Ashish Wale

Ashish Wale

Machine Learning Intern

Followers of Ashish Wale387 followers
location of Ashish WaleTempe, Arizona, United States

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  • Timeline

  • About me

    Software Engineer | CS @ ASU | ex - eQ Technologic | Java | Full Stack | Microservices

  • Education

    • COEP Technological University

      2016 - 2020
      Bachelor of Technology - BTech Information Technology
    • Arizona State University

      2023 - 2025
      Master of Science - MS Computer Science 3.78/4.0

      Spring 2024:CSE 565 - Software Verification/Validation/TestingCSE 578 - Data VisualizationCSE 598 - Data-Intensive Systems for Machine LearningFall 2023: CSE 509 - Digital Video ProcessingCSE 551 - Foundation of AlgorithmsCSE 576 - Topics in Natural Language Processing

  • Experience

    • Anubhooti Solutions

      May 2018 - Jun 2018
      Machine Learning Intern

      [ Tech Stack: Python, TensorFlow, Scikit-Learn, Apache MXNext, Android Studio, Gradle, GIT ]• Developed an ML model to extract human emotions from text by creating a sophisticated LSTM architecture in TensorFlow with 94.07% accuracy, to dictate output voice tone of text-to-speech mobile app.• Integrated the model into the app using Apache MXNext to assist 50000+ senior users in listening to news articles

    • EQ Technologic

      Dec 2020 - Jun 2023
      Software Engineer

      [ Tech Stack: Java, Javascript, SQL, Spring Boot, Azure, Maven, JUnit, GIT, JIRA ]• Revamped EQ’s data model by designing new APIs, database schema, and search utilities using Java and Spring Boot, resulting in a 37% time optimized microservice architecture.• Spearheaded development of thread-safe Common Data Model (CDM) feature using software design patterns, facilitating migration of business data from over 60 connected systems, increasing revenue by 12%.• Optimized deployment process of data model with Azure DevOps CI/CD pipelines, cutting deployment time by 70%, and boosting scalability and reliability.• Created a utility search tool using Apache Lucene to generate indexes for data model entities during CRUD operations. Fetching results from these indexes reduced API latency from 90 ms to 50 ms.• Achieved 88% code coverage by writing test cases in JUnit 5 for the model and connector microservices. Performed code reviews and managed multiple projects using tools such as JIRA and Git. Show less

  • Licenses & Certifications