Question 1

Who is Ahmed Akram (Akramovic)?

Accepted Answer

Ahmed Akram Ahmed Shawky, also known as Akramovic or 0xAkramovic, is a Software Engineer, Blockchain Engineer, Security Engineer, and Smart Contract Auditor. He is Cofounder and CTO at FuzeX and VP of Engineering at WebDBTech. He specializes in blockchain protocol design, smart contract security auditing, and building wallet systems across EVM and non-EVM chains.

Question 2

What is Ahmed Akram's expertise?

Accepted Answer

Ahmed Akram specializes in blockchain architecture and security, spanning smart contract design and auditing (Solidity, Rust), wallet systems (custodial, semi-custodial, non-custodial), DeFi protocol development, and full-stack engineering. His work covers EVM chains (Ethereum, Polygon, BASE), non-EVM chains (Solana, Bitcoin, Casper), and cross-chain solutions using tools like Hardhat, Foundry, and Slither.

Question 3

What companies has Ahmed Akram worked for?

Accepted Answer

Ahmed Akram is currently Cofounder & CTO at FuzeX (since March 2023) and VP of Engineering at WebDBTech (since August 2022). He previously worked as a Full Stack Engineer at EJADA (2023), Frontend Engineer Intern at Link Development (2022), and Deep Learning Intern at Alexandria University (2022).

Question 4

What blockchain projects has Ahmed Akram built?

Accepted Answer

Ahmed Akram has built 12+ blockchain projects including: FuzeX App (decentralized events platform with NFT ticketing), Horus Wallet (multi-chain wallet across EVM/Bitcoin/Solana), Safemoon DEX smart contracts (audited exchange architecture), AIVP (AI Value Protocol), Lussa Platform (decentralized game creation ecosystem), and Atrium.earth (blockchain + environmental conservation with DAO governance).

Question 5

What publications has Ahmed Akram authored?

Accepted Answer

Ahmed Akram won the PAN 2023 Authorship Verification Competition at CLEF 2023 with his paper 'Enhancing Authorship Verification using Sentence-Transformers' (published on Semantic Scholar). He has also contributed to white papers for Phron AI (AI-orchestrated blockchain infrastructure), ZeroGas (gas-free transactions via Proof of Holding), AIVP (AI Value Protocol), and SuperWorld (AR virtual world platform).

Question 6

What smart contract security services does Ahmed Akram provide?

Accepted Answer

Ahmed Akram conducts smart contract security audits covering gas optimization, access control enforcement, reentrancy prevention, and vulnerability assessment using tools like Slither and formal verification techniques. He has audited contracts for decentralized exchanges (Safemoon DEX), NFT platforms, wallet systems, and DeFi protocols across Ethereum, Polygon, BASE, and Casper blockchains.

Question 7

What wallet systems has Ahmed Akram developed?

Accepted Answer

Ahmed Akram has designed and built custodial, semi-custodial, and non-custodial wallet systems. His Horus Wallet supports EVM, Bitcoin, and Solana chains with email/phone authentication, asset transfers, NFT collection creation, and scheduled payments. At FuzeX, he built wallet infrastructure for the activities passport system handling NFT tickets and memberships.

Question 8

How can I contact Ahmed Akram?

Accepted Answer

Ahmed Akram can be reached via email at ahmedakramshawky@gmail.com, on GitHub at github.com/Akramovic1, on LinkedIn at linkedin.com/in/ahmedakram1, or on Twitter/X at @0xakramovic. His portfolio website is ahmedakram.dev.

Question 9

What programming languages does Ahmed Akram use?

Accepted Answer

Ahmed Akram works with TypeScript, JavaScript, Solidity, Rust, Python, C, and Java. For blockchain development he primarily uses Solidity (EVM chains) and Rust (Casper, Solana). For full-stack development he uses React, Node.js, Vue.js, Angular, and Spring Boot with cloud platforms like AWS and Firebase.

Question 10

Where did Ahmed Akram study?

Accepted Answer

Ahmed Akram studied at the Faculty of Engineering, Alexandria University in Egypt. He also completed the Deep Learning Specialization on Coursera under faculty mentorship, where he built a GAN-based image colorization model achieving approximately 70% accuracy.