ForensicHub
→
Summary
Developed a full-stack digital forensics training platform using a Go backend and React/TypeScript frontend, delivering a scalable and responsive user experience.
Highly motivated B.Tech Computer Science Engineering student with a strong foundation in full-stack development, machine learning, and cloud architecture. Proven ability to design and implement scalable solutions, demonstrated through impactful projects like a digital forensics platform and an AI-powered text editor. Recognized for competitive programming success and active contributions to open-source, seeking to leverage technical expertise and problem-solving skills in a challenging software development role.
→
B. Tech
Computer Science Engineering
Grade: 8.8/10 CGPA
→
Class 12th
CBSE
Grade: 8.51/10 CGPA
→
Class 10th
CBSE
Grade: 9.43/10 CGPA
Awarded By
TCS
Achieved a Global Rank of 3279 out of 500,000 in a competitive programming contest, demonstrating exceptional proficiency in complex algorithms, data structures, and optimized solutions under strict time constraints.
Awarded By
Nokia
Achieved top rankings in Stage 1 (Top 2000/10,000) and Stage 2 (Top 700/3500), solving advanced technical challenges in telecommunications and developing innovative solutions for industry use cases.
Fluent
Native
Basic
Issued By
IBM CEP
Issued By
AWS Academy
Issued By
Linux foundation and CISCO Networking Academy
Python, Go, MySQL, TypeScript, JavaScript.
Django, Flask, React, React Bootstrap, Pandas, NumPy, Matplotlib, TensorFlow, PyTorch, Scikit-learn, Tkinter.
Git, GitHub, Git Actions, VS Code, Jupyter, Linux, AWS, Docker, Docker Swarm, CI/CD Pipelines, REST API.
Agile, DevOps.
→
Summary
Developed a full-stack digital forensics training platform using a Go backend and React/TypeScript frontend, delivering a scalable and responsive user experience.
→
Summary
Built an AI-powered text editor using Python and TensorFlow LSTM for word prediction, significantly boosting typing efficiency.
→
Summary
Created a backend email spam checker for Gmail using Python, IMAP, and ML models, achieving high accuracy in spam classification.
→
Summary
Contributed production-grade code to open-source repositories, enhancing version control and collaboration skills within global developer ecosystems.