I'm Peal Hasan, a passionate and dedicated Computer Science student at Stony Brook University, where I am on track to graduate in May 2026 with a GPA of 3.78. My academic journey has been marked by an intense focus on mastering various programming languages and technologies, including TypeScript, Java, Python, C, JavaScript, HTML, and CSS. Through my coursework and projects, I have developed a deep understanding of frameworks like React, Node.js, Next.js, Flask, and Express.js, as well as proficiency with REST APIs.
π§ Technical Proficiency:
I have a diverse skill set that includes developer tools like Git, Postman, and Jest, and I am adept at working with databases such as PostgreSQL, MongoDB, and Redis. My familiarity with libraries like jQuery, Axios, Pandas, NumPy, and Scikit-Learn allows me to build robust and efficient applications.
π± Professional Experience:
During my internship as a UX/UI Intern at Plant3r, I designed and implemented Figma-based front-end screens, significantly increasing user engagement and app performance. My work in engineering streamlined functions for data transfer reduced processing time by 30%, showcasing my ability to enhance operational efficiency through innovative solutions. Additionally, my rigorous testing processes ensured a bug-free user experience, reflecting my commitment to delivering high-quality software.
As a Research Assistant at SpotELF Inc., I spearheaded the conceptualization and planning phases for the Talantra mobile application, connecting users to local art events. Leading a cross-functional team, I demonstrated strong project management skills, achieving a 25% improvement in task completion rates and enhancing overall operational efficiency.
π Projects and Innovations:
My projects exemplify my dedication to leveraging technology for impactful applications. One notable project is the Sign Language Recognition ML Model and Learning Platform. By developing a machine learning model with 98.98% accuracy and integrating it with Mediapipe and OpenCV, I created a real-time ASL recognition system. The interactive frontend, designed using Next.js and Tailwind CSS, offers a 100% real-time feedback system, significantly aiding ASL learners.
Another significant project is the AI-Powered Twitter/X Newsletter and Podcast Service. I designed a responsive front-end using Vite, TypeScript, and React, which increased user engagement by 50%. The back-end services, secured with Express, TypeScript, and Passport, and optimized API calls, reduced response times by 40%. The integration of Twitter API and OpenAIβs Text-to-Speech API for auto-suggestions and content generation boosted content delivery efficiency by 60%.
π Vision and Drive:
I am driven by a passion for creating seamless and efficient user experiences, backed by rigorous testing and secure authentication methods. My strategic vision and relentless drive to push the boundaries of technology enable me to innovate and deliver impactful solutions. Whether working independently or as part of a team, I bring a strong commitment to excellence and a proactive approach to problem-solving.
Internship
Oct, 2022 - Mar, 2023
Remote
Internship
Jun, 2022 - Sep, 2022
NY, USA
Internship
Mar, 2022 - May, 2022
NY, USA
Experience the future of personalized content with Tweetipy, an innovative AI-powered platform that transforms your Twitter/X feed into daily newsletters and engaging podcasts! π Seamlessly sign up using email or X OAuth, and enjoy a sleek, user-friendly interface with features like real-time profile suggestions, comprehensive profile management, and a dynamic admin dashboard. Receive curated content directly to your email, with newsletters and podcasts generated by cutting-edge AI technology. Secure, reliable, and designed with the latest tech stackβTweetipy is the ultimate tool for staying updated with your favorite X accounts! π‘β¨
Signez is an innovative application designed to make learning the American Sign Language (ASL) alphabet engaging and effective. Leveraging real-time hand sign recognition powered by a sophisticated machine learning model, Signez provides an interactive platform for users to learn and practice ASL with immediate feedback and progress tracking. π Real-Time Hand Sign Recognition: Utilize your webcam to get instant feedback on your ASL signs. π Percentage Match & Predicted Words: See how accurately your signs match the ASL alphabet with real-time percentage scores and predicted words. π Progress Dashboard: Track your learning progress with a comprehensive dashboard showing your scores for each alphabet. π» User-Friendly Interface: Intuitive and responsive design built with Next.js and Tailwind CSS for a seamless user experience. π Secure & Robust Backend: Powered by Node.js, Express.js, PostgreSQL, and Redis, ensuring reliable performance and data security. π§ Technology Stack: Trained a Random Forest Classifier on an 87,000-image dataset, achieving 98.98% accuracy in recognizing ASL signs. The frontend is developed using Next.js and Tailwind CSS, while the backend is implemented with Node.js, Express.js, PostgreSQL, Redis, and integrated Google OAuth for secure authentication. The project is hosted on Vercel for the frontend and a reliable cloud provider for the backend, ensuring high availability and scalability.
Course Number |
Course Name |
Skills Learned |
---|---|---|
CSE 114 | Object Oriented Programming | Java, OOP |
CSE 214 | Data Structure and Algorithms | Java, DSA |
CSE 220 | System Fundamentals | C, Assembly, Git |
CSE 216 | Programming Abstractions | Python, Ocaml |
CSE 316 | Software Development | HTML, CSS, Javascript, Node.js, React |