Saad Saleh

Saad Saleh is Team Lead (Researcher) at the Applied Network and Data Science Research (AN-DASH) lab. He received his Masters and Bachelor degrees in Electrical Engineering from National University of Sciences and Technology (NUST) in 2013 and 2011, respectively. He specializes in computer networks, machine learning, probability theory and social networks. Saad has 5+ years of research and programming experience with Python, C/ C++, Matlab and VerilogHDL as major languages. From 2013-2015, he lead a 9.8 million rupees ICT R&D project with collaboration of Michigan State University (MSU), USA and Yahoo! labs, USA for covert link detection in Instant Messaging Networks. From 2014-2015, he lead a $40,000 project of Microsoft Research (MSR) for predicting road and traffic conditions using smartphone data. Saad also developed a Vehicular Network Coverage algorithm in collaboration with Sungkyunkwan University, Korea from 2013-2014. Currently, he is working on security and privacy of anonymous communication networks, alongwith an analysis and experimentation on software defined networks.


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M.S. Electrical Engineering

School of Electrical Engineering and Computer Science (SEECS)
National University of Sciences and Technology (NUST), Islamabad
Specialization: Communication and Computer Networks
cgpa: 3.95/4.00

NUST logo

B.E. Electrical Engineering

Electrical and Mechanical Engineering College (EME)
National University of Sciences and Technology (NUST), Islamabad
Major Subjects: Communication, Electronics and Computer Networks
Major gpa: 3.90/4.00, cgpa: 3.48/4.00

FBISE logo

Higher Secondary School Certificate (HSSC)

F.G. Sir Syed College, Rawalpindi
Federal Board of Intermediate and Secondary Education (FBISE), Islamabad
Major Subjects: Pre-Engineering Subjects
Marks: 973/1100, Grade-A1

APS logo

Secondary School Certificate (SSC)

Army Public School & College, Rawalpindi
Federal Board of Intermediate and Secondary Education (FBISE), Islamabad
Major Subjects: Mathematics, Physics and Chemistry
Marks: 976/1050, Grade-A1



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[1]. "MuGKeG: Secure Multi-channel Group Key Generation Algorithm for Wireless Networks", Accepted in Springer Wireless Personal Communications, 2017.

[2]. "A Stochastic Model for Transit Latency in OpenFlow SDNs", Published in the Elsevier Computer Networks, Volume 113, Pages 218–229, 11 February 2017. (Impact Factor: 1.446)

[3]. "Analytical Modeling of End-to-End Delay in OpenFlow Based Networks", Published in IEEE Access, 07 December 2016. (Impact Factor: 1.270)

[4]. "Improving QoS of IPTV and VoIP over IEEE 802.11n", Published in the Elsevier Journal of Computers and Electrical Engineering, Volume 43, Pages 92–111, April 2015. (Impact factor = 1.084)


Conference Papers:

[5]. "Post Summarization of Microblogs of Sporting Events", Published in the Proceedings of the 26th International Conference on World Wide Web (WWW) Companion, Perth, Australia, 3-7 April, 2017. (Acceptance Rate = 17%)

[6]. "Sentiment Classification of Tweets using Hierarchical Classification", Published in the 26th IEEE International Conference on Communications (ICC'16), Kuala Lumpur, Malaysia, 23-27 May, 2016.

[7]. "Detecting National Political Unrest on Twitter", Published in the 26th IEEE International Conference on Communications (ICC'16), Kuala Lumpur, Malaysia, 23-27 May, 2016.

[8]. "IM Session Identification by Outlier Detection in Cross-correlation Functions", Published in the 49th Annual Conference on Information Sciences and Systems (CISS), Johns Hopkins University, Baltimore, MD, USA, 18 - 20 Mar, 2015.

[9]. "Breaching IM Session Privacy Using Causality", Published in 33rd IEEE Global Communications Conference (GLOBECOM), Austin, TX, USA, 8 - 12 Dec, 2014.

[10]. "Predicting New Collaborations in Academic Citation Networks of IEEE and ACM Conferences", Published in ASE International Conference on Social Computing (SocialCom), Stanford University, CA, USA, 27 - 31 May, 2014. (Acceptance Rate = 11.9%)

[11]. "Capacity Analysis of Combined IPTV and VoIP Over IEEE 802.11n", Published in 38th Annual IEEE Conference on Local Computer Networks (LCN), October 2013, Sydney, Australia. (Acceptance Rate = 26%)

[12]. "IPTV Capacity Analysis Using DCCP over IEEE 802.11n", Published in 78th IEEE Vehicular Technology Conference (VTC Fall), September 2013, Las-Vegas, USA.

[13]. "Performance Analysis of IPTV and VoIP over WiFi", Poster Presentation at International Symposium on Next-Gen Broadband Networks and Enabling Technologies (in collaboration with UNC Charlotte), April 2013.


MS Thesis:

Saad Saleh, "Capacity Analysis of IPTV over IEEE 802.11n", School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad.


Team Lead (06/2013-Present)
AN-DASH lab, SEECS, NUST, Islamabad


Doing research in networking covering anonymity networks and software defined networks. Leading various projects in collaboration with researchers at University of Cambridge, Michigan State University (MSU), University of Iowa, Rutgers State University, EPFL Switzerland and TATA Research India.

Team Lead (06/2013-06/2015)
Ministry of ICT & SEECS (NUST), Pakistan


Jointly appointed by Ministry of ICT and SEECS (NUST) for a 9.8 million rupees project. Lead a team of 6 engineers towards the compeltion of project "Detecting covert links in Instant Messaging Networks using Flow level log data". Responsibilities included the management of human resources, timely completion of all tasks, preparation of quarterly and progress reports and maintaining an active communication link between ministry of ICT and NUST and collaboration with Yahoo! Labs and Michigan State University (MSU).

Research Assistant (Developer) (11/2011-06/2013)
SEECS, NUST, Islamabad, Pakistan


Worked under the supervision of Dr. Zawar Hussain and Dr. Adeel Baig. Designed and implemented Internet Protocol Television (IPTV) over WiFi. Worked on the development of transport layer protocol for IPTV for intime delivery of real time data. Conducted research on physical layer parameters for transmission of IPTV and VoIP over WiFi. Upto 20% performance gains were achieved compared to preceding strategies.

Researcher (02/2011-07/2011)
EME College, NUST, Islamabad, Pakistan


Conducted research work under the supervision of Dr. Shoab A. Khan. Implemented the concept of various energy levels in Gaussian Minimum Shift Keying (GMSK), currently used by NATO in highly tactical and surveillance devices. Also worked on Stanford University Interim models of channel realization for performance of GMSK signals. Significant performance gains were achieved incomparison to previous state of the art schemes.

Internee (06/2010-07-2010)
Islamabad Electric Supply Company (IESCO), Islamabad, Pakistan


Remained as an Internee in P&I and SST&I departments and gained theoretical and practical knowledge regarding the power distribution and it's control. Visited various 132/11 kV and 220/132 kV grid stations under IESCO supervision and executed responsibilities of "Team Leader". Prepared project reports and guided engineers for efficient power distribution.


Covert link detection in Instant Messaging Networks using Flow log data


Studying an attack on relayed instant messaging (IM) traffic that allows an attacker to infer who's talking to whom with high accuracy. This attack only requires collection of packet header traces between users and IM servers for a short time period, where each packet in the trace goes from a user to an IM server or vice versa. The packet header traces contain information such as timestamps, IP addresses, and port numbers of users and IM servers. Note that packet payloads are encrypted by most IM services; therefore, they cannot be used to infer which users are talking to each other. The specific goal of this attack is to accurately identify a candidate set of top-k users with whom a given user possibly talked to, while using only the information available in packet header traces. It is technically challenging to perform this attack in real-world IM networks due to simultaneous one-to-many communication among users, unequal transmission delays, and out of order or duplicate packets.

Predicting New Collaborations in Academic Citation Networks of IEEE and ACM Conferences


Of key interest in the study of social networks is their evolution with time. Among social networks, collaboration networks have been the subject of significant interest with regards to link prediction. The accurate prediction of the appearance of new collaborations between members of a collaboration network can help accelerate the realization of new synergies, foster innovation and raise productivity. For this study, the authors collect a large data set of publications in 630 conferences of the IEEE and ACM containing more than 257,000 authors, 61,000 papers, capturing more than 818,000 collaborations spanning a period of 10 years. The data set is rich in semantic data that allows the exploration of many features that were not considered in previous approaches.

A Zero-input Cloud-based Application to Measure and Map Road Conditions in Pakistan


We propose to design and develop a smartphone app that detects when it finds itself on a road and measures shocks and vibrations in order to A) map and measure the state of disrepair of roads, B) map the locations of potholes and C) map the locations of speed bumps. The app will not require any input from its user and report measurements to a cloud hosted application which stores data from cellphones and jointly processes the data from all users to obtain a better and more complete estimate of road conditions. This map will be made publicly available via a website that will allow citizens and municipal authorities alike to spot potholes and road segments in need of repair, as well as imbalances in infrastructure maintenance efforts across cities. If the municipality has data of approved and legally constructed speed bumps, it is able to identify all others as illegally constructed.

VNC: Vehicular Network Coverage for Multihop Quality-of-Service Data Delivery


Working over a Vehicular Network Coverage (VNC) algorithm for providing vehicles with the Quality-of-Service (QoS) Data Delivery in vehicular networks using infrastructure nodes, such as Road-Side Units (RSUs) and Relay Nodes. Two multi-hop data delivery directions have been considered i.e. outbound delivery from vehicle to RSU and inbound delivery from RSU to vehicle. We define the QoS of data delivery with the mean and standard deviation of End-to-End data delivery delay. For the given requirements of both outbound and inbound QoS delivery, we need to deploy an appropriate number of RSUs. In this research, we propose the optimal deployment of RSUs.

Post Summarization of Micro-Blogs of Sporting Events


Social networking sites e.g. Facebook, Twitter, LinkedIn are becoming popular among users as they are successful in connecting people and have become a great means of information dissemination, communication and entertainment. Popularity of these services motivates us to study characteristics of online social networks. In 2012, more than 500 million users have subscribed Twitter, generating over 340 million posts and 1.6 billion search queries each day. Due to the enormous number of posts generated by Twitter, it is often difficult to understand what is being said by people on a specific topic. In this research, we perform post summarization of critical events using twitter posts on three sporting events.

On the Quality of Service (QoS) of IPTV and VoIP over IEEE 802.11n


Internet Protocol Television (IPTV) and Voice over Internet Protocol (VoIP) have gained unprecedented growth rates in the past few years. Data rate and high coverage area of IEEE 802.11n motivate the concept of combined IPTV and VoIP over IEEE 802.11n. Transmission of combined IPTV and VoIP over a wireless network is a challenging task. In this research, we deal with the capacity evaluation of combined IPTV and VoIP over IEEE 802.11n. We evaluate the use of Datagram Congestion Control Protocol (DCCP) at transport layer of IPTV and VoIP. We propose a multicast congestion control protocol for efficient data delivery with better quality of service.

Research Interests


  • Computer Networks
  • Machine Learning
  • Social Networks
  • IEEE 802.11 WLANs
  • IPTV, VoIP and Multimedia
  • Wireless sensor networks
  • Optimization Theory
  • Probability theory
  • Cloud Computing


      saad dot saleh at seecs dot edu dot pk 

Online Publications