- Bachelor of Technology, Civil Engineering | Zakir Husain College of Engineering and Technology, Aligarh Muslim University (2020-24)
Machine Learning Intern @ Feynn Labs (_June 2024 - August 2024)
- Developed AI product prototype.
- Conducted market segmentation for the company's projects using Machine Learning.
- Developed business and financial modeling for an AI-based product.
Technical Team Member @ IEEE Computer Society (ZHCET) (_November 2023 - June 2024)
- Contributed to various Machine Learning projects for the organization.
- Conducted research and literature reviews in deep learning, computer vision, and natural language processing.
- Assisted in organizing workshops, seminars, and events related to computer science and technology
- User-friendly chat interface with concise responses for general queries and detailed explanations for programming-related questions
- Utilized the GroqCloud API to integrate the Flask web app to the llama-3.3-70b-versatile LLM in backend.
- Web application designed to detect pneumonia from chest X-ray images.
- DL model utilizes a VGG19 CNN pretrained on ImageNet, fine-tuned for pneumonia detection
- Streamlit-based NLP web application that predicts the top 3 job categories of a resume along with confidence scores.
- The model is trained on SVC algorithm and uses Regular Expressions for data cleaning and TfidfVectorizer for text vectorization.
- This project is a web application that allows users to scrape product reviews from Myntra (a popular Indian e-commerce website) based on a specified query. Users can enter a product query and specify the number of products they want to search for.
- The app then scrapes reviews for these products, displays them in a table, and provides an option to save the data to MongoDB. The results are also available as a downloadable spreadsheet.
- This project is a machine learning-based application for detecting faults in sensor data. It uses Flask as a web framework, Docker for containerization, GitHub Actions for CI/CD, and MongoDB for data storage.
- The application can be deployed locally, on AWS EC2, or through Amazon ECR/ECS using an automated pipeline.
- The NLP web application utilizes Google’s Pegasus LLM for text paraphrasing using the Hugging Face Transformers library in Python
- Users can input text through the web interface and receive multiple paraphrased outputs generated by the Pegasus model.
- Studied the mechanical and durability characteristics of the concrete using different industrial waste materials such as fly ash, iron slag, GGBS (Ground Granulated Blast furnace Slag), and jarosite.
- Utilized various ML algorithms to predict the mechanical and durability properties, bridging the knowledge gap where their application has been limited in previous studies.
- Applied SHAP analysis to check the features on the predicted values.
- International Journal of Engineering Applied Sciences and Technology, 2022 Vol. 7, Issue 9, ISSN No. 2455-2143, · Jan 23, 2023 Publication link
- International Research Journal of Engineering and Technology (IRJET) · Jan 1, 2023 Publication link
- Muskurahat Foundation | Internship (August 2023 - September 2023)
- InAmigos Foundation | Internship (June 2023 - July 2023)
- Team Everest NGO | Internship (December 2021 - January 2022)