Jaya Soorya

I’m a passionate and driven Machine Learning and AI enthusiast currently pursuing my B.Tech in Computer Science and Engineering (AI & ML) at Vel Tech University. My journey in AI has been defined by a strong commitment to solving real-world problems through research and applied machine learning. I specialize in building intelligent systems that not only demonstrate technical depth but also have practical impact.

Over the past few years, I’ve led multiple AI-focused projects—from EV energy prediction systems that optimize routes in real time, to anomaly detection in hyperspectral imaging for environmental safety, to building non-lethal combat detection systems using YOLOv8 and Jetson edge devices. Each of these projects has helped me develop a full-cycle understanding of the AI pipeline: from data collection and preprocessing, to deep learning model development, and finally deployment on web or edge platforms.

My technical toolkit includes TensorFlow, PyTorch, Scikit-learn, OpenCV, and tools like Streamlit and Flask for model deployment. I have experience working with diverse datasets—biomedical (e.g., sleep EEGs), environmental, and mobility—and using advanced techniques like CNNs, GRUs, transfer learning, synthetic image generation (with Stable Diffusion), and SHAP explainability.

Beyond the code, I’ve also co-authored research papers and conference presentations. I take pride in leadership, having led teams in hackathons, collaborative research, and college innovation challenges. I’ve won multiple awards, including 2nd place at IIT Patna’s Hackmatrix 2025, and consistently ranked high in intra-college technical competitions.

As someone deeply inspired by the future of AI, I strive to stay at the intersection of innovation, research, and social impact. My goal is to continue exploring cutting-edge areas like generative AI, healthcare diagnostics, and smart systems—and eventually contribute to impactful AI products that shape the world for the better.

I’m always open to collaborations, internships, or mentorship opportunities in AI, deep learning, or applied research.