Finthrift
→
Summary
Created a responsive AI-powered personal finance web application, enabling users to track spending, set budgets, and receive real-time AI-generated financial insights.
Highly motivated and results-driven Computer Science student with a strong foundation in full-stack development and AI/ML, poised to innovate in dynamic tech environments. Proven ability to design, develop, and deploy impactful applications, including an AI-powered mock interview assistant and a driver drowsiness detection system, leveraging React, Next.js, Python, and TensorFlow. Eager to apply robust problem-solving skills and a passion for creating high-performance, user-centric solutions in a challenging software engineering role.
→
Bachelor of Science
Computer Science
Grade: CGPA:8.18
Awarded By
VII BioEngineering Conf, NIT Rourkela
Presented 'Agro Shield - Crop Disease Detection' at the VII BioEngineering Conference 2024 and was recognized for innovation.
Awarded By
Aarambh College
Achieved runner-up position in the Aarambh College Volleyball Tournament.
Issued By
Walmart USA on Forage
Issued By
IBM Career Education Program
Issued By
IBM Career Education Program
Issued By
Microsoft & Simplilearn
C++, JavaScript, Python, HTML5, CSS3, TypeScript.
Next.js, React.js, Node.js, Tailwind CSS, Vercel, FastAPI, Framer Motion, Shaden UI.
OpenAI APIs, Gemini AI, TensorFlow, OpenCV, LSTM-AE Model.
MongoDB, PostgreSQL, Prisma ORM, Firebase Firestore, Supabase.
Firebase Authentication, Supabase, Vapi.
Git, CI/CD Pipelines, PowerBI, Arcjet.
Badminton (State-level).
→
Summary
Created a responsive AI-powered personal finance web application, enabling users to track spending, set budgets, and receive real-time AI-generated financial insights.
→
Summary
Architected and engineered a responsive, SEO-optimized personal portfolio website to showcase projects, certifications, and achievements with an engaging user interface.
→
Summary
Developed and deployed a comprehensive voice-based AI mock interview assistant, dynamically generating role-specific and difficulty-tiered questions to enhance interview preparation.
→
Summary
Implemented an advanced LSTM-AE model for real-time detection of driver drowsiness, significantly enhancing operational efficiency and safety.