Hi, I am Prajwal Negi
I am a passionate Full Stack Web Developer and a Deep Learning enthusiast. Working on projects that integrate web development with AI/ML techniques. Whether it is building responsive applications, creating efficient backend systems, or diving into deep learning models, I’m always eager to learn and innovate and open to Internship, Research Projects, Collaboration in Backend Development, or AI/ML domains.
About Me
I am a passionate software developer who loves building things that live on the internet. My journey in web development started 3 years ago, and I have been constantly learning and growing ever since.
My Journey
I discovered my passion for programming during college when I built my first web application. The excitement of seeing code come to life in the browser hooked me instantly.
Since then, I have been dedicated to mastering both frontend and backend technologies. I enjoy the entire development process, from planning and design to deployment and maintenance.
Currently I am student in NSUT, and focus on building scalable web applications using modern technologies like Nextjs, Expressjs, and cloud services. I am always eager to learn new technologies and improve my skills.
Quick Facts
Projects Completed15+
Technologies Mastered20+
Coffee Consumed∞
Technical Skills
Frontend
HTMLCSSReactNextjsTypeScriptTailwind CSSJavascriptFigmaShadCnBootstrap
Backend
NodeExpressJSPythonGraphQLtrpcWebsocketClerkZodPrisma ORMDjangoGo
Database
MongoDBPostgressSQLRedisNOSQLCDNS3
Tools & Others
Git/GithubDockerC++Deep LearningAWSKafkaKubernetesNginxLinuxCCWSCADAPLCHMI
Featured Projects
Here are some of my recent projects that showcase my skills in Full-Stack development, Deep Learning, and Open-CV and Yolo.
BroCars
Developed a full-stack web application that streamlined the online car sale and purchase process. Built with Next.js, Shadcn, TypeScript, Express.js (integrated with DDoS protection), and MongoDB, the platform ensures high performance and robust security. The app features secure authentication for smooth and reliable account management. Users can request test drives, upload their car listings, and filter vehicles based on brand, model, and price. An admin dashboard was created to manage and moderate car submissions and test drive requests, along with interactive sales reports and analytics tools. This platform successfully digitized the dealership experience, facilitated verified sales, and delivered a scalable, production-ready solution with tangible business impact.
ExpressjsNextjsTypescriptMongoDBShadcnCloudinary
Jacky
Developed a full-stack web application of Dog-Website. User can book appointment with a doctor and instructor, based on their feedback for the user house to perfrom various activities of dogs. They can upload blogs, view characteristics and instructions about the dogs, can report about StrayDog, buy dog products. User can also adopt a Puppy and a TrainedDog for respective purposes. User can search other dogs for mating of his dog and can also post information about his dog to mate, Page for collaboration is also made to partner with Jacky.
React.jsMongoDbExpressjsRedisNodemailer
AI Fashion Analyzer
Built an AI-powered web application using Next.js, TypeScript, Shadcn, and Gemini to enhance user engagement and drive sales. Integrated modern and secure authentication through Clerk, along with robust middleware protections, leading to improved user trust and retention. The app introduced a cutting-edge AI-driven style assessment feature that analyzes user-uploaded photos to predict age and body measurements with high accuracy, enabling highly personalized shopping experiences. Additionally, a curated shopping experience was launched, offering tailored suggestions that significantly increased session durations and overall sales.
ReactjsTypescriptClerkShadcnGemini
LawScope
Developed Lawscope, an intelligent legal assistant web app built with Next.js, TypeScript, Shadcn, and Gemini. The platform empowers users to upload PDFs or plain text documents, which AI then analyzes & simplifies into clear, easy-to-understand language—making complex legal terms accessible to everyone. Lawscope also offers a feature where users can describe their real-life legal situations while taking on roles such as landlord, renter, employee, employer etc. For example, a renter can explain that they've been locked out of their home after missing rent payments due to job loss, and the application will provide AI-generated legal advice, outlining what actions they can take & what legal consequences they might face—along with relevant legal sections & protections. Users can upload specific paragraphs or scenarios, and the AI will analyze the context and deliver tailored legal solutions. The platform bridges the gap between everyday problems & legal understanding.
NextjsTypescriptShadcnGemini
Sleep Tracker
Proposed and developed a Sleep Tracker web application using Next.js, TypeScript, and Shadcn UI, allowing users to log daily sleep quality, track hours slept, and visualize sleep trends through dynamic, interactive charts. The application includes optimized queries for improved performance and responsiveness. Built with Prisma ORM and NeonDB, the platform ensures secure and efficient CRUD operations while supporting a growing dataset. For user authentication and account management, Clerk was integrated with OAuth, enabling a seamless and secure login experience across multiple user accounts.
NextjsTypescriptPrismaNeonDBPostgresqlClerk
TweetBar
This Django-based web application, TweetBar, is a dynamic platform where users can post, edit, and delete tweets through a clean and responsive interface built with HTML and Bootstrap. The application includes a full authentication system using Django’s built-in features, allowing users to sign up, log in, and log out securely. Only authenticated users are permitted to create or manage their tweets, ensuring privacy and control over content. In addition to text-based tweets, the app also supports image uploads, enabling richer user interaction. Users can view tweets from others, creating a simple yet interactive microblogging experience. TweetBar is an excellent example of combining Django's backend capabilities with a modern frontend for a complete web app solution.
DjangoHTML/CSSBootstrap
Other Notable Projects
AI MOCK INTERVIEW
This is the project where user can see companies vacancy for the particular job type and can apply to it. User can also get feedback of its application for the particular company profile by the Gemini Api in it. User also provided with the option of take Practise interview where user enables his webcam and microphone and Gemini APi generate the interview question for the particular job description. The user has to answer the question and submit the responses which will be store in the database. User can also get the feedback of his interview with the Gemini Api. Also User can build his resume and get it download. Gemini Api also provide feedback to user of his resume for the particular job description.
Security Alarm System
This project is a real-time object detection system built using YOLOv8, integrated with OpenCV for video processing and SMTP email alerts for notifying unusual object presence. The application uses a webcam feed to detect objects frame-by-frame with the help of a pre-trained YOLOv8 model and overlays bounding boxes along with FPS metrics on the live video. When objects are detected, an alert email is automatically sent to a configured recipient, ensuring prompt security notification.
AI-Based Workout Monitoring System
This project is a smart fitness monitoring system built using Ultralytics' AI Gym solution, leveraging YOLOv8 pose estimation to analyze human posture and movements during workout routines like push-ups and pull-ups. By processing pre-recorded videos, the system accurately tracks key body landmarks (specifically joints like shoulders, elbows, and wrists) and monitors repetitions. The system visually overlays pose estimation outputs on each frame, counts repetitions, and generates annotated output videos for review and feedback.
Coffee Machine using Hand Gesture Recognition
This interactive virtual coffee machine utilizes hand tracking to allow users to make coffee selections using finger gestures without any physical touch. Using a webcam feed, the system detects specific finger patterns to navigate through multiple selection stages such as choosing the type of coffee, sugar quantity, and milk preference. The gesture-based interaction is visualized with an engaging UI, showing animated option selection using a progress ellipse. It provides a touchless and futuristic user experience, ideal for smart cafés.
Volume Control Using Hand Gestures
This real-time computer vision project enables users to control system volume using simple hand gestures—specifically the distance between the thumb and index finger. By tracking hand landmarks with a webcam, it dynamically adjusts the volume based on finger distance, displaying a visual bar and percentage overlay.
Virtual Keyboard
This project implements a virtual keyboard that allows users to type by interacting with an on-screen QWERTY keyboard using hand gestures captured from a webcam. Using computer vision and hand landmark detection, it tracks finger positions to detect which key the user is 'hovering' over and simulates key presses when a pinch gesture (distance between the index and middle finger) is detected.
Restaurant Name Generator
This project leverages the LangChain framework integrated with OpenAI's language model to build an intelligent restaurant name and menu generator. The system accepts a cuisine type as input and then generates a creative and fancy restaurant name tailored to that cuisine. Following that, it automatically suggests a list of relevant menu items, suitable for the generated restaurant name.
Watchlist
This project is a simple yet powerful Movie Watchlist backend developed using Go (Golang) and MongoDB. It allows users to add movies with a title and a watched status (true or false), making it easy to keep track of what they've seen. The application supports full CRUD operations—users can create new movie entries, read the complete watchlist, update the watched status, and delete movies from the list. With a clean RESTful API design and seamless MongoDB integration using the official Go driver.
Tesla Stock Prediction
This project predicts Tesla's stock trading volume using historical stock data, including prices and dates. By analyzing the data with visualizations, it explores trends and relationships between stock features and volume. Two machine learning models—Linear Regression and Random Forest Regressor—are used.
Plant Disease Predictor
A Convolutional Neural Network (CNN) was trained for plant disease classification using a dataset of images categorized into three classes: Healthy, Powdery, and Rust. The model architecture included three convolutional layers followed by max-pooling, flattening, and several dense layers. The model is trained using the Adam optimizer and categorical cross-entropy loss. During training, the accuracy steadily improved from 39.78% to 97.84%, with a final validation accuracy of 90%. Evaluation on the test set yielded a test accuracy of 93.69% and a loss of 0.2332.
Next Word Predictor
This project implements a deep learning model using LSTM (Long Short-Term Memory) networks to predict the next word in a given text sequence. A small corpus of motivational and philosophical phrases is used as training data. The text is tokenized using Keras's Tokenizer, and input sequences are generated in an n-gram style. The model architecture includes an Embedding layer to transform word indices into dense vectors, followed by an LSTM layer with 150 units to capture sequential dependencies. A final Dense layer with softmax activation is used to output the probability distribution over the vocabulary.After training the model for 100 epochs using categorical cross-entropy loss and the Adam optimizer, it can predict the next likely word for any given input phrase.
Customer Purchase Prediction
This project is a ML-based system that predicts whether a customer will make a purchase based on their demographic and behavioral data. It utilizes Logistic Regression, a supervised learning algorithm, to classify customer intent based on features such as age, time spent on the website, whether a product was added to the cart, gender, and past purchase behavior. The program accepts real-time user input to simulate customer behavior and predict their likelihood of making a purchase.
Hostel Accomodation
This is a console-based application developed in C++ to manage hostel bed reservations efficiently. The system allows students to reserve beds by entering their details, which are then stored in a file for record-keeping. It tracks available beds, updates hostel data, and ensures reservation logic through file handling operations. The project demonstrates practical knowledge of object-oriented programming, file I/O in C++. It’s a simple yet effective solution for managing hostel accommodations in small institutions.
Red Light PLC Project
As part of my PLC project work, I developed a Red Light Control System using timers, bits, and reset functions within the CCW software environment. The system was designed to mimic the functioning of a basic traffic signal. I programmed sequential lighting for red, yellow, and green phases with precise delays using on-delay timers and bit toggling. The logic was structured to ensure smooth transitions and looping behavior, replicating real-world signal patterns. This project helped me gain a strong understanding of timer-based logic, resetting sequences, and state transitions in PLC programming
Car Parking Management System
In another project, I created a Car Parking Management System that displayed available parking spots using LEDs controlled by a PLC. The system used input sensors to detect car entries and exits, updating the status of parking slots in real time. When a car was parked, the corresponding LED would turn off, indicating the spot was occupied; when the car left, the LED would turn back on. I programmed the logic to count vehicles, manage slot allocation, and reset indicators as needed. This project allowed me to apply condition-based logic and reinforced my skills in creating responsive, real-world automation systems.
DOL Startor PLC Simulation
I also built a Direct-On-Line (DOL) Starter PLC simulation, commonly used for starting 3-phase induction motors. The system included a start/stop push-button logic, motor control with contactor simulation, and overload protection integration. I implemented interlocking logic to prevent simultaneous activation and added indicators to show motor status. This project provided valuable insights into motor control circuits and safety mechanisms, reinforcing my understanding of industrial automation and protective relay integration through PLCs.
Experience & Education
My professional journey and educational background that shaped my skills and expertise in software development.
Work Experience
Freelance Developer
BRO PGDwarka, DelhiJune 2024 - July 2024
- Developed and maintained React-based web application serving 100+ users
- Help in reducing the load of owner by arranging things online
- The PG-Owner can see the Complaints posted by his guests and can update the status of the problem
- Implemented REST APIs using Node.js and Express framework
- Create listing of the properties of the PG Owner
ReactNode.jsExpressjsMongoDBFramer-Motion
Research Intern
World QuantzRemote, US BasedJune 2025 - July 2025
- Simulate alphas to refine and improve their predictive performance improving test pass rates from 78% to 87%.
- Researched behavioral finance principles by examining 80+ trading case studies.
- Competited in the International Quant Championship 2025.
- Promoted to Research Consultant.
Expressional Language
Instrumentation Intern
Bry Air(ASIA)GurgaonJune 2025 - July 2025
- Explored industrial dehumidifiers and their integration into automation systems.
- Worked with contactors, relays, RTDs, and sensors for motor control and process automation.
- Programmed PLCs using CCW and built basic HMI control logics.
- Learned to read electrical drawings and observed machine calibration and testing.
PLC ProgrammingHMI ProgrammingDehumidificationReactjsRTDsSCADAElectrical DrawingElectronics EquipmentsRelaysThyristorsSMPS
Education
BTech in Instrumentation and Control Engineering
Netaji Subhas University of TechnologyDwarka, Delhi2022 - Present
Relevant coursework: Data Structures & Algorithm, Software Engineering, Web Development, Deep Learning Enthusiast
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