diff --git a/README.md b/README.md index 7404c56..d8a68d7 100644 --- a/README.md +++ b/README.md @@ -62,29 +62,55 @@

Where I've Worked

- Technical Consultant Intern @ CRMNEXT + Software Engineer Intern @ Auto BIM Route

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+ Technical Consultant Intern @ Acidaes Solutions Pvt LTD +
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+ +
+
Software Engineer Intern @ C-BIA Solutions
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National Police Incident Dashboard | React.js, Python, Apache Jena Fuseki, Sparql + href="https://github.com/sohmpatil/NPID-UI">National Police Incident Dashboard
  • - Implemented a full stack web application with a 99.9% uptime on Amazon EC2, ensuring continuous accessibility for users. - Integrated Flask API for seamless data flow, expanding application capabilities + Created a user-friendly National Police Incident Database (NPID) full stack application using semantic web engineering.
  • - Led data preprocessing with pandas, analyzing a 1900+ police incidents dataset. Generated 42,000+ triples, showcasing advanced - RDF data management. Developed an ontology-based system for optimized data organization and query efficiency + Deployed on Amazon EC2 with a 99.9% uptime, ensuring continuous accessibility. Integrated Flask API for seamless data flow, + expanding application capabilities.
  • - Accomplished a responsive user interface, reducing page load times by 99% through ReactJS optimization + Preprocessed data with pandas, analyzing a 1900+ police incidents dataset, generating 42,000+ triples. Built an ontology-based + system for optimized data organization and query efficiency.

PACMAN 3D | Unity, C# + href="https://play.unity.com/mg/other/manpac-build-webgl">PACMAN 3D
  • - Synthesized gaming experience with immersive audio and visual elements, and smooth camera transitions, resulting in a significant - 25% increase in user satisfaction and a 15% boost in player engagement + Synthesized gaming experience with immersive audio and visual elements, and smooth camera transitions, resulting in a + significant 25% increase in user satisfaction and a 15% boost in player engagement.
  • - Pioneered responsive player controls and refined enemy AI, contributing to a 35% improvement in overall user experience + Pioneered responsive player controls and refined enemy AI, contributing to a 35% improvement in overall user experience.
  • - Solved intricate technical challenges through methodical debugging, accomplishing a substantial 40% decrease in critical bugs + Overcame intricate technical challenges through methodical debugging, accomplishing a 40% decrease in critical bugs.

- Face Recognition and detection system | python + Face Recognition and detection system
  • - Built an advanced face detection and recognition system using OpenCV library and SVM (Support Vector Machine) algorithm + Built an advanced face detection and recognition system using OpenCV library and SVM (Support Vector Machine) algorithm. +
  • +
  • + Utilized advanced feature extraction algorithms to identify crucial facial components (eyes, ears, nose, and mouth).
  • - Extracted key facial features(eyes, nose, and mouth) utilizing a feature extraction algorithm and delivered a precision of 91% by - training an SVM classifier on extracted facial features to perform face recognition + Attained 91% precision by training an SVM classifier on extracted features for precise face recognition

Paracom | Kotlin, Node-Red, Raspberry Pi, Arduino + href="https://thesai.org/Publications/ViewPaper?Volume=11&Issue=6&Code=IJACSA&SerialNo=84">Paracom
    diff --git a/home.html b/home.html index 95fc1a6..20fe775 100644 --- a/home.html +++ b/home.html @@ -62,29 +62,55 @@

    Hello There, it's me

    Where I've Worked

    • - Formulated and documented Product 360 overview and optimized pipeline for client, achieving a 25% increase in efficiency + Mitigated legacy Windows Forms application to a modern WPF application using C#, XAML and .NET.
    • - Designed, developed, and integrated websites and external data sources with CRMNEXT Platform. Led management of MySQL - database and optimization of procedures, improving efficiency by 40% + Adopted MVVM architecture, integrating OpenTK and OpenGL with JSON files for rendering 2D design layouts.
    • - Constructed interactive reports and analytical dashboards, reducing manual data manipulation time by 99% + Established a fully automated CI/CD pipeline, reducing deployment time by 30%.
    • - Crafted ASP.NET API, conducted rigorous testing utilizing Postman and Soap UI, achieving a 15% defect reduction and a 20% - improved system response times. Boosted performance by 30% through implementation of Auto-reloading functionality + Incorporate ABR AI API into the new software systems, aiming for a 3.5% reduction in processing time for relevant tasks

    + +
    +
      +
    • + Formulated and documented Product 360 overview and optimized pipeline for client, achieving a 12% increase in efficiency. +
    • +
    • + Developed, and integrated websites, external data sources, and AI-driven chatbots, enhancing customer service response time + by 30%. +
    • +
    • + Collaborated on a team of 10 to migrate CRMnext to a microservices architecture, enhancing scalability by 13%. +
    • +
    • + Created a real-time analytics dashboard using React and D3.js, improving data visualization for 1,000+ users. +
    • +
    • + Crafted RESTful APIs, conducted rigorous testing using Postman and Soap UI, and enhanced CRMnext mobile responsiveness with + Bootstrap for 5,000+ mobile users. +
    • +
    • + Led the management of the MySQL database and optimization of procedures. +
    • +
    +
    +
    @@ -108,61 +134,63 @@

    Things I've built

    National Police Incident Dashboard | React.js, Python, Apache Jena Fuseki, Sparql + href="https://github.com/sohmpatil/NPID-UI">National Police Incident Dashboard
    • - Implemented a full stack web application with a 99.9% uptime on Amazon EC2, ensuring continuous accessibility for users. - Integrated Flask API for seamless data flow, expanding application capabilities + Created a user-friendly National Police Incident Database (NPID) full stack application using semantic web engineering.
    • - Led data preprocessing with pandas, analyzing a 1900+ police incidents dataset. Generated 42,000+ triples, showcasing advanced - RDF data management. Developed an ontology-based system for optimized data organization and query efficiency + Deployed on Amazon EC2 with a 99.9% uptime, ensuring continuous accessibility. Integrated Flask API for seamless data flow, + expanding application capabilities.
    • - Accomplished a responsive user interface, reducing page load times by 99% through ReactJS optimization + Preprocessed data with pandas, analyzing a 1900+ police incidents dataset, generating 42,000+ triples. Built an ontology-based + system for optimized data organization and query efficiency.

    PACMAN 3D | Unity, C# + href="https://play.unity.com/mg/other/manpac-build-webgl">PACMAN 3D
    • - Synthesized gaming experience with immersive audio and visual elements, and smooth camera transitions, resulting in a significant - 25% increase in user satisfaction and a 15% boost in player engagement + Synthesized gaming experience with immersive audio and visual elements, and smooth camera transitions, resulting in a + significant 25% increase in user satisfaction and a 15% boost in player engagement.
    • - Pioneered responsive player controls and refined enemy AI, contributing to a 35% improvement in overall user experience + Pioneered responsive player controls and refined enemy AI, contributing to a 35% improvement in overall user experience.
    • - Solved intricate technical challenges through methodical debugging, accomplishing a substantial 40% decrease in critical bugs + Overcame intricate technical challenges through methodical debugging, accomplishing a 40% decrease in critical bugs.

    - Face Recognition and detection system | python + Face Recognition and detection system
    • - Built an advanced face detection and recognition system using OpenCV library and SVM (Support Vector Machine) algorithm + Built an advanced face detection and recognition system using OpenCV library and SVM (Support Vector Machine) algorithm. +
    • +
    • + Utilized advanced feature extraction algorithms to identify crucial facial components (eyes, ears, nose, and mouth).
    • - Extracted key facial features(eyes, nose, and mouth) utilizing a feature extraction algorithm and delivered a precision of 91% by - training an SVM classifier on extracted facial features to perform face recognition + Attained 91% precision by training an SVM classifier on extracted features for precise face recognition

    Paracom | Kotlin, Node-Red, Raspberry Pi, Arduino + href="https://thesai.org/Publications/ViewPaper?Volume=11&Issue=6&Code=IJACSA&SerialNo=84">Paracom