Vaibhav Anand

• CodeChef Starters 50 (08/2022): Secured Global Rank 73 out of 10,000+ participants in a highly competitive coding contest.
• CodeChef Starters 51 (08/2022): Achieved Global Rank 365 out of 10,000+ participants in an international coding competition.
• GATE 2023 Qualified: Ranked among the top candidates out of 75,000 nationwide, demonstrating strong technical proficiency.
• DSA Mastery: Solved over 300 Data Structures and Algorithms problems on global platforms like LeetCode and GeeksforGeeks.

Image Denoising Using Deep Learning
Deep Learning | Python, TensorFlow/PyTorch

• Developed an image denoising model using Convolutional Neural Networks (CNNs), achieving a 20% reduction in noise levels across multiple datasets (e.g., BSD500, Urban100).
• Applied residual learning techniques, leading to a 15% increase in PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index).
• Demonstrated improved image fidelity through quantitative and qualitative analysis, enhancing visual clarity in denoised outputs.

Ecommerce Application
Full-Stack Development | MERN Stack

• Designed and implemented a full-featured ecommerce platform with product browsing, shopping cart, order placement, and user profile management.
• Integrated secure user authentication, resulting in a 30% increase in user engagement.
• Developed admin functionalities for product and order management, boosting system efficiency by 25%.
• Leveraged MERN stack to ensure scalability, supporting 10,000+ concurrent users.

Image-to-Image Translation Using Conditional GAN
Deep Learning | Python, TensorFlow/PyTorch

• Developed image-to-image translation models using Conditional Generative Adversarial Networks (cGANs), focusing on tasks like grayscale-to-color, edge maps to photos, and day-to-night translation.
• Optimized cGAN architecture, improving output quality and reducing model loss by 18%.
• Demonstrated high-quality, domain-consistent outputs, resulting in a 20% improvement in SSIM over baseline models.