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FAST School of Computing Research Groups

FSC > Research

High Performance Computing (HPC) Lab

FAST-NUCES houses an OpenStack based private cloud infrastructure and next generation provisioning frameworks like Kubernetes and Kubeflow. Dr. Muhammad Usman Awais is managing an HPC lab which provides access to the above mentioned infrastructures. Although the scale is not very large, it is good enough for the students to conduct research for their master's theses and Final Year Projects (FYPs). Following major research areas are being explored in the lab

Big Data Lab Establishment

A Big Data lab has been established in Lahore campus. The use of Big Data is becoming a crucial way for leading companies to outperform their peers. In most industries, established competitors and new entrants alike, leverage data-driven strategies to innovate, compete, and capture value. Big Data will help to create new growth opportunities, and also entirely new categories of companies, such as those that aggregate and analyze industry data.

Students of Dr. Usman Awais and Dr. Zareen Alamgir have successfully setup this lab and cluster. In guidance of Dr. Usman Awais an OpenStack Cloud infrastructure is also established. The deployed OpenStack cloud provides Platform as a Service (PaaS) infrastructure.The PaaS enables the students to analyze many different distributed computing technologies, including Data and Compute Clusters and Grids.The initial set up will be used by master thesis students, and students working on their Final Year Projects (FYP). It will allow the students to have a practical exposure to cloud related technologies. A personalized cloud dashboard can also be made accessible over the internet, in future.

Students can access this Hadoop master cluster from other Labs. Now "Big Data" students can access the Hadoop cluster for their assignments, without going to the Big Data Lab.

Following are the students who made considerable efforts to realize the plan of setting up these labs.


Current and Past Projects

·   Fuzzy clustering of mixed mode data in Apache SPARK

·   Exploiting review helpfulness rating on scalable recommendation systems using Apache Spark

·   SP-CURE, a clustering algorithm developed on Apache Spark to cluster gigantic datasets

·   Personalized User Tag recommender

·   for Social Media Photos using Spark

·   Tag Recommender for Spark, a system for recommending user tags for huge datasets.

·   Social Event based recommendation system in distributed environment

·   Distributed Typicality-based Recommendation System for Apache Spark

·   Hybrid Recommendation System using Apache Spark Framework

·   Keyword based personalized Hotel Recommender on Map Reduce.

·   Opinion Mining on Big Data using MapReduce Framework.

·   Deep Packet analysis in Software Defined Networks

·   Distributed algorithms for Machine Learning (kubernetes operators are being used)

·   FRSG to develop a Kubernetes operator

·   Distributed Simulation using Docker ( Kubernetes will be included) 

Recent Publications

GPU Server

To spur the research in the field of Machine Learning, a high fidelity server is made available for the faculty and students at FAST-NUCES. The server is a Dell PowerEdge R740xd2 series server. Using a freely available solution named, the server is accessible to the authorized users over the web. Meaning, users can access it while being at their home. is a docker based solution which allows many users to use the GPU server simultaneously, while allowing users to deploy a software stack of their own choice in their containerized environment. The IT department of FAST-NUCES with the assistance from Dr. Muhammad Usman Awais is able to make it 24/7 available for the users since the begnning of 2020. 

Liberty Lab

Liberty lab aims to put together and apply the knowledge gained from diverse areas of expertise including robotics, embedded systems and artificial intelligence, to engineer out-of-the-box solutions that practically solve the problems faced by the local society. Research is done to make robots that can achieve autonomous behavior. Problems of localization, mapping, navigation and image processing in robots are explored. Control algorithms on ground and air robots are developed to improve the navigation capabilities of such robots. The goal is to make autonomous mobile and industrial robots, and induce learning and long-term autonomy in them. This lab achieves its aims via projects at both graduate and undergraduate levels.

Completed FYPs

Research Areas and Ongoing Projects

Machine Intelligence Group (MInG)

Co-founders consists of Dr. Rauf Baig, Dr. Kashif Zafar and Dr. Usman Shahid. 

Past Projects

Recent Publications

Research Center for Information Management and Cyber Security (CIMACS)

The Center for Information Management and Cyber Security (CIMACS), headed by Dr. Taimur Bakhshi is involved in undertaking research and development in the broad domains of information management, cyber security and computer networking. The center undertakes consultancy, auditing, installation and management work in the following avenues.

Current & Past Projects

·  User behaviour profiling

·  Securing software defined networks

·  Social engineering vulnerabilities

·  Ransomware detection and mitigation

·  Android platform security:

·  Securing the Internet of Things (IoT)

·  Fault-Tolerance in Software Defined Networks

·  Forensic of Things

·  IoT for Smart Cities

Further information about these projects is available on the center website:


Recent Publications

Software Engineering Research Centre (SERC)


Software Research Engineering Centre is dedicated to conducting research and development in various facets of software engineering. The centre has been established to promote theoretical research in the software engineering area, resolve problems faced by the software industry, and help establish software engineering practices in the industry. Through the establishment of the SERC, the University seeks to help and support the local software industry in establishing and improving their processes and practices through continuous feedback and training. SERC aims to achieve these objectives by collecting the industry data to understand productivity, cost, and quality parameters. This will hopefully also help in developing more suitable process and lifecycle models for different types of projects being undertaken by our local industry in the offshore and distributed environment. In the past, this Centre has arranged many seminars and workshops in the software engineering domain to encourage and promote academia-industry collaboration. Current research focuses on areas such as empirical software engineering, software cost estimation, software project management, and requirements engineering.

Past Projects

Recent Publications



Optimization and Data Science (OptiMi'nDS) research group, headed by Dr. Irfan Younas, carries out research and development in Optimization and Data Science related areas. Major research themes in our research group include Evolutionary Computation, Swarm Intelligence, Evolutionary Deep Learning, Multi/Many-objective Optimization, Artificial Intelligence, Data Science, Machine Learning, Natural Language Processing and Information Retrieval.

Solving large scale optimization problems have always been very challenging and demanding. Our research group carries out multi-disciplinary research into mathematical models and intelligent algorithms for a variety of real world optimization, specifically NP-hard problems. The NP-hard problems are very complex with intractably large and highly complex search spaces.

Our research group also works in area of Natural Language Processing (NLP) and Machine Learning. NLP addresses fundamental questions at the intersection of human languages and computer science. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate almost everything in language: web search, advertisement, emails, customer service, language translation, radiology reports, etc.

Research Group Members:

·         Dr. Irfan Younas (Faculty member)

·         Dr. Maryam Bashir (Faculty member)

·         Mr. Muhammad Amir Iqbal (Faculty member & PhD student)

·         Mr. Shakeel Zafar (Faculty member & PhD student)

·         Mr. Qamar Askari (PhD student)

·         Ms. Maria Tamoor (PhD student)

·         Ms. Sadia Marium (PhD student under co-supervision)

·         Ms. Umber Nisar (PhD student)

·         Mr. Asif Ameer (PhD student)

Past and Ongoing Projects:

·         Designing novel Socio-inspired Optimization Algorithms for Global Optimization

·         Developing Transfer Learning Based Classifier System for Image Classification

·         Evolving Deep Neural Networks using Evolutionary Computation

·         Large scale optimization of Assignment, Planning and Scheduling Problems

·         Distributed Large Scale Many Objective Optimization

·         Multi and Many Objective Optimization Algorithms

·         Many Objective Optimization for IoT

·         Learning Regular Expressions using Learning Classifier Systems

·         Solving Large-scale Optimization Problems using Evolutionary Computation and Machine Learning

·         Solving Classification and Learning Problems using Evolutionary Machine Learning

·         Predicting Future News Events and Crimes using Data Science


Recent Publications:


  • * means equal contribution.
  • + means student under supervision.


International Collaborations: