Portrait of Bardia Taghavi

Bardia Taghavi

PhD Candidate, Florida Atlantic University · Cryptographic Hardware Engineer, PQSecure

Boca Raton, Florida · Born July 23, 1994

I design hardware for post-quantum cryptography. My work covers the polynomial arithmetic behind ML-KEM and ML-DSA, from tiny cores for IoT devices to fully parallel FPGA accelerators. I'm now extending this work to FALCON (FN-DSA).

News

Research

High-performance PQC hardware

Parallel and unified polynomial cores that run every multiplication ML-KEM and ML-DSA need. ParallelNTT cuts NTT latency 24× on UltraScale+ FPGAs.

Lightweight cryptography

Cores for constrained devices. KNightCore multiplies ML-KEM polynomials with zero DSP blocks; LightNTT uses a constant-geometry pipeline.

FALCON (FN-DSA)

New work on hardware for FALCON, the NTRU-lattice signature scheme NIST is standardizing as FN-DSA, with its floating-point FFT and Gaussian sampling.

Side-channel security

Masking and shuffling for polynomial arithmetic, and power-analysis attacks on hardware ML-DSA in a post-quantum root of trust.

Publications

  1. Springer 2026

    High-Performance Post-Quantum Cryptographic Engineering in Hardware

    B. Taghavi et al. · Book chapter

  2. IEEE TCAD · Under review

    HyperPoly: A High-Throughput Unified Core for Full-Spectrum Polynomial Arithmetic of ML-KEM and ML-DSA

    B. Taghavi, R. Azarderakhsh, M. Mozaffari Kermani

  3. LightSEC 2025

    LightNTT: A Tiny NTT/iNTT Core for ML-DSA Featuring a Constant-Geometry Pipelined Design

    B. Taghavi, R. Azarderakhsh, M. Mozaffari Kermani · Springer LNCS

  4. QRSEC @ CCS 2025

    KNightCore: An Ultra-Lightweight NTT-Based Polynomial Multiplier for ML-KEM on Resource-Constrained Platforms

    B. Taghavi, R. Azarderakhsh, M. Mozaffari Kermani · ACM

  5. GLSVLSI 2025

    ParallelNTT: Maximizing Performance of Forward and Inverse NTT on FPGA for ML-DSA and ML-KEM

    B. Taghavi, R. Azarderakhsh, M. Mozaffari Kermani · ACM

Talks & posters

Crypto Cafe slides: PDF. The ewNA tutorial comes with a Jupyter notebook that implements ML-KEM and ML-DSA in pure Python (download .ipynb).

Teaching

A three-part lecture series on post-quantum cryptography, from first principles to the internals of ML-KEM and ML-DSA.

TA and lab instructor at FAU for Advanced FPGA Design, Cryptographic Engineering, Structured VLSI Design and Design of Digital Systems.

Experience

Education

Service

Reviewer for IEEE HOST 2025 and 2026, ARITH 2026, IEEE Transactions on Computer-Aided Design (TCAD) and IACR Transactions on Cryptographic Hardware and Embedded Systems (TCHES).

Contact

For research collaboration, talks or PQC hardware questions: bardia.taghavi@pqsecurity.com or staghavi2024@fau.edu.