Abhijeetjha@2026
About me
Final-year Information Technology student at SRMCEM (Graduating 2026). Aspiring Software Development Engineer with hands-on experience building AI-integrated full-stack applications using Next.js and the MERN stack. Solved 600+ DSA challenges on LeetCode and HackerRank using CoreJava. Focused on developing scalable web architectures, real-time data synchronization, and efficient database
Photos
Education
Btech
Bachelor
November 3, 2022
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Present
I am currently pursuing a Bachelor of Technology in Information Technology at Shri Ramswaroop Memorial College of Engineering and Management (SRMCEM) in Lucknow, UP. My academic journey, which spans from 2022 to 2026, has allowed me to maintain a CGPA of 7.4/10.0 while building a robust technical foundation. Throughout my studies, I have gained deep proficiency in Core CS concepts, including Data Structures & Algorithms, Object-Oriented Programming (OOPS), Database Management Systems (DBMS), and Operating Systems. This academic background serves as the cornerstone of my practical expertise in full-stack development and algorithmic problem-solving
Projects
Welth-Ai finance Management Platform
Developed RESTful APIs using Next.js, Supabase, and Tailwind CSS for authentication and transaction management, resulting in a 25% reduction in API response time. ◦ Implemented AI-based models using Google Gemini for budgeting and forecasting, improving finan cial planning and increasing user savings by 15% within three months. ◦ Integrated third-party services including Arcjet and Inngest for security and background automation, leading to a 30% increase in user engagement and 20% improvement in user retention. ◦ Optimized UI/UX: Leveraged Next.js Server Components, Shadcn UI, and Tailwind CSS to improve app usability by 40%; integrated Clerk for secure authentication. ◦ Tech Stack: Next.js, Supabase, Tailwind CSS, Shadcn UI, Clerk, Google Gemini AI, Arcjet, Inngest.
SensAi-Ai Career Coach
Developed an AI-driven career platform using Next.js and Neon, integrating Google Gemini and Inngest to increase user engagement by 35% within the first two months. ◦ Engineered 3+ RESTful APIs for skill analysis and salary forecasting, utilizing Inngest for data pro cessing and Clerk for secure auth, resulting in a 25% improvement in user retention. ◦ Database Optimization: Enhanced Neon (PostgreSQL) performance via SQL indexing, reducing data retrieval latency by 20% and boosting query efficiency by 15%. ◦ Tools Used: Next.js, Neon, Tailwind CSS, Shadcn UI, Clerk, Google Gemini, Arcjet, Inngest.