I'm a Computer Science graduate from Rutgers University- Camden. I spend my day-to-day improving my programming skills by developing projects.
Developed an Android chat application using Kotlin which allows users to engage in conversations with AI in 108 languages,
supporting both speech and text inputs. Integrated Amazon Polly and Google TTS for text-to-speech conversion, supporting 41 languages.
Utilized AWS as the backend, using an AWS lambda function as the interface between the frontend and Amazon Polly and S3 bucket
for storing generated audio files. Implemented speech recognition to support voice input in multiple languages.
Used an LruCache for caching audio, reducing the need for repeated calls to the backend service by 50%. Utilized Google's Gemini api to generate conversations. Integrated Firebase for user
authentication and MongoDB to store users coversation, which enables users to resume conversations.
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Developed a Chrome extension using HTML, CSS, and JavaScript to generate tailored cover letters by analyzing user experience against job description.
Integrated multiple APIs for precise job data extraction, resume parsing, and utilized GPT-3.5 API to create individualized cover letters.
Collaborated with a team of three ensuring seamless task delegation.
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Developed a customizable exerciser app using Kotlin, Android Studio, and SQLite with API integration,
allowing users to access different workouts based on muscle, type, and difficulty level. The app also features
saved exercise functionality with persistent database storage, as well as a dark mode/light mode option. Material
Design principles were used to create an intuitive user interface with optimized performance on
various screen sizes and devices. UI testing was done using Espresso and Retrofit was used to display results from a
REST API and Google Search API to retrieve images for all query results.
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Created an Android app, using Android Studio, Kotlin, XML, and REST API's.
Implemented REST and Google Search API's to provide comprehensive food results and images for over 200,000 queries.
Optimized app performance with recyclerview, viewbinding, navigation, and API connection. Added a toolbar with multiple options for enhanced usability.
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Developed an Intrusion Detection System (IDS) using Python and Machine Learning algorithms to classify network traffic data.
The models were trained on the USNW-NB15 dataset and achieved an accuracy of 98.02% using Random Forest, Decision Tree, XGBoost, Lotistic regression,
and K-Nearest Neighbors algorithms. A feed forward neural network was also implemented.
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Developed a talking alarm system that utilizes RestAPIs, JQuery, HTML, and CSS. The system won first place for the most original idea at the Quinnipiac University Semi-Annual Hackathon.
To create the talking alarm, we started by identifying a common problem that many people face - remembering important tasks throughout the day. We knew that existing alarm systems could be easily overlooked or ignored, so we decided to create something more engaging and interactive.
After experimenting with various technologies and design concepts, we settled on a talking alarm system that uses speech synthesis to notify users of important activities, even if they are not on the website. Users can input the activity they want to be notified for, and the system will deliver the message at the scheduled time in a natural-sounding voice.
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Wrote an automation Python script that uses Twilio API to send random messages and pictures to my partner everyday.
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Worked with a five-man team to develop a multi-level platformer game in Java. There is a goal at the end of the game and each level contains
various themes to keep the player interested. I optimized content and audio using Java Clip library to enhance user experience by
20% and boost user engagement and we used Github for version control and
agile methodology for project management.
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Developed a functioning graphical Tic-tac-toe game. Used Java Swing to create the GUI.
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Worked with a partner to create a simulated version of Quinnipiac's mobile dining ordering system. Implemented an
ArrayList from Scratch using arrays. Used this ArrayList to add various Foods to the program.
Implemented a Queue Data Strucuture using Linked List. Used the Queue to simulate a real-life restaurant Queue.
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I performed extensive analysis on H1B VISA data using SQL and data visualization techniques in Visual Studio. I
applied ETL processes to efficiently integrate and transform data into a database for analysis. Finally, I
produced a thorough and insightful 20-page report to summarize key findings. Platforms used for this analysis include-
Visual Studio and Microsoft SQL Server. More information about the result of my analysis can be found by clicking the
button below.
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Used R programming langauge to analyze LONGSCAN data. I analyzed data to see if there is a correlation
between between young criminal charges and children who grew up in a drug violent neighborhood.
I discovered that these two had no relationship. To perform my analysis I used regression analysis,
p test and also controlled for various factors(in order to isolate my analysis). The link below provides
a more detailed statistical analysis.
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