Software Engineering | Hamad Bin Khalifa University
Software Engineering

Research Engineering Group

Founded in 2018, the Research Engineering Group was established with the vision of becoming an innovation hub that generates transformative solutions addressing real-world challenges of both local and global significance. Our mission is to transform QCRI research outcomes into robust, commercially viable products. Our team has a distinct focus on creating solutions that have tangible real-world applications and strong commercial prospects. By leveraging QCRI’s research expertise, we develop products that stand out in both innovation and practicality.

Our engineering practices are grounded in the Agile software methodology that fosters adaptability, collaboration, and iterative progress. This enables us to stay responsive to evolving research and project requirements. Our current projects include:



Allama is a specialized AI (Artificial Intelligence) based chatbot, designed to serve as a one-stop information source for all government services in Qatar. It aims to assist anyone, including citizens, residents, businesses, government employees, and foreign entities, with questions about governmental procedures, laws, regulations, and more. Leveraging the latest advances in Large Language Models (LLMs), the system interprets and generates answers to user inquiries conversationally. Allama aims to provide accurate and up-to-date information, helping users navigate government processes more efficiently.


SIHA (System for Integrated Health Analytics)

SIHA is a cloud-computing platform that enables the development of diverse digital health solutions and applications using data from various wearable fitness trackers, smart IoT medical devices, and electronic medical records. The platform offers several features including support for clinical workflows, automated data collection from a wide range of wearables and medical devices, compliance monitoring, analytics, and customizable dashboards. Solutions powered by SIHA range from chronic disease management systems, remote patient monitoring solutions, and clinical trial tools, to comprehensive health and fitness tracking mobile apps for promoting overall health. SIHA was deployed in several clinical trials at Hamad Medical Corporation and Weill Cornell Medicine – Qatar.



FEHRIS is an intelligent personal content management solution, designed to streamline the organization and accessibility of various data types and information across an array of platforms and devices. It empowers knowledge workers by enhancing their efficiency and productivity by providing a systematic and robust arrangement of their data. Through the utilization of tags and categories, FEHRIS facilitates the organization of URLs, documents, notes, and multimedia files – encompassing images and videos – that are amassed throughout their tasks. FEHRIS can be seamlessly accessed across multiple devices, simplifying the process of locating and retrieving these data items when needed. By utilizing large language models, FEHRIS also offers the unique functionality of engaging in interactive conversations with your data. FEHRIS is being customized as an enterprise solution for the Qatar National Library in its efforts to fight the illegal trafficking of historical artifacts.



MedQoder is an AI-enabled system that powers multiple healthcare-related solutions including medical coding, clinical documentation, and auditing of clinical records. MedQoder uses cutting-edge AI and NLP techniques to process thousands of records instantly. It integrates with the Electronic Medical Record, gets all the relevant clinical data from patient records, and then produces accurate diagnoses and procedure codes in ICD 10 format that can then be used for billing, auditing, or documentation.



This is a bilingual news app that caters specifically to the Arab world, gathering news from over 2,500 Arabic and English media sources in the region. It offers a comprehensive platform for users to stay informed about the latest news and events. ZAMAN app works by grouping related news articles together, providing users with a concise view of the news and the ability to compare news coverage across various sources. It offers headline translation and highlights sources that are relevant to the user's selected country. With push notifications for important stories, Zaman delivers timely updates to keep users informed. The app's interface is intuitive for both Arabic and English speakers, making it an accessible and convenient way to stay informed about the Arab world. The app was downloaded more than 10K times from different app stores.



Judo is a web-based traffic micro-simulator that utilizes a parallelized version of SUMO (a widely used open-source multi-modal traffic simulation package) that was developed by QCRI called qarSUMO. The system aims to fill the gap in the market for usable web-based microsimulation systems, leveraging the open-source SUMO platform to provide accurate traffic simulations. With its unique combination of web-based accessibility and robust microsimulation capabilities, JUDO is poised to become a valuable tool for transportation planning and analysis.



SAQR is a scalable and customizable X (formerly Twitter) analytics platform. It offers top-k analytics and uses in-house research to perform dialect identification, Arabic lexical search, propaganda detection, offensive language detection, and much more. Users can also set up scheduled reporting and real-time alerts to stay updated on social media activities of interest. Given its capability to handle large amounts of data, SAQR comes with a monitoring platform that provides insights into system health, performance, usage, and activity. SAQR has been used by several researchers and government entities in Qatar. It was also used to provide instrumental intelligence on different health-related matters during the COVID-19 pandemic to public health authorities in Qatar.



In an impressively brief period, the Research Engineering Group has successfully processed a range of key projects through the technology transfer and commercialization pipeline. Notable among these are:



QARTA is a data-driven map engine, powered by real-time GPS data and advanced machine learning models, to provide affordable and highly precise mapping and navigation services. Businesses and government entities can elevate their operational efficiency by using QARTA to optimize routes, traffic flow, and transportation logistics. Tasks from basic traffic monitoring and routing to complex route operations and estimated time of arrival (ETA) predictions are supported by QARTA. It can serve millions of routing requests in real-time and has been shown to outperform Google Maps in ETA accuracy at potentially a fraction of the cost. QARTA has been serving Karwa, the National Taxi company, and Rafeeq, a delivery company, for several years.



The Qatar National Library (QNL) is routinely tasked with monitoring and cataloging illegal trading or trafficking of historical artifacts. This involves a manual process of tracking suspicious posts and classifieds on commercial websites and social media, typically, in files and spreadsheets that are then shared between various stakeholders, making it tedious and error-prone. To improve their efficiency, FEHRIS is being customized to automate the search and cataloging process and enable cross-organization collaboration in QNL’s workflow through a single integrated interface.



Decision makers, public health professionals, and researchers often need to conduct a systematic review in support of their evidence-based decision-making. For example, evidence-based medicine relies on systematic reviews of clinical trials to show what treatments have been proven to work and what remains unknown. However, the process of systematic review creation and maintenance is labor and time-intensive, requires sifting through and screening thousands of studies, and needs collaboration and sharing between authors. RAYYAN was built as an end-to-end collaborative platform meant to expedite the creation of systematic reviews using text mining, machine learning, database, and proven software engineering frameworks. Having served over 150K users in research literature screening, the project was successfully spun out into RAYYAN SYSTEMS.



The Arabic Languages Technologies group at QCRI built the Advanced Transcription System (QATS) based on state-of-the-art deep learning technologies that convert speech to text including English and dialectal Arabic. It has been deployed in different organizations including Al Jazeera showing impressive competitive performance. QATS eventually merged with a recent technology startup namely, KANARI AI which provides speech technology solutions for dialectal Arabic and other low-resource languages. This includes automatic speech recognition (ATS), text-to-speech (TTS), and NLP.


Please reach out to us for more information, collaboration, or partnership inquiries.