I am a software developer with 3 years of professional experience at Tata Consultancy Services. Currently, I am pursuing my master's degree in computer science from the State University of New York At Binghamton and my expected graduation date is Dec 2020.
During, my work at TCS I have worked on technologies like C#, Design Pattern, OOP, JavaScript, Angular, HTML, CSS.
Currently, I am involved in developing NodeJS based full-stack applications where I try building a distributed and highly scalable microservice systems. I have also built some full-stack personal projects using technologies like NodeJS, Python, React, MongoDB, Deep Learning, Tensorflow, Docker, Kubernetes.
For the demo and codebase of my projects, please do check out the portfolio section on my website.
Personal Portfolio: www.siddheshkolhapure.com
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Experience
I have 3 years of professional experience at TCS, where I
• Built a Portfolio Management Tool for a leading US bank that helped the bank’s end users to get a better user experience for their wealth management portfolio. This Single Page Application demonstrates a graphical representation of the user’s wealth management portfolio which helped the user update his holdings depending upon the analysis provided in the tool
• As a software developer, provided and implemented solutions for web applications using .NET, C#, JavaScript, jQuery, CSS, HTML, optimized algorithms and put Task Parallel Libraries in practice increasing application’s performance by 15%
• Utilized object-oriented design principles to increase the maintainability and scalability of the application
• Analyzed application errors and statistics on tools like Splunk to detect and troubleshoot complex application problems. Partnered with the engineering team to perform Failure Mode Effect Analysis to test negative scenarios
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Projects
Personal Project.
1: Sentiment Analysis of Real-Time tweets on H1B Visa and F1 Visa ( 2 contributors ) | (as of 7/13/2020) | ( Status: In Progress )
This project tries to analyze the sentiment of a tweet on a specific topic. As there is a lot of tension going on regarding the H1BVisa and F1Visa we decided to create a dashboard to display real-time tweets with the sentiment. The dashboard will also include a Pie chart that will display the sentiment(Negative, Positive, Neutral) percentage of the tweets processed till now by the application.
1. Used Deep learning LSTM model to create a trained model. This model is trained using 1.6 million tweets dataset available on Kaggle. Containerized and exposed model as API to the outside world.
2. Used Apache Kafka for live tweet streaming and processing
3. Pending - Integration with a React-based UI
Technologies used:
Deep learning Model: Flask, Python, Docker, Tensorflow, Google Colab, NLP, GPU
Other microservices built using NodeJS
Message Bus: Apache Kafka
UI: React, HTML, CSS, Webpack
Demo: Comming soon
Project 2: Online Exam system using Face recognition based Authentication. ( 2 contributors) | ( Status: Completed )
As due to COVID colleges were going online we decide to create this project.
The online exam system will register a live user and then authenticate the user to access protected information like an exam. This system will ask the answer to multiple-choice questions and provide instant results.
This system is a distributed microservices-based system that supports horizontal autoscaling on Kubernetes.
Technologies Used:
1. Face Recognition docker container by MachineBox.io
2. NodeJS, Express, MongoDB, HTML, CSS - Microservices built on NodeJS (Face recognition service, Questionnaire Service, UI Service, MongoDB Service).
3. Docker, Kubernetes, GCP - All the services are containerized in a separate docker container and deployed on Google Cloud Platform Kubernetes Engine.
Demo:
https://github.com/sid94/Container-based-Authenticated-Online-Exam#demo
Some more interesting projects are listed on my website.
www.siddheshkolhapure.com
