I'm Raghav, an MS CS graduate from ASU. I'm deeply passionate about technology and love learning new skills through meaningful projects. With 2 years of internship and full-time experience in the industry, I'm driven by solving real-world problems through innovative solutions and cutting-edge technology. When I’m not coding, I make music, point my phone at things, read, and cook.
Web Development Intern • June - August 2020
• Launched an online museum with Augmented reality and 3D viewing experiences using Apple’s WebKit and Divi in WordPress.
• Built and integrated a responsive 3D-model viewer using three.js and jQuery that showcased museum sculptures interactively.
• Resolved 2 server-side/client-side issues concerning multiple user logins and user disconnection for a RESTful captive portal.
Project Coordinator Assistant • October 2019 - May 2020
• Optimized resource capacity planning for 60+ members of the Cloud Acceleration teams resulting in a 30% increase in logged and planned time reporting in Jira.
• Wrote 20+ queries in Jira Query Language (JQL) that filtered employees based on different use cases, which significantly increased time reporting visibility for product owners and scrum masters.
• Attended product meetings and monitored teamwork plans to document action items and major decisions in Confluence.
Software Engineer Intern (Computer Vision)• January - May 2019
• Led a team of 2 in developing an Optical Character Recognition (OCR) scanner that extracted text data from 4 identity documents.
• Applied image and text processing techniques such as automatic cropping, image transformation, and RegEx considerably improving the OCR engine’s performance. Tested application on 15+ document samples obtaining an accuracy of 90.48%.
• Deployed the service as a serverless web application on AWS Lambda using Flask and Zappa, allowing users to upload images and view the extracted text as a JSON response.
Web Development Intern • June - July 2017
• Helped design and publish a responsive landing page for a residential project using JS, jQuery and Bootstrap.
• Created and curated content for 10+ CBRE residential projects.
Database Intern • June - July 2016
• Developed a Complaint Manager System using JAVA Swing and MySQL.
Technologies: JAVA, Android Studio • September - December 2020
• Employed a master-slave architecture between mobile devices to perform distributed task (matrix multiplication) computation based on certain criteria (battery level, proximity).
Technologies: JAVA, Android Studio, Python, PHP, JS, nginx • September - December 2020
• Designed a symptom tracking mobile application allowing users to measure heart rate and respiratory rate using mobile sensors.
• Implemented a server-side contact tracing algorithm by processing location information of 11 patients.
Technologies: Python, NLTK, TextBlob, Tableau • May - June 2020
• Analyzed Amazon user reviews over multiple product categories and generated a hierarchical dashboard of visualizations using Tableau.
• Performed sentiment analysis using NLTK and TextBlob to calculate polarity and sentiment of the reviews.
Technologies: Python, Scikit-learn, SciPy, Seaborn, SVC, DBSCAN • January - May 2020
• Predicted meal intake in type-1 diabetic patients using supervised and unsupervised learning methods.
• Extracted meaningful temporal and frequency-based features from the CGM time-series data.
• Achieved an accuracy of 81% using a linear SVC and 44% using DBSCAN algorithm.
Technologies: Apache Spark, Scala, SparkSQL, sbt, Getis-Ord • January - May 2020
• Identified statistically significant clusters for taxi pickups in a Spatio-temporal domain using Apache Spark and Spark SQL.
• Retrieved the 50 most significant hot spot cells using the Getis-Ord (Gi*) statistic.
Technologies: C++, Bash Scripting, Ubuntu • September - December 2019
To view the projects, please request access due to the course's copyright policy.
• Implemented a compiler from scratch by generating a linked list of nodes for I/O, assignment, and looping statements.
• Constructed a parser for a given input grammar and integrated a type checker enforcing syntactic and semantic rules.
• Calculated useless symbols, first and follow sets and list of terminals and non-terminals for any given context-free grammar.
Technologies: Python, Search, RL, Gradient Descent • September - December 2019
• Implemented artificial intelligence concepts such as search, adversarial behaviour, reinforcement learning and neural nets on a Pacman interface.
Technologies: Python, NumPy, Pandas, Matplotlib, kNN, SVM, Naive Bayes • January - May 2018
• Predicted IMDb ratings of upcoming movies using supervised machine learning algorithms such as Decision Trees, Bayesian Regression etc.
Technologies: Python, BeautifulSoup, Google Text-to-Speech • October - November 2017
• Designed a python script for automating web searches using voice command and obtained results on Google Search and Maps.
