Hello, my name is Mansi Thanki. I recently graduated with a Master's degree in Computer Science from Northeastern University. During my academic journey, I interned as a Software Engineer at Dassault Systèmes, where I gained valuable industry experience and leveraged technologies like JavaScript, Backbone.js, Java, HTML and CSS. I worked as a Software Engineer for one year at Infogen Labs, India where I worked upon building a training hub for individuals who treat ASD using C#, ASP.NET MVC and JavaScript. I also worked at Shine Infosoft as a Software Engineer where I leveraged technologies like JavaScript, ReactJS, Redux, Tableau, SQL and Python. I am an enthusiastic and ambitious individual who loves to code and come up with innovative ideas! I have good problem solving skills and proficient in JavaScript, Python, Java, C#, C++, SQL and R. Apart from coding, I love to read books, learn new languages and interact with people to create more opportunities. Currently seeking a challenging assignment which will provide avenues for professional learning, hone my technical skills and enrich my experience as well as knowledge in the process.
Explore GithubI have worked with a wide variety of programming languages. For web applications I use Java and Javascript and finally when I am building prototypes or working on my hobby projects I fall back on Python. Here are a few of the technologies I have worked on:
JavaScript, Python, Core Java,
SQL, R, C#
ReactJS, HTML, CSS, Bootstrap, AngularJS, Node.js, Selenium, Cypress, Jasmine, Postman
S3, RDS, EC2, Lambda, CloudFormation, Elastic Beanstalk, AutoScaling, CloudWatch
OS: Mac,Windows XP/7/8/10, LINUX
Databases: MySQL, Mongo DB, Oracle Database
Developed a robust food delivery application using MERN stack, Redux, and Git for collaboration; integrated frontend (React.js, Material UI) with backend (Node.js, Express.js, MongoDB) for authentication, orders, and restaurants, enriched with Google APIs for location-based search and a distinctive multi-restaurant purchase feature.
Tools used: ReactJS, Express.js, Node.js, MongoDB, Redux, MaterialUI
ImageVoyager is a React application for exploring and discovering a wide range of images. It provides a user-friendly interface for searching and viewing images.
Tools used: Javascript, React.js, Tailwind CSS, Unsplash API
A React Native job search app exemplifying sleek UI/UX, real-time API integration (JSearch from RapidAPI), advanced search and pagination, custom API hooks, and adherence to best coding practices.
Tools used: ReactJS, Express.js, Node.js, MongoDB, Redux, MaterialUI
Analyzed US Accidents dataset, conducted EDA, & developed a severity prediction model.
Performed Random forest & logistic regression along with hyperparameter tuning & undersampling techniques.
Achieved 85% accuracy & 79% recall with logistic regression, and 93% accuracy and 83% recall with random forest.
Tools used: R and Python
Developed Amazon Clone App using ReactJS, HTML, CSS, React Context API, Node.js & VSCode. Designed Front-end using MaterialUI & used Google Firebase for Authentication, Database & Hosting.
Tools used: JavaScript, ReactJS, MaterialUI
Implemented a dungeon game using JAVA and object-oriented design principles. Developed GUI using Swing and performed JUnit tests. Applied SOLID principles & used MVC Design Pattern.
Tools used: Java, Swing
Developed a tool for Cyber Forensic Experts to detect tampering of OS logs using cryptographic hashes,
Anomaly detection using timestamp-based method and Event correlation using semantic rule-based method.
Tools used: C# .NET
Developed a Python notification application to provide the realtime COVID-19 data to the user by performing
web scrapping on MoHFW India.
Tools Used: Visual Studio Code, Beautiful Soup, Plyer, Tkinter
A fully functional progressive web app (PWA) deployed in cloud to help manage and analyze customer data.
Tools Used: IntelliJ IDEA, Spring Boot, Vaadin, Spring Data, Spring Security
Used Convolutional Neural networks and python libraries to classify road signs present in the images into
different categories which is useful for autonomous vehicles. Accuracy achieved by this model is 95%.
Libraries used:TensorFlow, Keras, PIL, Matplotlib, Sklearn, Pandas, Numpy.
Tools: Jupyter, Tkinter
Built ML model for classifying persons based on their characteristics and finding group of people with similar
characteristic from dataset using logistic regression, decision trees, K-means clustering in Python.
Used data mining concepts like missing value handling, Normalization, discretization while exploring data.
Libraries used: Pandas, NumPy & Sci-kit learn.
Tool Used: RStudio, Selenium
An IOT based project to provide an eco-friendly and cost-effective alternative to auto-flushing technology in
India which was implemented for only Rs 930.
Tools Used : Arduino IDE, Arduino Nano
Sensors Used: Proximity Sensors, Magnetic Door Switch, Soil Moisture Sensor, Buzzer, LED