Nikhil Reddy Billa

I am Nikhil Reddy Billa, a graduate student, researcher, and AI enthusiast, currently pursuing my Master’s in Computer Engineering at Virginia Tech. I am a Graduate Research Assistant at the Responsible Data Science Lab, where I focus on privacy and security specifically memorization in LLMs, adversarial robustnes. My research is driven by innovation in AI with a strong emphasis on privacy, safety, and trustworthiness.
Previously, I earned my B.Tech in Electrical Engineering from NIT Rourkela and worked as a Software Engineer at NCR Corporation. My experience spans both industry and academia, allowing me to bridge cutting-edge research with real-world AI applications.
My research spans multiple areas, including AI security, computer vision, and autonomous navigation.Currently I am working on LLM memorization risks, adversarial robustness, and trustworthiness, ensuring the safe deployment of AI models. My previous work in computer vision and image forensics involves developing CNN-based techniques for digital integrity verification, while my contributions to autonomous navigation focus on enhancing segmentation models and data for unstructured traffic and adverse weather conditions. Additionally, During my time at IIIT Hyderabad I have collaborated with University of Leicester on unsupervised domain adaptation for medical AI, specifically analyzing retinal development.
Beyond research, I actively contribute to the AI community as a Reviewer for the JISA, evaluating research on AI security. I engage in open-source collaborations and stay at the forefront of LLMs and multimodal AI to drive impactful innovations.
I am actively seeking opportunities that align with my expertise, allowing me to develop AI solutions that prioritize safety, privacy, and real-world impact. Let’s connect and collaborate!
Please find my CV here
news
Feb 01, 2025 | I am reviewer of Journal of Information Security and Applications, Elsivers |
---|---|
Jan 01, 2024 | Our paper IDD-AW: A Benchmark for Safe and Robust Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weather is published at WACV 2024 |