CV

Research focus

At Adobe Research, I work on video and audio watermarking, with an emphasis on robustness, content authenticity, and durable media provenance. My other research includes adaptable image watermarking, conditional-access watermarking, and generative AI attribution, building on my doctoral work in proactive manipulation detection and localization, object detection, and generative-model reverse engineering.

Experience

1. Jan 2025
   Present

   Research Scientist

   Adobe Research · San Jose, CA

   Current work on video and audio watermarking, with an emphasis on robustness, content authenticity, and durable media provenance.

   Mentored interns on TokenTrace (CVPR 2026); co-developed object-level watermarking (ICCV 2025) and NRGMark (WACV 2026).

2. 2024
   2023

   Research Scientist Intern

   Adobe Research · May - November, each year

   Developed CustomMark (ICCV 2025 APAI Workshop) and ProMark (CVPR 2024) for proactive attribution in diffusion models.

3. Aug 2020
   Dec 2024

   Doctoral Research

   Michigan State University · Advisor: Prof. Xiaoming Liu

   Proactive manipulation detection and localization, generative-model parsing, and proactive object detection. Research collaborations with Meta AI and DEVCOM Army Research.

Education

Technical expertise

Languages

Python, C/C++, SQL

ML & vision

PyTorch, PyTorch Lightning, TensorFlow, NumPy, scikit-learn, OpenCV, CUDA

Research methods

Diffusion-model customization, textual inversion, token embeddings, encoder-decoder architectures, vision-language models, LoRA

Cloud

AWS, Google Cloud Storage

Service and communication

• Co-organizer, Foundations and Frontiers of Watermarking, CVPR 2026.
• Co-organizer, Reverse Engineering of Deceptions, CVPR 2023.
• Reviewer for computer-vision and machine-learning conferences and journals.
• Research presentations at Scale AI.

See the publication list and talks and tutorials for details.