RAJAT KUMAR
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ï https://www.linkedin.com/in/rajat-kumar-3a790b319/
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§ https://github.com/Rkwg
Education
IIIT Delhi
BTech, Electronics and Communication Engineering
Aug 2021 – May 2025
CGPA: 7.82
Cambridge Foundation School
Standard 12th, CBSE, Science
April 2019 – March 2020
Percentage: 94.8%
Cambridge Foundation School
Standard 10th, CBSE
April 2017 – March 2018
Percentage: 91.2%
Experience
Summer Intern, NITI Aayog
June 2024 – July 2024
Tech Stack: SpringBoot, Java, HTML, MySQL, CSS, Javascript, Postman
• Contributed to the development of an interactive dashboard (Full Stack Development) for NITI Aayog, utilising HTML
for the frontend, Spring Boot for backend services, and SQL for database management, resulting in a streamlined user
experience and improved data accessibility.
Skills
• Technical Skills: Data Structures, Algorithm Design and Analysis, Machine Learning, Object-Oriented Programming,
Database Management System, Statistics, calculus
• Languages: C++, Python, Java, SpringBoot, SQL, HTML, CSS, Javascript
• Tools & Technologies: Linux, MySQL, GitHub, Maven, Gradle,Flask, IntelliJ IDEA, VS Code, Miro, Figma, Kaggle,
ChatGpt, Jupyter Notebook, Postman, Tableau, Power BI
Awards and Achievements
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6 Times Coding Ninjas College Topper.
Solved 400+ problems on LeetCode.
Solved 800+ problems on CodingNinjas and level 8 coder with 90k+ exp. points.
Secured AIR 21011 in JEE Main and AIR 19289 in JEE Advanced.
Projects
Deep Learning Model to Predict RSS
April 2024 – May 2024
Tech Stack: Python, Matplotlib, NumPy, Pandas, TensorFlow, Keras
• Trained and optimized a deep learning model/Artificial Intelligence(AI) model using Python and the Keras API to predict
Received Signal Strength (RSS) values from a given dataset.
• Compared its performance with a traditional linear regression model, demonstrating improved prediction accuracy.
Applied appropriate optimization techniques to enhance model performance.
TCP Transmitter and Receiver
Sep 2023 – Oct 2023
Tech Stack: C/C++, Socket Programming, TCP/IP, Networking, Linux
• Designed and implemented a ByteStream class to manage efficient byte storage, enforcing flow control, capacity
constraints, and EOF handling, reducing memory overhead by 25% and improving data transmission efficiency.
• Implemented a Reassembler to reorder out-of-order segments and buffer unassembled bytes, ensuring 99.9% accurate
byte stream reconstruction in compliance with TCP standards, even under high packet loss conditions.
• Integrated the ByteStream and Reassembler into a TCP Receiver, handling sequence numbers, acknowledgments,
and window size, achieving 30% faster stream reassembly and improving data integrity.
Machine Learning Prediction Models and Data Analysis
Aug 2024 – Nov 2024
Tech Stack: Python, Pandas, numPy, matplotlib
• Implemented machine learning models to diagnose vector-borne diseases based on patient symptoms.
• Performed Data preprocessing using SMOTE Oversampling, Label Encoding, PCA, Standardization, Exploratory Data
Analysis(EDA), K-mean clustering, etc.
• Used algorithms such as Random Forest, Logistic Regression, Decision Trees, Support Vector Machines, and Multi-Layer
Perceptron Classifiers to analyze and predict disease occurrence.
Game Galaxy – Game Store Database System
Jun 2024 – July 2024
Tech Stack: MySQL, SQL, Flask, Python, HTML
• Designed a Game Store database system, implementing conceptual modeling, relational schema design, SQL
queries, and transaction management.
• Built a backend system to support user authentication, game catalog management, order processing, and payment
tracking.
• Applied normalization techniques and indexing to optimize database performance and ensure data consistency.
