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Data Science with less than a year in AI, Machine Learning & Deep Learning
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As a passionate and detail-oriented AI & Data Scientist enthusiast from Innomatics Research Labs, I aim to leverage my strong foundation in statistics, machine learning, NLP, Deep Learning, Gen AI and programming to contribute to data-driven decision-making in a growth-oriented organization. Eager to apply my skills and gain hands-on experience in the field of data science.
S.G.S govt.pg autonomous college sidhi
Bachelor of Science · Maths
N/A – June 30, 2024
Innomatics Research Labs
Data Science intern
November 1, 2025 – March 1, 2026
India
Wine Quality Prediction Using Python and Scikit learn
June 23, 2026 – Present
Developed an end-to-end machine learning pipeline to predict wine quality using physicochemical features such as alcohol, density, and acidity. Performed exploratory data analysis, preprocessing, and feature engineering to improve model performance and reliability. Trained and optimized multiple ML models, selecting the best-performing one for accurate quality prediction. Built an interactive Streamlit app to allow users to input wine characteristics and receive real-time quality predictions.
View ProjectAI Powered Multimodal Chatbot Using Gemini
June 23, 2026 – Present
Built a lightweight multimodal application enabling both text-based conversations and AI-generated images using Google Gemini API. Designed an interactive interface where users enter text prompts and instantly receive high-quality generated images. Implemented clean, single-file architecture (app.py) handling prompt processing, model inference, and output rendering. Ensured smooth user experience by optimizing request handling, error control, and multimodal response generation.
View ProjectStable Diffusion-Powered Image Generation App (Python + Streamlit)
June 23, 2026 – Present
Built a Streamlit-powered Text-to-Image Generator using Stable Diffusion v1.5 to convert natural language prompts into high-quality AI-generated images. Implemented adjustable generation settings including guidance scale, inference steps, and display width for user-controlled outputs. Developed a gallery feature to save, display, and manage previously generated images for easy access and reuse. Designed a clean, responsive UI using Streamlit, providing an intuitive and interactive user experience for generating and downloading images.
View ProjectPneumonia Detection from Chest X-rays image using (CNN)
June 23, 2026 – Present
Developed a CNN-based model to classify chest X-ray images into Normal and Pneumonia categories for early detection. Performed image preprocessing and augmentation (resizing, normalization, rotation, flipping) to improve model performance. Implemented Grad-CAM visualization for model explainability, highlighting critical regions in X-ray images. Built a Streamlit web app for real-time, interactive predictions with user-uploaded chest X-ray images.
View ProjectAgentic Based APP/GAME Generator
December 1, 2025 – December 31, 2025
Built an AI-driven App/Game Generator using Streamlit + n8n that converts user prompts into fully functional apps or Python games with real-time execution. Implemented automatic code generation, file creation, and app/game detection to streamline end-to-end deployment. Optimized user experience with a clean Streamlit interface, enabling seamless prompt input and instant app/game launch.
Agentic Based Presentation Generator
November 1, 2025 – November 30, 2025
Developed an automated PPT generator using Streamlit, n8n, and python-pptx to create complete slide decks from a single user prompt. Integrated LLM workflows to generate structured slide content, themes, and layouts with instant .pptx download. Enhanced presentation quality by implementing dynamic slide formatting, color themes, and automated content organization.
Smart Query Routing System
November 1, 2025 – November 30, 2025
Automated student query classification using sentiment analysis and LLMs to assign issues to correct departments. Designed an n8n workflow that pulls form data, detects urgency, classifies category, and sends emails to respective HODs. Improved operational efficiency by reducing manual query handling and ensuring timely responses to students.
Data Science Course Completion
Innomatics Research Labs
August 23, 2025 – Present
Advanced Data Science with Python Gold Badge
NASSCOM Future Skills Prime
April 9, 2025 – Present
AI Basics For Beginners
HP LIFE (AI BASICS)
April 5, 2025 – Present
Master in Data Management For Beginners
TCS-iOn (DATA MANAGEMENT)
April 5, 2025 – Present
Cultural Fit Analysis
The candidate's project portfolio shows a strong alignment with modern data science trends, particularly in AI, Generative AI, and MLOps (deployment with Streamlit). The diversity of projects, from multimodal chatbots to image generation and classification, indicates a broad interest and willingness to explore different domains within data science. The open-source contributions further highlight a collaborative spirit and a desire to share knowledge, which are positive indicators for cultural fit in a growth-oriented, innovative environment. The candidate's enthusiasm for continuous learning, as shown by multiple certifications, also aligns well with a culture of innovation and skill development.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and a proactive learning attitude through self-directed projects and open-source contributions. The ability to build end-to-end applications with interactive UIs (Streamlit) suggests good problem-solving and user-centric design thinking. The focus on automation and efficiency in projects like 'Smart Query Routing System' indicates an operational mindset. However, with limited formal work experience, the candidate's ability to navigate complex team dynamics, handle project management, or adapt to corporate operational structures is yet to be fully demonstrated.