Senior Scientist · Cryptography
Ahmad Al Badawi, Ph.D.
I work at the intersection of applied cryptography and machine learning, advancing fully homomorphic encryption toward practical, deployable systems for private AI.
- 50+ Publications
- 2,300+ Citations
- 20 h-index
- $22M+ Funded research
Recent publications
Cryptology ePrintPreprint SoK: Private LLM Inference using Approximate Homomorphic Encryption
IACR CiCJournal Application-Aware Approximate Homomorphic Encryption: Configuring FHE for Practical Use
IJRESJournal Hardware Design for Fast Gate Bootstrapping in Fully Homomorphic Encryption over the Torus
Recent writing
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The Math of Slot Rotation in BGV and BFV
Ahmad Al Badawi
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SIMD Packing in BGV/BFV FHE Schemes
Ahmad Al Badawi
Recent talks
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OpenFHE: A Community-Driven Open-Source Project for FHE
I had the pleasure of participating in the NUMFOCUS Project Summit 2024, which was held at the Microsoft New England Research & Development (NERD) Center, Cambridge, MA, United States, to share...
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FHEllo, world! FHE Community Workshop
I had the pleasure of participating in the FHEllo World! workshop, a community-oriented online event focused on Fully Homomorphic Encryption (FHE). During the workshop, I presented a talk on the Op...
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enCRYPTON: Summer School on Cryptographic Solutions for Privacy Enhancing Technologies
I participated in this workshop as an instructor and gave five lectures on the following topics:
About
I am a dedicated researcher specializing in applied cryptography and privacy-preserving technologies - fields focused on developing efficient methods to secure data throughout its lifecycle, whether at rest, in transit, or in use. I hold a Ph.D. in Electrical and Computer Engineering from the National University of Singapore (2018) and have built a strong publication record with papers in prestigious journals and top-tier conferences. Beyond research, I have taught university courses, built and led research teams, and advised deep-tech startups on designing and deploying secure, privacy-aware solutions. My expertise extends to hardware acceleration, where I focus on optimizing the performance and efficiency of complex cryptographic operations.
My goal is to contribute to a more secure and resilient digital world - bridging theoretical foundations and practical solutions to make privacy-preserving computation usable at real-world scale.
For details on my current and past projects, funding, and research themes, see my research page. For the work in code, see open-source contributions.