Aparajith Raghuvir

Aparajith Raghuvir

Ivy

A perpetual optimist. Interested in leveraging technology to solve problems for humankind. An NLP & AI enthusiast. Interdisciplinarian that enjoys applying computer science to different domains such as biomedicine where he builds language models to understand and extract knowledge from biomedical texts.

He works on machine learning engineering in the daytime and is building a deployment auto-tuning process to make AI deployment easier and faster at Ivy with open source technologies!

Download his résumé.

Interests

  • Machine Learning
  • Compilers
  • Cybersecurity
  • Natural Language Processing
  • Artificial Intelligence

Education

  • Master of Science in Computer Science, May 2025

    University of Massachusetts, Amherst

  • BTech in Computer Science and Engineering, 2022

    Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram

  • High School Graduate in Computer Science, 2018

    PSBB Senior Secondary School

Certifications

Chartered Financial Analyst Level 1 Pass

Study for the CFA Level 1 and clear the exam
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Sequence Models

A foundational program on sequence models using GRUs, LSTMs and the transformer architecture
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Deep Learning Specialization

A foundational program to understand the capabilities, challenges, and consequences of deep learning
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Convolutional Neural Networks

Introduction to convolutional neural networks
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Structuring Machine Learning Projects

Build a successful machine learning model and practice decision making as a machine learning project leader
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Neural Networks and Deep Learning

Introduction to the foundational concepts of neural networks and deep learning
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Introduction to Machine Learning

Introduction to the basic concepts of machine learning from a mathematically well motivated perspective.
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CS50’s Introduction to Artificial Intelligence with Python

Explore and implement the concepts and algorithms at the foundation of modern artificial intelligence.
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Developing Data Products

Creating data products using Shiny, R packages, and interactive graphics.
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Practical Machine Learning

Predictive analysis and machine learning with an emphasis on practical applications.
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Reproducible Research

Concepts and tools behind reporting modern data analyses in a reproducible manner
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Exploratory Data Analysis

Exploratory techniques for summarizing data.
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The Data Scientist’s Tool Box

Introduction to the main tools and ideas of a data scientist.
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