Samriddh Singh

Samriddh Singh Github , LinkedIN, Leetcode -1700 Email:-Mobile: - Skills Languages: C++| Python | SQL | JavaScript Web Development: React JS | HTML| CSS | Styled Components | Material UI | NodeJS | MongoDB ML Frameworks: Sklearn | PyTorch | Numpy | Pandas | Matplotlib | OpenCV Education • • • National Institute of Technology, Hamirpur - 2023 Class XII – 90.3% (ISC) Class X – 93.3% (ICSE) CGPA: 8.85 Experience TCS Innovator -SDE • • • SQL ExpressJS, React and Node JS (September ’23) Requirement Management System – Developed a dynamic dashboard with role-based access, file parsing (.xlsx/csv), SQL database integration, and Excel export for efficient project tracking. React Web App Development – Designed and optimized a responsive React application for US clients, integrating APIs from a .NET backend and SQL DB2. Successfully migrated from legacy system to ReactJS and .Net 8. Full-Stack Development – Proficient in building scalable, high-performance web applications with React, API integration, advanced UI/UX, and data visualization. Internship at IIT GANDHINAGAR (Indian Academy of Sciences) (May 2022 – July 2022) • • Collaborated on optimizing CNN computations using Python with two mapping algorithms for in-memory computation , significantly improving performance. Utilized Intel’s Cacti software to analyse energy consumption and latency, achieving an 8x enhancement in computational efficiency through innovative mapping algorithms in collaboration with IIIT Bangalore. Major Projects E-Commerce Website (Deployed) • A popular E-Commerce Website clone. The project uses MongoDB as database, Node and Express JS as backend server, React JS for front End and Redux for managing state in the whole web app. Neural Style Transfer – CNN Deep Learning – PyTorch, Python, Image Processing and CNN • • Implemented Neural Style Transfer using PyTorch and VGG-19 CNN to extract and merge content and style features from two images uutilizing Gram matrices for precise style transfer, tuning learning rates and running multiple epochs for convergence and visually compelling results. Applied transfer learning and deep learning techniques in Python, leveraging hyperparameters tuning to estimate ratio of style vs content in output. Twitter Sentiment Analysis – Machine Learning and Data Analysis (Deployed here) • • Did analysis on text data of tweets. Compared performance of XG-Boost on Random Forest vs Multinomial Naïve Bayes classifier. Achieved 88% of precision, recall and f1-score average on each class of the highly imbalanced dataset for prediction. Web Hosted on Heroku platform using StreamLit. Humanoid (Computer Vision Recognition system and Simple Chatbot) • Trained a facial recognition model and did image processing in Python with Open CV and implemented a chatbot using Google’s text to speech library. Courses Technical: Design and Analysis of Algorithms (NPTEL), Machine Learning (Udemy), Deep Learning Specialization (DeepLearning.ai), SQL (UC Davis), Computer Networks (NPTEL) Non-Technical: Social Psychology with Hons (Coursera) , Guitar Scales and Chord Progressions.(Coursera). Extra Curriculars: 1. Strength Training and nutrition. Guitar (Flamenco and Finger style) 2. Blog Writing (WordPress) on Psychology and several Book Analysis and summary. 3. Current Coordinator and Content Writer at English Literature Club NIT Hamirpur. 4. Volunteered in Robotics Society -)