Digital Pakistan Lab is a flagship initiative under NCBC at College of E&ME, NUST Rawalpindi — advancing Industry 4.0, Healthcare, Energy Systems, and Cloud Computing through data analytics, HPC, and AI solutions.
To transform Pakistan into a digitally empowered and innovation-driven nation by enabling industries and institutions to harness cutting-edge cloud, analytics, and HPC solutions.
To provide a customized and secure digital ecosystem for Pakistan's industrial, healthcare, and energy sectors through HPC clusters, indigenous analytics algorithms, and data sovereignty.
Based at College of E&ME, NUST Rawalpindi, DPL is established with PSDP funding under NCBC. We provide secure, scalable, and domain-specific solutions to industry, academia, and government — enabling researchers and developers to augment their algorithms, computing and storage resources.
Our key research areas address Pakistan's national needs through cutting-edge technology and data-driven solutions.
Business process digitization using IoT, RFID, NFC, IIoT, and automation tools. We model and digitize workflows of textile and manufacturing units with deployed automation and process control systems.
Development of Medical Data Decision Support Systems (MDDS) for cancer, cardiac, and diabetic care. EMR-based analytics for ophthalmology with remote monitoring and digital diabetes education.
High-performance simulations, reduced-order modeling, and energy optimization for HVAC and industrial units. Advanced control design and computational fluid dynamics for energy efficiency.
Development of private cloud infrastructure (Azure Stack), dynamic link libraries, mobile agents, and national-level HPC integration connecting HEC, NUST, and international computing clusters.
DPL's layered architecture connects multiple computing clusters — HEC, International, NUST, and Local — through a Hardware Abstraction Cloud Broker. Application-specific and generic plug-in layers serve Energy, Industry 4.0, and Health sectors via web services and mobile agents.
The Medical Decision Support System uses machine learning classifiers on EEG, ECG, and clinical datasets to generate predictive recommendations for medical specialists and patients.
A comprehensive digital healthcare initiative addressing diabetes care through remote registration, medical follow-ups, tele-education services, and flipped model delivery to doorsteps across Pakistan. Leveraging health data from 16,000+ hospitals worldwide and patient monitoring systems generating 86,400+ readings per day.
Modeled and digitized workflows of textile and medical equipment manufacturing units. Automation and process control systems deployed at Crescent Bahuman Limited and Chenab Metallurgy.
MDDS for breast cancer, cardiac, and diabetic diseases completed. EMR analytics piloted in ophthalmology hospitals. Meethi Zindagi healthcare initiative launched.
High performance computations, reduced-order modeling, and control design completed. HVAC controller prototype development underway for industrial energy optimization.
Local cluster and data repository operational. Private cloud and web services infrastructure established connecting NUST, HEC, and international computing resources.
Held at NUST featuring keynote addresses, poster sessions, oral presentations, and project displays. Industrial Advisory & Steering Committee meetings held alongside.
Engagements with Crescent Bahuman Limited (Textiles), National STEM School, Chenab Metallurgy & Foundries for technology transfer and digitization projects.
Collaborating with NUST, CEME, partner NCBC labs, textile and energy companies, and engaging internationally through Big Data & Cloud conferences.
The lab is supported by Team Leads, Business Development Managers, Research Associates, Research Assistants, PhD/MS students, and Technical Staff under NCBC's governance model with oversight from the National Steering Committee (NSC) and Industrial Advisory Board.
Whether you're from industry, academia, or government — DPL offers access to cutting-edge HPC infrastructure, data analytics tools, and cloud computing resources. Let's build Pakistan's digital future together.