Welcome to my GitHub! I’m a passionate AI Researcher, AI Tools Expert, and Computer Vision Specialist focused on planetary image enhancement, satellite imagery processing, and advanced deep learning techniques.
I love building solutions that bridge the gap between space science and artificial intelligence.
I recently completed a research internship at ISRO – Space Applications Centre, where I developed enhancement models for Martian surface imagery.

• 🔭 Recently developed GAN, ResNet, and U-Net based pipelines for enhancing planetary surface images using reflection padding, feathered stitching, and perceptual quality metrics.
• 🌍 My work focuses on Mars terrain analysis, crater detection, and super-resolution for space applications.
• 📚 I’m consistently learning and pushing boundaries in Data Science, Deep Learning, and Computer Vision.
• 💬 Ask me about: Deep Learning, GEN AI Tools, Image Processing, Data Science, LLMs, Satellite Imagery, or anything Space-Tech + AI!
• 📫 How to reach me: LinkedIn | Email

Image Enhancement Models: CNN, U-Net, GAN (Pix2Pix, CycleGAN), ResNet, Reflection Padding, Feathered Stitching
Computer Vision & Preprocessing: Satellite Imagery, Crater Detection, MSR, CLAHE, Adaptive Gamma Correction, Median Filter, Bilateral Filter, SSR, Mars Image Enhancement
No-Reference Metrics (Custom NumPy): BRISQUE, NIQE, PIQE, Entropy, SNR, HVS
Cloud & Compute: NVIDIA DGX, Google Colab GPU, ISRO-HPC

Languages : Python, C, HTML, CSS, SQL
AI/ML Frameworks : TensorFlow, Keras, PyTorch, OpenCV
Concepts : Deep Learning, CNNs, GANs, Image Preprocessing, Computer Vision, Data Science, Prompt Engineering
Tools : GEN AI Tools, NumPy, Pandas, Matplotlib, Git, Microsoft Office, Adobe Illustrator, Canva, Power BI, Excel, Canva, Jupyter Notebook, Google Colab, VS Code
Other : UI Designing, Editing, Data Analytics
Soft Skills : Analytical Thinking, Research-Oriented Mindset, Attention to Detail, Collaboration and Teamwork, Time Management

• Developed a deep U-Net model with skip connections and attention layers
• Enhanced satellite terrain features with high contextual accuracy across patch boundaries

• Developed and documented a complete planetary image enhancement pipeline as part of a research paper during ISRO internship
• We have evaluated our proposed methods using Indian Mars Colour Camera (MCC) images and compared with other state of the art image enhancement techniques. It involves Adaptive Gamma Correction (AGC) to correct brightness, Contrast Limited Adaptive Histogram Equalization (CLAHE) to locally enhance contrast, noise removal via median filtering, sharpening fine details through unsharp masking, and edge-preserving smoothing by bilateral filtering. In addition, we assess the improved performance of Mars Colour
• Demonstrated results on Martian terrain with quantitative and visual comparisons

• Designed a Pix2Pix GAN to enhance Martian surface images with reflection padding and Gaussian feather stitching
• Improved perceptual quality without introducing boundary artifacts
• Evaluated using BRISQUE, NIQE, and entropy metrics

• Created a patch-level deep learning pipeline for large planetary images
• Implemented seamless stitching, patch line removal, and adaptive enhancement strategies

• Implemented a ResNet-based enhancement network for improving fine surface details in planetary imagery
• Compared performance with U-Net and GAN pipelines for various patch sizes
• Integrated reflection padding and evaluated using no-reference IQA metrics
• Achieved superior enhancement in low-texture crater regions and edge fidelity

• Built a complete image classification pipeline using CIFAR-10 dataset
• Developed a baseline CNN and advanced to MobileNetV2 transfer learning
• Implemented training, evaluation, and real-time inference scripts
• Visualized results with confusion matrices, training history, and accuracy plots
• Designed as an educational and research-friendly framework for rapid AI prototyping

• Multi-Language Support – Offline Speech Recognition for English, Hindi & Gujarati using optimized language models.
• Lightweight Execution – Core files like offline_stt.py, offline_stt_hi.py, and offline_stt_gu.py handle speech-to-text efficiently without heavy dependencies.
• Configurable & Scalable – settings.json allows easy customization, and the project supports modular expansion for additional languages.
• Testing Made Easy – test_stt.py enables quick testing & validation of all models for smooth execution.
• External Model Hosting – Heavy models stored on Google Drive for easy download.

• End-to-End Automation - Fully scheduled n8n workflow that automates trending topic research without manual execution.
• Dynamic Keyword Selection - Rotational keyword strategy ensures diversified and unbiased trend discovery across executions.
• Multi-Platform Data Integration - Aggregates trending signals from YouTube Data API v3 and NewsAPI with fault-tolerant design.
• AI-Driven Content Ideation - LLM-oriented analysis pipeline designed to synthesize cross-platform trends and generate strategic content ideas.
• Structured Output Storage - Automatically persists insights into Google Sheets using timestamped, structured records for downstream use.

• 🎓 Research Intern – ISRO, Space Applications Centre, Ahmedabad
• 🌍 Developed and author of a research paper on planetary image enhancement pipelines for Earth and interplanetary missions
• 🏅 Built fully custom no-reference image quality metrics (BRISQUE, NIQE, PIQE, etc.) without third-party libraries on ISRO DGX cluster
• 🚀 Contributor to advanced AI solutions for satellite change detection and image restoration in ISRO
• AI Tools in the Workplace Certificate : Covered Prompt Engineering, ChatGPT - June 2025
• Deloitte Data Analysis Virtual Internship (Forage) – June 2025
• Predictive Modeling : Forecast Like a Pro - July 2025
• Excel Using AI Workshop - July 2025
• Work Ready Certificate by BEEP and Shark Tank - July 2025
• AI Dashboards using Microsoft Power BI - July 2025
• Machine Learning with Python : k-Means Clustering by LinkedIn Learning - July 2025
• 5 Days Python for Data Science Bootcamp - July 2025
• Freedom withh AI Masterclass - August 2025
• BUILD AN AI THAT SEES : IMAGE RECOGNITION - August 2025
• IEEE Student Branch Member – 2022 to 2023 Video and Image Editing Contributor – IEEE Student Branch

• 🔗 LinkedIn
• 📬 Email

Thanks for visiting my profile!
Let’s build intelligent solutions that explore the universe. 🚀

⭐️ From Shivam Raval