Bio

Anudeep Vurity
My research advances secure contactless fingerprint authentication by developing robust Presentation Attack Detection (PAD) algorithms. I apply Computer Vision and Deep Learning to improve PAD resilience under diverse conditions, focusing on defenses against spoofing, adversarial attacks, and privacy threats like model inversion. I also explore machine unlearning to support data compliance and right-to-forget principles, while enhancing PAD interpretability to ensure fairness and trust in biometric systems.

Education:

  • George Mason University – Ph.D. in Information Science Technology (August 2019 – Dec 2025 (Expected))
  • George Mason University – M.S. in Data Analytics Engineering (Aug 2019 – May 2021)
  • JNTU Hyderabad – B.Tech in Electrical and Electronics Engineering (Aug 2015 – May 2019)

Expertise:

  • Languages & Tools: Python, R, SQL, Kotlin, LaTeX, MATLAB, Bash, Excel, Tableau
  • Frameworks & Libraries: PyTorch, TensorFlow, LangChain, Keras, Scikit-learn, OpenCV, Pandas, NumPy, LIME, SHAP, Matplotlib, Pillow
  • GenAI & Systems: AWS (S3, Redshift, Bedrock, EC2, SageMaker, Q, Rekognition, Textract), Docker, HuggingFace, SLURM, Argo/Hopper Clusters, Git, Jupyter, Linux, Copilot Studio, Agent SDK, CI/CD, Shell scripting
  • Soft Skills: Critical Thinking, Public Speaking, Problem Solving, Team Player
  • Languages Spoken: English, Telugu, Hindi