Sathvik Nair

Hello! I'm a third year undergraduate at UC Berkeley double-majoring in Computer Science and Cognitive Science with an emphasis on data science. My academic interests include teaching, psycholinguistics, and applications of computing to sociopolitical issues. In my free time, I enjoy playing the violin and tabla (a South Asian percussion instrument), reading and writing about history and current events, and cooking new recipes. Feel free to reach out to me at any of the links below!


What am I working on?

This semester, I'm on the teaching staff for two data science courses, tutoring Foundations of Data Science, and assisting lab sections in Probability for Data Science, and also helping direct and advise an educational outreach program I founded last summer to promote data science education in India. I'll be taking Computer Architecture (CS 61C), Natural Language Processing (INFO 159/259), Introduction to Linguistic Science (LING 100), and Contemporary Theories of Political Economy (POLECON 101). I'm also looking for internships in data science and related fields for summer 2019!

Work Experience

This summer, I interned as a Data Scientist at AppliedX, part of Applied Materials's edtech division. I created descriptive visualizations for various business units in the company using Tableau, preprocessing data from Microsoft SQL Server using Pandas, and analyzed major causes of roles changing using logistic regression and Bayesian inference. I also developed a recommendation algorithm to connect employees with one another based on content-based filtering and document similarity using NLTK, Scikit-Learn, Pandas, Scipy, and Numpy, applied over a based of 13,000 employees. I productionized the algorithm by designing and developing a web app, and iterated on feedback from users from both within and outside the group.

I interned at CivikOwl last summer 2017 working on software development. I learned technologies like ReactJS, D3.js, and jQuery, which greatly improved my skillset as a frontend developer, followed up on my interest in civic tech, and picked up concepts of the Agile methodology, human-centered design, and product management. I added major features (both web and mobile) to a web app and also created a data visualization of users' news reading habits, such as time spent and political leaning of articles read. These data were gathered through the CivikOwl Chrome extension, featured on ProductHunt.

Research

During my sophomore year, I was a research assistant at UC Berkeley's Computational Cognitive Science Lab designing and developing an audiovisual web-based experiment that models a game of "Telephone," through which we examined how understanding of language changes as the same phrase is transmitted across multiple subjects. Because we needed to record and play audio from users, I used the Web Audio API in JavaScript for this functionality, and JQuery with Bootstrap UI components to take participants through the experiment. I mostly worked on the frontend, but added several backend functions in Flask, writing data to a Firebase database. I also worked on pipelines to analyze the data using probabilistic context-free grammar models, which involved writing a Python module to interface with an incremental top down parser from Roark, 2001. I also developed a logistic regression model to predict whether a sentence would change in the game, based on their probabilities under various models, using Numpy, Pandas, and Scikit-Learn. I'm currently working on publishing a paper on this research.

I was an astrophysics research intern at UC Santa Cruz in the summer of 2015. I learned how to program using Python and scientific computing libraries such as Numpy, Scipy, and Matplotlib, and developed a novel algorithm that analyzes data from the spectra of distant galaxies to draw conclusions about their temperature. Our abstract was published on the Harvard-NASA database and we were named national semifinalists in the Siemens Competition for Math, Science, and Technology.

Teaching

During both spring and summer terms of 2018, I was a tutor for the fastest-growing course at UC Berkeley, Foundations of Data Science, helping teach statistical inference techniques using Python. I held office hours, taught a small section, developed content with Jupyter notebooks and LaTEX, and graded assignments. I also got the opportunity to speak at UC Berkeley's undergraduate data science pedagogy workshop this summer as a student panelist, where I described my experience on Data 8 course staff to around 50 professors from universities across the United States.

I founded Data Science for India with fellow Berkeley students last May. I've largely been focusing on directing and participating in curriculum development, as well as interfacing with instructors on the ground. I devised and implemented a workflow for content development involving Jupyter and Git for coding content and Google Drive for worksheets. Our work over the summer teaching fundamental concepts of data science to 500 students in over 12 Indian high schools was recognized by the Institute of South Asia Studies at UC Berkeley. This summer, we piloted a curriculum tailored to students on "Data Literacy," and are working on bootcamp workshops targeted to teaching Python with an emphasis on data science for high school students.

In the spring of my freshman year, I joined Paradigm Shift, a venture that's working to promote computer science education in underserved high schools across the US, as a developer. I worked on content for workshops introducing computer science and a Python project that teaches basic concepts of artifical intelligence.

Coursework

  • Efficient Algorithms and Intractable Problems (CS 170, Spring 2018)
  • Probability for Data Science (STAT 140, Spring 2018)
  • Stigma and Prejudice (PSYCH 167, Spring 2018)
  • Foundational Concepts of Neuroscience (MCB C61, Spring 2018)
  • Discrete Matematics and Probability Theory (EECS 70, Fall 2017)
  • Linear Algebra and Differential Equations (MATH 54, Fall 2017)
  • Algorithms and Data Structures (CS 61B, Spring 2017)
  • Data Science and the Mind (COGSCI 88, Spring 2017)
  • Foundations of Data Science (CS/STAT/INFO C8, Spring 2017)
  • Designing Information Devices and Systems (EECS 16A, Fall 2016)
  • The Structure and Interpretation of Computer Programs (CS 61A, Fall 2016)

Projects

Carbon Tweetprints

Gender and Color Perception

Project Virulence

Reach

FoodAnalyzer

BearMaps