Data Mining: COMPUTER SCIENCE LABS---LUMS

Artificial Intelligence and Robotics research at LUMS is primarily focused on Applied Soft Computing, with contributions to the fields of Intelligent Speech and Natural Language Processing, Intelligent System Modelling, Simulation and Controls, Data Mining and Self Rule Generation, Artificial Intelligence, Databases and Aspect Oriented Programming, Neural Networks and Fuzzy Systems, and Robot Design, Planning, and Learning. The Robotics and Intelligent Computing (RICE) lab at SBASSE has also developed two working robots indigenously and plans to develop an automatic assembly line robotic system.

Networks, Information Security, Privacy and Distributed Systems

This research area explores the manner in which computing devices interconnect and the design of innovative computer systems that such interconnection enables. The focus is on the fundamental theory of computer networks and innovative applications of systems especially in the context of the developing world. Areas of research include cloud computing and data centers, mobile and wireless networks, network security., pervasive computing, multimedia communications, access control, data privacy and smart grids. Faculty members working in this area have published their research in the most prestigious conferences and journals including ACM SIGCOMM, IEEE INFOCOM, ACM CoNEXT, ACM IMC, IEEE/ACM Transactions on Networking and ACSAC.

Algorithms and Theory of Computation

Theory of Computation is the formal study of the power as well as limits of computing machines. This is accomplished by the design of efficient algorithms as well as proofs of intractability for various computational problems. Theoretical computer science includes sub-areas such as Graph Theory and Algorithms, Randomized Algorithms, Data Structures, Complexity Theory, Computational Biology, Computational Geometry, Cryptography, Computational Learning Theory and Coding Theory.

DATA MINING

Data Mining involves extracting informative patterns from large scale datasets. The rapid growth in this field is fuelled by increasing demand for automated data analysis and the rise in computation power. The Computer Science Department at SBASSE is currently undertaking research in the realm of parallel algorithms for data mining, efficient message protocols and hardware/software performance benchmarking, machine learning and intelligent information processing. The Department has two fully equipped labs – Knowledge and Data Engineering Lab and High-Performance Computing Lab with hardware and software resources for the development and evaluation of algorithms and computational models for analysis of large structured and semi-structured date-sets.

Software Engineering

Software Engineering is the study and application of engineering to the design, development, and maintenance of software. The focus of the research undertaken by the Software Engineering Lab is in the areas of Software Reengineering, Software Testing and Quality Assurance, Software Engineering for Smart Grids, Formal Verification and Validation, Software Architectures for e-Government initiatives, and Software Engineering for Healthcare Systems. The research output of the Software Engineering group has been disseminated at various top international conferences and journals like ICSE, ICSM, OOPSLA, TSE, TSG, SASO, and ASE, among others in recent years.

Research Computer Vision

Computer Vision focuses on the theoretical aspects as well as practical applications of machines that can ‘see’, that is, extract useful information from an image or video, to carry out certain functions or tasks. Current research in the Computer Vision Lab at SBASSE focuses on applications of this field for developing countries. In this context, recent projects include the development of a crawler for Google Earth that allows for segmentation of nucleated villages in satellite imagery, as well as the development of a low-cost ultrasound training simulator that will allow trainee doctors to practice without relying on real patients and innovative ways to map socio-economic parameters for Pakistan.