Objectives:

Intelligent decision making is important in area for building computerized decision support systems. The research goals of this group are directed toward understanding and building intelligent decision making models for assisting and supporting decision making in different application areas such as image processing, security and bioinformatics. The fundamental issues that are generally encountered in such models are too many options to choose from and involvement of contradictory decision making criteria. The group is actively engaged in utilizing machine learning methods, such as rough sets and granular computing, in inducing rules for complex decision making. One of the main focus area is three-way decision making, especially when multi-criteria and multi-agents are involved.

Key Projects:

• Development of effective classification technique for malware analysis
• A three-way decision making approach to protein function classification
• Employing game theory in building effective recommender system

International / National MOUs / Partnerships / Associations (formal or informal):

• International Rough Set Society
• Decision-theoretic Rough Set Group (University of Regina)
• Three-way Decision Making Group.

Specialized courses offered by Research Center:

• Rough sets with Applications
• Bioinformatics
• Multimedia and Security

Team Members:

• Dr. Nouman Azam (Dept. of computer science, NUCES, Peshawar)
• Dr. Hafeez Ur Rehman (Dept. of computer science, NUCES, Peshawar)
• Dr. Naveed Islam (Dept. of computer science, NUCES, Peshawar)
• Dr. Mohammad Nauman (Dept. of computer science, NUCES, Peshawar)

Selected Research Publications:

• M. Nauman, N. Azam, J. T. Yao, A Three-way Decision Making Approach to Malware Analysis, Proceedings of 10th International
• Conference on Rough Sets and Knowledge Technology (RSKT'15), Tainjin, China, Nov 20 - Nov 22, 2015, Lecture Notes in Computer Science 9436, Pages 273-284.
• J. T. Yao, N. Azam, Web-based Medical Decision Support Systems for Three-way Medical Decision Making with Game-theoretic Rough Sets, IEEE Transactions on Fuzzy Systems, Vol. 23, No. 1, Pages 3- 15, 2015.
• N. Azam, J. T. Yao, Game-theoretic Rough Sets for Recommender Systems, Knowledge-Based Systems, Vol. 72, Pages 96-107, 2014.
• Benso, Alfredo, et al. "Using gnome wide data for protein function prediction by exploiting gene ontology relationships." IEEE International Conference on Automation Quality and Testing Robotics (AQTR), 2012.
• Islam, Naveed, William Puech, and Robert Brouzet. "A homomorphic method for sharing secret images" Digital Watermarking. Springer Berlin Heidelberg, 121-135, 2009.

pwr.nu.edu.pk/home/nusys/

Objectives:

The NuSyS group at Peshawar has been established to promote research activities at Peshawar Campus in a diverse set of emerging disciplines of well established research areas. The focal strengths of the group lies in wireless and sensor networks, signal processing, smart-grid systems, high performance computing, and computational electromagnetics. Work objectives in these main lines of work are described as below:

• Wireless Sensor Networks: Physical development of sensing devices, development of mac protocols, routing, and localization algorithms.
• Signal Processing: Acoustics and speech processing, Fourier Transforms
• Smart Grids: Development of reliable, flexible, and automated delivery systems.
• High Performance Computing: Development of various tools that exploit high performance promised by graphic processing units for different applications.
• Computational Electromagnetics: Development of simulation tools for micromagnetics at macroscopic time and length scales.

Key Projects:

• Development of OpenCL based multi-dimensional FFT library supporting arbitrary sizes (target platform: CPU, GPU, Mobile Phones)
• Development of Micromagnetic simulation tool (supporting determination of magnetostatic, exchange, and applied field, as well as excitation of magnetostatic spin-waves)

Informal collaborations:

• CADEMA Research Group, Politecnico di Torino, Torino, Italy. Contact: Prof. Carlo Ragusa
• SATO Lab, Waseda University, Tokyo, Japan. Contact: Prof. Takoro Sato (IEEE Fellow)
• State Key Lab of Alternate Electrical Engineering, North China Electric Power University, Beijing, China. Contact: Prof. Zhenyu Zhou.

Specialized courses offered by Research Center:

• Networks and Graph Theory
• Advance Digital Communication
• Detection and Estimation Theory
• Smart Grids
• Advanced Digital Signal Processing
• Parallel and Distributed Computing

Team Members:

• Omar Usman Khan, PhD (Dept of CS, NUCES, Peshawar Campus)
• Khalil Ullah, PhD (Dept of EE, NUCES, Peshawar Campus)
• Muhammad Tariq, PhD (Dept of EE, NUCES, Peshawar Campus … Currently on leave for PostDoc: Princeton University, USA)

Selected Research Publications:

• Freschi F., Giaccone L., Khan O. Ragusa C., Repetto M., Multi-scale analysis of the circuit-field interactions in magnonics experiments, In: 16t Biennial IEEE Conference on Electromagnetic Field Computation, Annecy, France, 25-28 May, 2014
• Freschi F., Giaccone L., Khan O. Ragusa C., Repetto M., Coupling spin waves to circuits through PEEC approach, In proceedings: 9th IET International Conference on Computation in Electromagnetics, p 1-2, April 2014, DOI: 10.1049/cp.2014.0207
• Jinfang Bai, Zhenyu Zhou, Sheng Zhou, Muhammad Tariq , Distributed energy management in smart grid with dominated electricity provider and multiple microgrids, In Power System Technology (POWERCON), 2014 International Conference on, 2014.
• Zhenyu Zhou, Jun Wu, Muhammad Tariq, Zhiheng Liu, Takuro Sato, Performance evaluation of WLAN under impulsive electromagnetic interference in substation, In ICT Convergence (ICTC), 2013 International Conference on, 2013.

Reconfigurable computing, a computer architecture which provides flexibility through features such as field-programmable hardware, is emerging as a promising paradigm of high-performance information processing. We aim to establish the nation's first multidisciplinary research center in reconfigurable high-performance computing, and to support industry and government needs with cooperative, cost-effective research programs and rapid technology transfer. Reconfigurable systems can work for a variety of platforms, from large-scale machines on earth to mission-critical machines in space. Advantages can be realized in performance, power, size, cooling, cost, versatility, scalability, and dependability.

Program Objectives

The MS (Computer Science) comprises course work and research component. It has four ‘core courses’ aimed at strengthening the understanding and competence in computer science fundamentals. The University expects its MS graduates to pursue careers either as ‘Computer Science Faculty Members’ or as ‘Software Development Managers’ in the industry.

Learning Outcomes

• Students will be able to possess advanced knowledge of Computer Science field
• Students will be able to think creatively and critically; to solve non-trivial problems
• Students will be able to use computing knowledge to develop efficient solutions for real life problems
• Students will be able to design solutions and can conduct research related activities

Recommended Courses

The following core courses are recommended to be completed before entering the MS (CS) program.

1. Computer Programming
2. Data Structures
3. Operating Systems
4. Database Systems
5. Analysis of Algorithms
6. Computer Networks
7. Theory of Automata
8. Software Engineering
9. Assembly Lang. / Computer Arch.

A student selected for admission having deficiency in the above stated courses may be required to study a maximum of FOUR courses. These courses must be passed in the first two semesters. The deficiency courses shall be determined by the Graduate Studies Committee before admitting the student.No fee will be charged for studying deficiency courses.A student cannot take MS courses unless all specified deficiency courses have been passed. Typical course load in a semester is four courses. However, NUCES staff cannot register for more than two courses in a semester.A student has the option to pursue MS by undertaking either a 6 credit hour MS Thesis or MS Project, spread over two regular semesters.

Award of Degree

For the award of MS degree, a student must have:

• Passed courses totalling at least 31 credit hours, including all those courses which have been specified as Core courses
• Obtained a CGPA of at least 2.5