Sid Padmanabhuni
Engineering Intern at Aryaka Networks
Undergraduate Researcher at Arizona State University
Engineering Intern at Aryaka Networks
Undergraduate Researcher at Arizona State University
I am an undergraduate student studying Computer Science at San Francisco State University. My interests lie in Human-Computer Interaction (HCI) and Artificial Intelligence (AI). Previously, I was a researcher working on projects focused on designing and evaluating interactive tools for a robot hand collection and creating accessible video descriptions for visually impaired users. My research also involved developing AI-driven systems to generate video descriptions, enhancing accessibility and user experience.
At Aryaka Networks, I developed and deployed advanced security solutions for monitoring and controlling GenAI-related transactions, focusing on both network and application layers. I built parsers to intercept, analyze, and redirect GenAI HTTP traffic to our Envoy proxy, enabling robust monitoring and granular policy enforcement. Additionally, I designed and implemented security features at the Firewall layer to detect, track, and enforce compliance policies, ensuring enterprise data protection (DLP). My role also encompassed full-stack development, where I defined RESTful APIs, integrated the backend SQL database with the controller plane, and contributed to the GUI design to seamlessly connect frontend and backend components. Throughout this work, I strengthened my expertise in cloud security, API monitoring, microservices architecture, and scalable infrastructure, enhancing my problem-solving capabilities in AI-driven cybersecurity.
Below are some of my publications and articles. Feel free to reach out if you have any questions or would like to collaborate on a project.
In Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports (HRI)
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In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), 2025.
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This article elaborates on the security threats that Secure Web Gateways (SWGs) address and how they mitigate these threats. It then delves into how GenAI-based Internet Access patterns render the current SWG functionality ineffective, leading to a discussion on new approaches.
Published on December 20, 2024
In today’s rapidly evolving digital landscape, Large Language Models (LLMs) have become integral to numerous applications, from virtual assistants to content generation. However, their widespread adoption brings forth a range of security challenges to be addressed.
Published on November 29, 2024