Vishnu Kommineni

Software Engineer | Data Engineer

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About Me

I am an Engineer with an interest in Big Data Anatytic, Machine Learning, and Artifical Intelligence. I was a part of the Honors computer science program (CS^2) at University of Texas at Dallas and obtained my BS in Computer Science in 2021. I am currently pursuing my MS in Computer Science with a focus in Data Science and am expecting to graduate in May 2023.
I have experience working on various projects that involved processing and analyzing healthcare and pharmaceutical data. I also have experience developing various web applications and software as a part of my Internships and personal projects. I am an computer science enthusiast always trying to learn about the latest technology.


Education

University of Texas at Dallas

Master in Computer Science, Data Science Track May 2023

University of Texas at Dallas

Bachelor of Science in Computer Science, CS^2 Honors Student December 2021

Experience

Data Science Intern

MyElth May 2021 - August 2022

  • Implemented a ranking algorithm to rank medical providers based on selected criteria.
  • Performed Feature Extraction to create new features for the data set.
  • Analyzed the data to select specific attributes that provided best results for ranking.
  • Utilized SQL and Python to process and extract specific data from a data set of over 500 million data points.

Research Assistant

University of Texas at Dallas July 2019 - December 2020

  • Developed a web application to retrieve data from IOT devices and store in MongoDB.
  • Analyzed structure of data for a small amount of IOT devices to develop an algorithm to extract required data from the devices.
  • Created a visualization of the data in the web application using HTML, Node.js and JavaScript.
  • Web application was used to visualize data that was to be encrypted by Intel SGX.

Skills


Languages: Java, C, C++, C#, Python, JavaScript, SQL, R
Technologies: Apache Spark, Apache Kafka, Node.js, React
Coursework: Data Structures/Algorithms, Machine Learning, Artificial Intelligence, Big Data Management, Databases, Natural Language Processing, Operating Systems, Data and Application Security, Computer Architecture, Human Computer Interaction, Data Representation

Projects

McKesson Patient Preference

McKesson Corporation

  • Evaluated data to find patient preference for various attributes of a drug.
  • Used Natural Language Processing and NLTK to process and clean large data sets.
  • Performed Feature Extraction to create new features to be used in the ML models.
  • Implemented Logistic Regression and Naive Bayes model to predict preference for a drug with an accuracy of 80% and 63% respectively.

Twitter Sentiment Analysis

Big Data Analytics

  • Developed an algorithm that was capable of gathering, processing and analyzing the sentiment of tweets related to a specific topic.
  • Streamed live Twitter data using Apache Spark and Apache Kafka.
  • Processed the data and performed Sentiment analysis using Python with NLTK.
  • Streamlined the algorithm to store the data in Elasticsearch and Visualized the data in Kibana.

Contact

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