User:Taghi

Mohammadtaghi (Taghi) Badakhshan received his Ph.D. from the University of Waterloo under the supervision of Professor Guang Gong, with a specialization in privacy-preserving protocols, zero-knowledge proofs, and post-quantum-secure zkSNARKs. His research includes accelerating zkSNARK protocols using optimized fast Fourier transform (FFT) algorithms in C++ and C, and designing privacy-preserving systems on smart-contract-enabled (Ethereum-like) blockchains. He collaborates on open-source cryptographic protocols.

• Ph.D. in Computer Software Engineering, University of Waterloo (2021–2025)
  • Thesis: Accelerating Post-Quantum Secure zkSNARKs and Privacy-Preserving Frameworks.
• M.Sc. in Secure Communication & Cryptography, University of Tehran (2017–2020)
  • Thesis: Security Analysis of Lightweight Clients in a Blockchain Based Peer-to-Peer Network.
• B.Sc. in Electrical Engineering, University of Tehran (2013–2017)
  • Project: Network Traffic Classification and Industrial Control System (ICS) Intrusion Detection.

• Intern (MITACS), BTQ Technologies Corp. (2024–2025)
  • Led a team consisting of a postdoctoral researcher and a master's student to analyze and accelerate the Aurora post-quantum secure zkSNARK, and prepared technical reports documenting the findings.
  • Implemented, optimized and benchmarked additive FFT algorithms in C, C++, and SageMath.
  • Reduced Aurora zkSNARK prover runtime by 40% via optimized FFT implementations.
• Research Assistant, University of Waterloo (2020–2025)
  • Designed and threat-modeled a privacy-preserving ownership protocol for supply chains on Ethereum, implemented using Aurora and Groth16 zkSNARKs in C++ and Solidity.
  • Designed and implemented application-specific zkSNARK circuits in C++.
  • Designed an arithmetic circuit for the GKR protocol to enhance efficiency of the Polaris zkSNARK.
• Teaching Assistant, University of Waterloo (2021–2024)
  • Conducted tutorial sessions and provided guidance to students for various courses, including Computer Security, Digital Circuits and Systems, Digital Computers, and Digital Computation.

By optimizing the additive FFT algorighm using the Cantor special basis, we reduced the Aurora post-quantum secure zkSNARK prover’s runtime by 40%.

• Programming Languages: C++, C, SageMath
• Tools & Libraries: CMake, memory-management helpers, SIMD instructions
• Theoretical Concepts: Abstract algebra, zero-knowledge proofs
• Code Repositories:
  1. cantor-libiop: https://github.com/mtbadakhshan/cantor-libiop
  2. additive-fft: https://github.com/mtbadakhshan/additive-fft
• Research Article:
  • Accelerating Post-quantum Secure zkSNARKs by Optimizing Additive FFT (Selected Areas in Cryptography (SAC), 2025. [PDF])

• Programming Languages: C++, Solidity
• Tools & Libraries: CMake, libsnark, ZoKrates
• Theoretical Concepts: Zero-knowledge proofs, ZK circuits, anonymous authentication, adversary modeling
• Code Repository:
  1. zupply-zkp: https://github.com/mtbadakhshan/zupply-zkp
• Research Articles:
  • Evaluating the Integration of Aurora zkSNARK in the Zupply Framework (IEEE/ACM 6th International Workshop on Engineering and Cybersecurity of Critical Systems (EnCyCriS), 2025. [DOI])
  • Zupply: Anonymously Maintained Decentralized DAG Data Record Over Public Blockchains (TechRxiv, 2024.[DOI])
  • Privacy-Preserving Ownership Transfer: Challenges and An Outlined Solution Based on Zero-Knowledge Proofs (IEEE World Forum on Internet of Things (WF-IoT), 2023.[DOI])