of Computation
  • Discrete Structures
  • Systems Programming
  • Database Systems
  • Artificial Intelligence
  • Applied Machine Learning
  • Neumerical Methods
  • Computer Architecture
  • Software Design Studio
Statistics
  • Statistical Analysis
  • Statistics & Probability- I
  • Statistics & Probability- II
  • Statistical Computing
  • Advanced Data Analytics
Business
  • Corporate Finance
  • Accountancy
  • Management & Organizational Behavior
  • Principles of Marketing
  • Business Ethics

Work Experience

My past and current work experience
  • Motorola Solutions      |    SWE Intern

    • Worked in Agile to create a mobile-app based ML and data-driven solution that enables millions of customers to identify radio anomalies with over 90% accuracy and notify users, providing first responders with seamless, interruption-free communication
    • Spearheaded the productization of the system architecture through building and deploying APIs on Azure
    • Collaborated with product/project managers and executives to deliver features important to customers
    • Recipient of the Moto-Moment intern award out of 250 interns during the summer in recognition of my work
  • Gulp (Startup)      |   Product Management Intern

    • Collaborated with potential customers to identify important features for the app, and was responsible for marketing and the product lifecycle of in-app features for the online food truck ordering startup
  • Degirum      |    Data Science Intern

    • Led the development, and design of ImageNet based CNNs for edge devices using Pytorch and TensorFlow
    • Delivered ensemble neural nets that were 15% more accurate and 30% more efficient that existing models
    • Analyzed ensemble methods through ML algorithms such as random forest and k-means clustering
    • Wrote python scripts to automate saving and using custom weights and display key features of models
  • UIUC College of Informatics      |   Research Assistant

    • Used Neo4J and SQL for creating databases to provide insights on research conducted by professors
    • Instrumental in extracting and cleaning 1000+ files with medical data containing Zika Virus information
  • UIUC Computer Science     |    Course Assistant

    • Held office hours for the course- ‘Introduction to Computer Science’
    • Taught core computational concepts in Java and helped students with doubts

Projects

Some of my projects that I'm proud of
Mobile App Development

Readability

Readability is a mobile app designed to assist people with reading disabilities such as dyslexia. With the help of text extraction and text to speech capabilities, the user can capture a photo of the text in the app which is then displayed and read out. The pitch and speed of the audio can also be toggled allowing the user to listen to the text at a pace he or she is comfortable with. Readability was featured at a Computer Science fair at college as one of the best projects presented. I am currently working to improve the app by incoporating google translate, allowing for instant translation while reading text in a foreign language.

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Web Development

Find - A - Professor

Find - A - Professor is a website that acts as a valuable resource for students looking to find research opportunities in their desired field of interest. The website utilizes the large google-scholar database to provide students with an easy way to find professors and researchers, view top papers and discover new research areas based on their inputted interest. Additional data visualizations as well as a clean and intuitive UI also make it easy for users to explore information on the website.

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Web Development

U of Fly

UofFly is an end to end travel solution which allows students at the University of Illinois Urbana-Champaign to get the most ideal route to get to their homes across the world. The app combines the schedules of Peoria Charter Bus Service to Chicago with flights out of OHare International Airport, Chicago to find the most convenient combination of both. Through data analysis, the algorithm ranks flights based on cost, duration and fuel efficiency in the order of importance given by the user.

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Machine Learning

Sight to Sound

Sight to Sound is an application that helps convert sign language to English audio. The purpose of the app is to bridge the gap faced by speech-impaired people by allowing others to unnderstand them while speaking in sign language. The application utilizes a webcam to capture sign language and a trained neural net hosted on Google Cloud Platform to process the video captured by the webcam, convert it to text and finally audio.

Contact Me

I love meeting new people so feel free to reach out

The best way to reach me would be through email or Linkedin