Vaishnavi Mamidala

I’m an Engineering student and Research Intern with a strong interest in the intersection of Artificial Intelligence, Cybersecurity, and DevOps. I enjoy building systems that are not only intelligent, but also secure, scalable, reliable, and practical to deploy. My current work involves AI-driven drug discovery, where I work with deep learning, Graph Neural Networks, diffusion models, SE(3)-equivariant architectures, reinforcement learning, and molecular modeling. Although this research experience has strengthened my understanding of machine learning and complex systems, my broader career interests extend beyond research into building real-world AI systems and infrastructure. I have hands-on experience with Python, C, Java, JavaScript, React, Node.js, PyTorch, PyTorch Geometric, Git, Linux, Docker, CUDA, and deployment tooling. I particularly enjoy working close to the system level, whether that involves configuring Linux servers, networking and secure remote access, containerization, deployment, or understanding how software behaves in production environments. I’m increasingly focused on the intersection of AI and cybersecurity, with an interest in areas such as AI-powered security, automated threat detection, secure infrastructure, adversarial machine learning, and intelligent security systems. At the same time, I’m developing my DevOps and cloud engineering skills to understand how modern applications are built, deployed, monitored, and secured at scale. I prefer learning by building rather than simply following tutorials. I like taking a problem apart, understanding the underlying concepts, implementing a solution, and then improving it until it is robust enough to be genuinely useful. My goal is to become a strong engineer who can bridge AI, security, and infrastructure, building intelligent systems that are reliable, secure, and production-ready.