Erman Sinan Turan

I developed the back-end APIs and front-end implementations of a social media-like app for helping street animals. It has photo and text advert posting, comments, story posting, and P2P messaging features.

Looking Searcher is an address book application for firms. I developed both back-end and mobile UI implementations. The app has P2P messaging between firm owners and customers and location-based suggestions and promotions panels. I worked with geolocation data for the locations of firm addresses.

TVARZ is a video streaming web and mobile app that schedules video programs shared as live streaming feeling, synchronized according to time. I developed the back-end, front-end, and mobile UI implementations.

I created a GPS device tracker map project with OpenLayers and React. I used Styled-components, Redux, and Evergreen UI to build the application. It was showing live GPS locations with different icons of the devices.

Quest Social was an event scheduling app where users could share their custom events with their contacts. Events have a private messaging feature on the notification system. Users are able to message and schedule their custom events in real time via the Firebase database.

Tawk.Social was a personal mobile app project for group calling and messaging via WebRTC. Users could join audio/video group calls and message each other by text, image, gif, and emojis. The app also had a synchronized YouTube video sharing and screen sharing feature for watching videos together.

This bike rental web app was a personal portfolio project for renting bikes and other devices based on their specifications. These specifications can be the device's color, model, year, and other properties. It had two user roles as admin and customer. Admins can add and edit device entries, and customers can rent them for a specific scheduled time.

Moirai is a multi-tenant B2B SaaS platform that centralizes operations for healthcare clinics, replacing disjointed tools with a streamlined scheduling and management system. Clinics struggle with admin bottlenecks, high no-show rates, and data silos across multiple branches. They require a scalable ecosystem that is intuitive enough for patients yet robust enough for enterprise networks.

I helped design and develop a secure, automated platform featuring:
• Multi-clinic Architecture: A centralized workspace for managing multiple locations, scalable billing, and staff permissions.
• Intelligent Scheduling: An advanced booking engine with staff approval workflows, custom domains, and embeddable website widgets.
• Automated Communications: Event-driven notifications and reminders that drastically reduce patient no-shows.
• Role-based Access (RBAC): Tailored, secure portals built specifically for administrators, medical staff, and patients.

Impact: Moirai enables clinics—from solo practices to enterprise networks—to reclaim administrative hours, scale effortlessly, and provide a frictionless digital booking experience.

OTELYONET is a comprehensive, AI-driven property management system (PMS) and channel manager that digitizes hotel operations and maximizes global sales reach from a single, unified dashboard. Hotels often struggle with double bookings, manual channel updates, and high commission fees from online travel agencies (OTAs). They need a centralized platform to manage daily operations (front desk and housekeeping) while seamlessly syncing prices and availability across global sales platforms.

I contributed to developing an all-in-one ecosystem offering "turnkey" digital transformation. Key features include:
• Advanced Channel Manager: Real-time synchronization with 120+ OTAs (Booking, Expedia, and Airbnb) to eliminate double bookings.
• Commission-free Direct Sales: Built-in custom website generation with a booking engine to drive 0% commission reservations.
• Core PMS and Operations: Centralized front desk, automated identity notification system (KBS), accounting integrations, and housekeeping tracking.

OTELYONET empowers over 500 active hotels to bypass operational friction, rapidly launch on global channels within 7 days, and significantly increase direct revenue.

An enterprise-grade, direct-to-consumer online ordering platform built for McDonald's Turkey. The web app allows users to seamlessly browse localized menus, customize orders, and track deliveries in real time. A major global QSR (Quick Service Restaurant) brand requires a digital platform capable of handling massive, concurrent daily traffic—especially during peak meal times. The system needed to support complex menu logic (conditional combos, size upgrades, item exclusions) while maintaining a lightning-fast, intuitive user experience across both desktop and mobile.

I played a key role in developing/architecting the digital ordering experience. Key achievements include:
• Dynamic Menu and Cart Logic: Engineered a highly responsive ordering flow that effortlessly handles complex product customizations, promotional bundles, and automated cross-selling (e.g., sauce prompts and meal upgrades).
• High-performance Architecture: Optimized front-end performance to ensure zero-latency browsing and fast load times, preventing drop-offs during high-traffic lunch and dinner rushes.
• Seamless Integrations: Ensured robust communication between the web front-end, regional point of sale systems, and secure payment gateways.

Ligandora is an advanced, multi-tenant SaaS platform built to power deep-tech computational biology and AI-driven drug discovery. It provides researchers with a highly scalable cloud infrastructure for running complex molecular docking and biotech simulations. Computational biology requires massive computational power. Running long-duration AI models and biochemical simulations for multiple institutional clients simultaneously presents significant infrastructure bottlenecks.

I engineered a robust, high-performance distributed back end tailored for heavy scientific workloads. Key technical implementations include:
• Built a secure, isolated multi-tenant environment, allowing different research organizations and pharma clients to manage their proprietary data and simulations independently.
• Provisioned and configured Google Cloud Platform (GCP) Compute Engines with Cloud GPUs to handle the intense processing requirements of deep learning models and in-silico drug discovery services.
• Integrated BullMQ (Redis-based queue) to manage long-running background tasks. This ensures complex molecular simulations and AI predictions are processed reliably without blocking the main application thread.