About Me

  • Name:Anagha Ajnadkar.
  • Email:anaghaajnadkar@gmail.com
  • Address:Dallas, TX, USA

Hi, I'm Anagha!

I am a first year graduate student pursuing Masters in Computer Science from University of Texas at Dallas.

I have previously worked in the domain of Full Stack Web Development and Software Development as an intern. I'm interested in finding solutions to problems using Machine learning as well as Deep learning. I also love to extract hidden patterns from data and turn them into useful insights.

What else? I'm addicted to music, specially the indie one. I love reading in my free time be it is a thriller novel, Mythological fiction, Sci-fi or just an article on politics.

  • Experience

  • Business Technology Solutions Associate Intern

    ZS Associates (Jan 2022 - July 2022)

    Designed Knowledge Graphs to develop customized Search engine by using SPARQL for retrieving semantic network data. End to end API development along with specialized algorithms for ranking of search results.

  • Software Development Intern

    FinIQ Consulting (June 2021- July 2021)

    Designed Single Sign On (SSO) System with ASP.NET webframework for centralized access to systems. Developed Full Stack Web UI using Angular JS for consistent and engaging interaction.

  • Data Science Research (Project Trainee)

    DGRE, DRDO (April 2021 - June 2021)

    Worked on route optimization problem using real-world Geospatial data. Computed Shortest Path using modified Bi-directional A* Algorithm for improved time and space complexity.

  • Web Developer Intern

    Study4U Software Services (Nov 2020 - Jan 2021)

    Designed and developed a quiz platform using Node, Express and MongoDB where quiz can be generated and attempted in levels. Created JS frontend along with Admin Dashboard for overall quiz activity monitoring.

  • Google Explore ML Facilitator

    Google AI (July 2019 - Dec 2019)

    A Google-sponsored program offering Machine Learning Content (Beginner, Intermediate and Advanced tracks). Student facilitators get familiar with ML content, meet one another and connect to Googlers.


  • Education

  • Master of Science in Computer Science (MSCS)

    University of Texas at Dallas
    Aug 2022 - Present
    Current Grades: 3.778/4.0

  • B.Tech in Computer Science and Engineering

    Indian Institute of Information Technology, Pune
    Aug 2018 - June 2022
    Final Grades: 9.38/10.0

  • Higher Secondary School (HSC)

    Pace Junior Science College, Thane
    Aug 2015 - May 2017
    Final Grades: 85.38%

  • Secondary School (SSC)

    Swami Vivekanand Vidyamandir School, Dombivli
    June 2014 - May 2015
    Final Grades: 96.80%

My Skills

Languages

Python, Java, SPARQL, Bash, C, C++, JavaScript, HTML, CSS
Web Frameworks

Node.js, Express.js, Angular JS, Django, Flask
ML Frameworks

TensorFlow Python, Keras Library, OpenCV, NLTK
Databases

SQL, PostgreSQL, MongoDB, GraphDB, Amazon Neptune
Data Analysis

PowerBI, Google Data Studio, Excel, Matplotlib
Others

Knowlege Graphs, Linux, JIRA, Github,

Projects

Automatic Proctoring System Using Deep Learning


Developed a software for monitoring students while taking exams by detecting actions like head movement, mouth opening etc. and automatically create detailed reports. It also uses face recognition and identification methods for authenticating the systems.

Smart Job Application Portal


Selected as one of top 4 teams for Smart India Hackathon Finale 2020. Built a complete recruitment management platform along with Interview Scheduling (Google Meet) integration. Auto summarised Job Descriptions from uploaded PDFs and generated job recommendations for applicants.

Amazon Product Review Sentiment Analysis


Analyzes sentiment of reviews by extracting recent reviews & ratings for the queried product from Amazon website. Implemented different Machine learning models for predicting the overall rating of the product.

Micro-blogging and Messaging Application


Designed a microblogging-cum-messaging platform on small scale with following - unfollowing option. Users can post publicly (restricted to followers only) and read others' posts. Integrated one-to-one private chatting feature for users.

Live Twitter Sentiment Analysis


Extracted live tweets using Twitter API for real-time analysis of sentiment. Used Natural Langugage Processing (NLP) techniques and ensembled classification algorithms for analysis.

Real Time Face Recognition System


Built a lightweight Face Recognition platform with triplet loss based Facenet architecture. Performed user identification task on live camera feed using Single Shot Detection (SSD) approach.

Brain Tumor Detection


Achieved high sensitivity for localizing as well as identifying malignant brain tumors in early stages. Extracted features using Histogram-gradient and performed the segmentation based on Watershed algorithm.