Zerdalu 's Work | ContraWork by Zerdalu Zerdalu
Software Developer
In May 1839, Scottish painter David Roberts documented the monumental ruins of antiquity across Egypt and the Levant, later published as iconic tinted lithographs. For this series, we imagined his fictional successor in 2026 embarking on a parallel grand expedition to document the colossal 'monuments' of the Anthropocene. Using Roberts’ signature sepia linework, warm gouache washes, and theatrical perspective, the series illustrates contemporary architectural landmarks. Sourced from the public domain archives of the Wellcome Collection, Roberts’ nineteenth-century romantic ruin aesthetic is repurposed to capture architecture the modern age. Newly designed zerdalu.com (https://zerdalu.com)
I got inspiration from here: https://tr.pinterest.com/pin/1152217885971073671/ Derbent is an edge-native Single Sign-On (SSO) and authentication engine built specifically for the Cloudflare ecosystem. I built this to solve the complexity and latency issues associated with traditional authentication setups, aiming to create a centralized, self-hosted service that securely manages user sessions across multiple subdomains.
What I Built
I engineered a highly secure, stateful authentication backend from the ground up using Cloudflare Workers, Cloudflare D1 (SQLite), and KV storage. Instead of relying on stateless JWTs—which are notoriously difficult to revoke—I designed a stateful session architecture. This ensures immediate session invalidation and superior security, all while running with zero cold starts at the edge, globally closer to the user.
Key Features & Technical Achievements:
- Edge-Native Performance: Deployed entirely on Cloudflare Workers, ensuring millisecond latency and high availability without managing traditional servers.
- Stateful SSO Architecture: Engineered a cross-subdomain Single Sign-On system that securely authenticates users across a suite of microservices seamlessly.
- Advanced Security Measures: Built-in session hijack protection, IP and User-Agent tracking, and detailed audit logging to maintain high security standards.
- Service Binding Integration: Utilized Cloudflare’s Service Bindings to allow internal apps to securely verify sessions with zero network overhead.
- Seamless OAuth: Integrated GitHub OAuth for frictionless user onboarding and login.
The Impact
This project highlights my deep understanding of backend infrastructure, modern edge computing, and application security. It demonstrates my ability to design scalable, centralized microservices and tackle complex architectural challenges—like secure cross-domain authentication—without relying on heavy, off-the-shelf third-party providers. Nâmedâr is an offline-first Optical Mark Recognition (OMR) platform designed for educators. I built it to solve a major problem in EdTech: the privacy risks and latency of uploading sensitive student exam data to cloud servers for grading.
What I Built
I engineered a full-stack solution that allows teachers to create, scan, and instantly grade paper exams entirely within their web browser. To achieve this without relying on backend servers, I developed a high-performance computer vision engine using Rust and WebAssembly (WASM). This handles complex image perspective correction and grading locally on the user's device, guaranteeing a "zero-upload" privacy model where student data never leaves the computer.
Key Features & Technical Achievements:
- Advanced In-Browser Processing: Leveraged Rust and WASM to bring heavy optical scanning computations directly to the frontend, resulting in lightning-fast, offline grading.
- Modern Frontend Architecture: Built a highly responsive UI using React and TanStack Start.
- Intuitive Form Builder: Implemented a drag-and-drop interface allowing educators to design custom bubble sheets easily.
- Data Portability: Engineered multi-format data exports (CSV, JSON, XML) so teachers can seamlessly sync grades with their school's existing systems.
The Impact
This project demonstrates my ability to take a complex, backend-heavy concept (computer vision/grading) and successfully migrate it to the frontend. It showcases my expertise in combining modern web frameworks (React) with systems-level languages (Rust) to build fast, secure, and privacy-first web applications.