Hello There. I'm an AI enthusiast pursuing a Master's in Artificial Intelligence at Northeastern University, Boston. With a B.Tech in Computer Science and Engineering (specializing in Data Science and ML) from Manipal University Jaipur, I’ve worked with multiple organizations on diverse projects, honing my skills in AI/ML, MERN stack, and software engineering methodologies. Beyond academics, I actively participate in hackathons, social clubs and events, always seeking opportunities to innovate, collaborate, and grow. Passionate about coding and automation, I strive to bridge the gap between theory and real-world impact.
Check out my internships and projects below..!!!
Download CVMaster of Science in Artificial Intelligence (Khoury College of Computer Sciences)
Sept 2024 - Dec 2026
Courses: Reinforcement Learning and Sequential Decision Making, Foundations of Artificial Intelligence, Algorithms, NLP
Bachelor of Technology in Computer Science and Engineering
Oct 2020 – May 2024
CGPA: 8.92/10
Courses: Natural Language Processing, Deep Learning, Design and Analysis of Algorithms, Database Management Systems, Computer Vision
-----------------------------------------
Earth ArXiv
Associated with the Indian Space Research Organisation (ISRO) - SAC
Nov, 2024
This study employs deep learning to estimate Land Surface Temperature and Emissivity from Landsat imagery (2018–2023). Using the Single Channel Method and an NDVI-based approach, Pix2Pix models achieve high accuracy, even on unseen data.
Read More-----------------------------------------
International Research Journal of Modernization in Engineering Technology and Science (IRJMETS)
Aug, 2023
This proposal enhances smart traffic lights using LSTM and GRU for traffic flow prediction, outperforming traditional models. Drone-captured images provide critical traffic features, showcasing deep learning's potential in urban mobility.
Read More-----------------------------------------
Pre-print (ResearchGate)
Associated with the National Institute of Technology, Trichy
May, 2023
OTPLM combines NLP, image analysis, and a multi-agent system for plant identification using hybrid semantics. A medicinal herb ontology enhances data, ensuring accurate infographic suggestions.
Read More-----------------------------------------
Pre-print (ResearchGate)
Associated with the National Institute of Technology, Trichy
June, 2023
This paper proposes a specialized document recommendation framework for horticulture, using WikiData ontology, dynamic knowledge tags, and robust learning methods for semantic reasoning.
Read More-----------------------------------------
International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET)
Aug, 2024
Our WasteSegNet, a custom CNN, achieves 87.5% accuracy in automated waste segregation into Organic and Recyclable categories, optimizing waste sorting and promoting sustainable smart city waste management.
Read More-----------------------------------------
International Journal of Progressive Research in Engineering Management and Science (IJPREMS)
Sept, 2023
This paper explores subword tokenization in enhancing NLP models like ELMo and BERT, improving handling of OOV words and capturing fine-grained patterns for better contextual understanding.
Read MoreConducted research in Signal and Image Processing, developing Land Surface Temperature (LST) and Emissivity models using satellite imagery from diverse global regions under varying weather conditions. Leveraged GANs, particularly Pix2Pix, for automated atmospheric predictions, achieving high performance on unseen data.
Developed a Mental Fitness Tracker using machine learning techniques to analyze mental health indicators across various countries and users. Applied data preprocessing on 6,840 records and compared ML models, achieving high prediction accuracy to provide personalized mental health insights.
Annotated 2,000+ drone images from 100 key Surat junctions for a Government project, classifying vehicles into 7 categories. Analyzed traffic patterns to provide insights for transportation infrastructure planning. Delivered high-quality annotated data, split 70-20-10, to the machine learning team for model training and further analysis.
Gained hands-on experience in data analysis, modeling, and visualization while contributing to real-world projects under the excellent mentorship of the Celebal Team, enhancing proficiency in data-driven decision-making with skills in data visualization, Python, discrete mathematics, data science, and machine learning.
Developed Salesforce applications using Apex and LWC, gaining expertise in automation, security, and workflow enhancements. Set up VS Code and CLI for efficient development, collaborated on real-world projects, implemented APIs, debugged code, and optimized processes in an agile environment.
Identified growth opportunities and conducted research to support decision-making, contributing to business growth. Developed skills in corporate communications, Google Analytics, collaboration solutions, strategizing growth, product management, and team building.
I harnessed data-driven insights to support critical decision-making processes, bridging the gap between data and business strategies. Contributing to 3 impactful projects and fostering a data-driven culture.
Built at Northeastern University’s Innovaite 2025 Hackathon, SmartCart uses AI to generate ingredient lists, compare vendor prices, and optimize delivery. Developed with Python, Django, PostgreSQL, and React, it enhances grocery shopping efficiency while supporting local businesses through automation and smart meal planning.
GitHubTripTailor creates customized itineraries based on your preferences, budget, and duration. It integrates weather forecasts, transit options, and optimized recommendations for hotels, restaurants, and attractions, simplifying travel planning. Built at the Social Winter of Code Season 5 Hackathon! 🏆
GitHubThis project automates soccer highlight reel creation using AI, identifying key moments like goals and fouls with CNNs and GRUs. Using the SoccerNet dataset, it detects events, trims videos, and generates highlights, allowing fans and analysts to focus on crucial moments without watching the entire match.
GitHubThis project applies advanced reinforcement learning (TD3, Options Critic) to autonomous car parking in a realistic simulation with vehicle dynamics and collision avoidance. Our RL agent learns efficiently, outperforming basic RL methods. This work advances autonomous navigation, demonstrating RL’s potential in real-world applications and autonomous vehicle research.
GitHubThis project develops an ensemble deep learning approach for leukemia subtype classification, combining CNN, SqueezeNet, and Inception V3. Individual models achieved up to 84.1% accuracy, while the ensemble improved it to 86.1%, enhancing diagnostic precision. This demonstrates ensemble learning’s potential in medical imaging and clinical decision support.
GitHubDeveloped a Stack Overflow clone with OCR integration using API Ninjas, enabling text extraction from images for seamless interaction. Features include user authentication, question management, interactive responses, voting, tagging, and customizable profiles. Built with React.js, Redux, Express.js, JWT authentication, and a responsive design for an enhanced user experience.
GitHub'Journey to the Beyond' is a thrilling, text-based choose-your-own-adventure game developed by me and two others in 12th grade, entirely in C++ with immersive sound effects. Set in 2082, players must navigate an alien planet, using logic and strategy to escape. The game challenges players to think creatively, offering an engaging, graphics-free experience that keeps them on edge with its intense and rewarding gameplay.
GitHub