LETS TALK
DATA

What We Do

Welcome to AI Lab

The AI Lab at ITU leverages the power of AI & Machine Learning for Social Good - unlock the opportunities for positive societal impact - learn the use of ICT for the improved efficiency and sustainability of Smart Cities - implement NLP techniques to infer and analyze human language - process textual information in order to make it accessible for smart decision making - by employing deep learning models that extract the high-level abstract features for classification.

AI Lab aims to realize the impact of cross-domain emerging technologies – specifically on the technical implementation of Artificial Intelligence, Machine Learning & Deep Learning applications for Social Good.

Flagship Project

The lab has been working on several research projects that seek to leverage the power of AI and Machine Learning for Social Good. Among these programs, a key project is the Mukhbir: Real-Time Anonymous Crime Reporting, The AI Lab along with CIPL at ITU has developed a real-time anonymous crime reporting android application named "Mukhbir", which will facilitate the general public to report crimes happening around them anonymously so that relevant security authorities can perform suitable actions accordingly. Mukhbir application can be downloaded via Google play store

Download

Projects

Deep Stylometry and Lexical & Syntactic Features based Author ...


13 (1)
In this paper, we address the problem of author attribution through unsupervised clustering using lexical and syntactic features and novel deep learning based Stylometric model. For this purpose, we download all available 158918 publications accessible till 1 July 2015 from PLOS.org – an open access digital repository of full text publications.

Altmetrics: A new way to measure social impact of scientific literature

altmatrics
In this project we measure the impact of scientific publications by deploying altmetrics indicators using the data from Google Scholar, Twitter, Mendeley, Facebook, Google-plus, CiteULike, Blogs and Wiki To capture the social impact of scientific publications,.

Detecting Target Text related to Algorithmic Efficiency in Full ..


NEW2
In this paper,We are observing an exponential growth of scientific literature since the last few decades. Tapping on the advancement of web-enabled tools and technologies, millions of articles are stored and indexed in the digital libraries. Among this archived scientific literature.

Identifying Important Citations using Contextual Information from Full Text

NEW

In this project we address the problem of classifying cited work into important and non-important to the developments presented in a research publication. This task is vital for the algorithmic techniques that detect and follow emerging research topics and to qualitatively measure the impact of publications in increasingly growing scholarly big data.

A bibliometric study of research activity in ASEAN related to the EU in FP7 priority areas

5 In this project Two relevant recent developments in the area of science and technology (S&T) and related policy-making motivate this article: first, bibliometric data on a specific research area’s performance becomes an increasingly relevant source for S&T policymaking and evaluation.

Small-world phenomenon of keywords network based on complex network

00

This project Based on the network comprised of 111,444 keywords of library and information science that are extracted from Scopus, and taken into consideration the major properties of average distance and clustering coefficients, the present authors …

A bibliometric study of the world’s research activity in sustainable development and its sub-areas using scientific literature

7This project presents a bibliometric study of the world’s research activity in Sustainable Development using scientific literature. The study was conducted using data from the Scopus database over the time period of 2000–2010.

A bibliometric assessment of scientific productivity and international collaboration of the Islamic World in science and technology (S&T) areas

8
 This project analyzes scientific research landscape of the Islamic World in order to access the research productivity, scholarly impact and international collaborations across all Science and Technology (S&T) areas over the time period of 2000–2011, using the Scopus database.

Robust hybrid name disambiguation framework for large databases

9

In many databases, science bibliography database for example, name attribute is the most commonly chosen identifier to identify entities. However, names are often ambiguous and not always unique which cause problems in many fields..

Tapping into intra- and international collaborations of the Organization...

10

This project analyzes the intra- and international collaboration of 11 member states of the Organization of Islamic Cooperation (OIC) in science and technology (S&T) disciplines in the period 1996–2010.by applying various bibliometric indicators along with publication and citation counts and our proposed .

Explaining the Transatlantic gap in research excellence

113

The research has shown that European universities, despite their history and overall scientific production, fail to compete in both quality and volume faced with increasing competition at the top. We also show that in addition to the competition from the USA, there is also the competition from follower countries in Asia

Measuring international knowledge flows and scholarly...

4

This project studies Intra and international collaboration of eleven member states of the Organization of Islamic Cooperation (OIC) in Science and Technology disciplines, by applying various bibliometric indicators, including our newly proposed ACS index that measures the intra collaboration strength of a region.

Knowledge Flows by Citation Context Analysis

ml
In this project we measure the knowledge flows among the countries by analyzing publication and citation data. We argue that not all citations are equally important, therefore, in contrast to existing techniques that utilize absolute citation countsto quantify knowledge …

Analyzing knowledge flows of scientific literature through semantic

In this project we present a new technique to semantically analyze knowledge flows across countries by using publication and citation data using our proposed topic model with distance matrix an extension of classic Latent Dirichlet Allocation model, .

A comprehensive examination of the relation of three citation-based ...

2

Increasing investments in higher education and research, particularly in cutting edge science and technology, coupled with increasing public demand for accountability have driven the need for objective and quantitative measures of research performance. .

ITU Quality Research Rankings for Pakistani Universities & Institutes

itu
The ITU Quality Research Rankings provide the measure of key dimensions of research performance: output, scholarly impact, volume and quality. The publication based indicators measure output; the citation indicators measure scholarly impact; and the h-index combines both.

Creation and the consumption of scientific knowledge across regions.

dfffIn this project we present an innovative research that integrates the creation and the consumption of scientific knowledge across regions. From a human behavior point of view this is significant, since it provides an advanced decision making layer for bringing together researchers from all over the world

The global research benchmarking system

1

To support strategic decision making, universities require research benchmarking data that is sufficiently fine-grained to show variation among specific research areas and identify focused areas of excellence; is objective and verifiable; and provides meaningful comparisons ..  .

Leadership

Saeed Ul Hassan
Director, AI Lab
AI for Social Good, Scientometrics, Altmetrics, Educational Data Science, Applied Machine Learning
WebsiteLinkedInGoogle Scholar
Peter Haddawy
Scientific Advisor
Decision-Theoretic Problem Solving, Medical and Public Health Informatics, AI, Scientometrics
WebsiteLinkedInGoogle Scholar
Raheel Nawaz
Scientific Director
Applied Machine Learning, Scientometrics, AI, Digital Technologies, Information Mining, Industry 4.0
ProfileLinkedInGoogle Scholar
Anna Visvizi
International Collaborator
AI, ICT, Smart Cities, International Political Economy
WebsiteLinkedInGoogle Scholar
Timothy D. Bowman
International Collaborator
Altmetrics, Scholarly Communication, Sociology, Impression Management
WebsiteLinkedInGoogle Scholar
Matthew Shardlow
International Collaborator
NLP, Machine Learning, Lexical Simplification, Text Mining
WebsiteLinkedInGoogle Scholar

Research Team

Iqra Safder
Researcher
Text Mining, Information Retrieval, Machine Learning, Deep Learning
WebsiteLinkedInGoogle Scholar
Anwar Said
Researcher
Social Network Analysis, Representation Learning, Graph Theory
WebsiteLinkedInGoogle Scholar
Hajra Waheed
Researcher
Educational Data Science, Data Science, Learning Analytics
WebsiteLinkedInGoogle Scholar
Farooq Zaman
Researcher

Text Summarization, Text Simplification. Machine Translation, Deep Learning

 
 
WebsiteLinkedInGoogle Scholar
Sehrish Iqbal
Researcher

Educational Data Science, Mining Scientific Researcg, Machine Learning

 
 
WebsiteLinkedInGoogle Scholar
M. Sohaib Khalid
Research Associate

Deep Learning, Computer Vision, Information Retrieval, NLP

 
 
WebsiteLinkedInGoogle Scholar
Hadia Irshad
Research Associate

Deep Learning, Information Retrieval, Big Data, Text Mining

 
 
WebsiteLinkedInGoogle Scholar
Mahrukh
Research Associate

NLP, Deep Learning, Educational Data Mining, Information Retrieval

 
 
WebsiteLinkedInGoogle Scholar
Momin Ali
Research Associate

Deep Learning, Data Mining, Natural Language Processing

 
 
WebsiteLinkedInGoogle Scholar

AI Lab Team

Alumni

Raheem Sarwar
Research Associate
Scientific Data Management, Large-Scale Machine Learning, Scientometrics
WebsiteLinkedInGoogle Scholar
Mubashir Imran
Research Associate
Algorithms, Graph Theory, Data Science, Machine Learning, Information Retrieval
WebsiteLinkedInGoogle scholar
Junaid Sarfraz
Research Associate
Application Development, Data Mining, Information Retrieval, Machine Learning
WebsiteLinkedInGoogle Scholar
Syed Uzair
Research Associate

Scientometrics, Altmetrics, Machine Learning, AI

 
 
WebsiteLinkedInGoogle Scholar
Zunaira Jamil
Research Associate

Scientometrics, Applied Machine Learning, Deep Learning

 
 
WebsiteLinkedInGoogle Scholar
Awais Asghar
Research Associate

Application Development, Data Scrapping and Crawling

 
 
WebsiteLinkedInGoogle Scholar
Imran Aslam
Research Associate

User-Centered Design, Interaction Design, Accessibility, HTML/CSS, Internet Marketing

 
 
WebsiteLinkedInGoogle Scholar
Tajwar Nasir
Intern

Computational Semantics, Cognitive Computing, Algorithmic Complexity

 
 
WebsiteLinkedInGoogle Scholar
Muhammad Junaid Pahat
Research Associate

Data Sciences, Text Mining, Deep Learning, Data Warehouse

 
 
WebsiteLinkedInGoogle Scholar
Hafsa Batool
Research Associate

Machine learning, Deep learning, Data Science, Text Summarization

 
 
WebsiteLinkedInGoogle Scholar
Salman Ahmed
Research Associate

Computer Vision, Deep Learning, Robotics and Embedded Systems

 
 
WebsiteLinkedInGoogle Scholar
Shafaq Malik
Research Associate

Data Science, Big Data Analytics, Machine Learning, AI, Deep Learning

 
 
WebsiteLinkedInGoogle Scholar
Ali Shahid
Research Associate

Information Retrieval, Text Mining, Big Data, Machine Learning

 
 
WebsiteLinkedInGoogle Scholar
Rutaba Niazi
Research Associate

Natural Language Processing, Deep Learning, Big Data

 
 
WebsiteLinkedInGoogle Scholar
Muhammad Rauf Tabassam
Research Associate

Deep Learning, Data Mining, Text Analysis, Machine Learning

 
 
WebsiteLinkedInGoogle Scholar
Muhammad Burhan
Research Associate

Deep Learning, Text Analysis, Data-Driven Business Strategies using Machine Learning

 
 
WebsiteLinkedInGoogle Schoalr
Fatima Farooq Bhatti
Research Associate

Applied Machine Learning, Text Mining, Information Retrieval 

 
 
WebsiteLinkedInGoogle Scholar
Hunain Malik
Research Associate

AWS, Microsoft Azure, Google, Device Configuration and Data Protection 

 
 
WebsiteLinkedInGoogle Scholar

Publications

Journal Articles

  1. Salman Ahmed, Saeed-Ul Hassan, NR Aljohani, R Nawaz, FLF-LSTM: A Novel Prediction System using Forex Loss Function, Applied Soft Compuing in press, 2020. (SNIP: 520, SJR: 1.405, Impact Factor: 5.402, Percentile in Scopus: 93%)
  2. Saeed-Ul Hassan, Naif Radi Aljohani, Nimra Idrees, Raheem Sarwar, Raheel Nawaz, Eugenio Martínez-Cámara, Sebastián Venturae, Francisco Herrera, Predicting literature’s early impact with sentiment analysis in Twitter, Knowledge-based System (in press), 2020. (SNIP: 902, SJR: 1.754, Impact Factor: 5.921, Percentile in Scopus: 97%)
  3. Saeed-Ul Hassan, M Shabbir, S Iqbal, A Said, F Kamiran, R Nawaz, U Saif, Leveraging Deep Learning and SNA approaches for Smart City Policing in the Developing World, International Journal of Information Management, in press, 2020. (SNIP: 3.225, SJR: 1.711, Impact Factor: 5. 063, Percentile in Scopus: 99%)
  4. Saeed-Ul Hassan, S Iqbal, NR Aljohani, S Alelyani, A Zuccala, Introducing the ‘alt-index’ for measuring the social visibility of scientific research, Scientometrics, vol. 123, 1407–1419; Springer, 2020. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  5. D Drongstrup, S Malik, NR Aljohani, S Alelyani, I Safder, Saeed-Ul Hassan, Can Social Media Usage of Scientific Literature Predict Journal Indices of AJG, SNIP and JCR? An Altmetric Study of Economics, Scientometrics, In press; Springer, 2020. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  6. F Zaman, M Shardlow, Saeed-Ul Hassan, N Aljohani, R Nawaz, HTSS: A Novel Hybrid Text Summarisation and. Simplification Architecture, Information Processing & Management, in press, 2020. (SNIP: 2.895, SJR: 1.043, Impact Factor: 3.892, Percentile in Scopus: 96%)
  7. Hajra Waheed, Saeed-Ul Hassan, Naif Radi Aljohani, Julie Hardman, Raheel Nawaz, Salem Alelyani, Predicting Academic Performance of Students from VLE Big Data using Deep Learning Models, Computers in Human Behavior, 104, 2020. (SNIP: 2.245, SJR: 1.711, Impact Factor: 4.306, Percentile in Scopus: 99%)
  8. Saeed-Ul Hassan, Aneela Saleem, Saira Hanif Soroya, Iqra Safder, Sehrish Iqbal, Saqib Jamil, Aljohani, Naif Radi, Raheel Nawaz, Sentiment analysis of tweets through Altmetrics: A machine learning approach, Journal of Information Science, in press, 2020. (SNIP: 1.581, SJR: 0.636, Impact Factor: 2.327, Percentile in Scopus: 90%)
  9. Saeed-Ul Hassan, Naif R. Aljohani, Mudassir Shabbir, Umair Ali, Sehrish Iqbal, Raheem Sarwar, Eugenio Martínez-Cámara, Sebastián Ventura, Francisco Herrera, Tweet Coupling: A Social Media Methodology for Clustering Scientific Publications, Scientometrics, in press; Springer, 2020. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  10. Zainab Mahmood, Iqra Safder, et al, Saeed-Ul Hassan, Deep Sentiments in Roman Urdu Text using Recurrent Convolutional Neural Network Model, Information Processing & Management, in press, 2020. (SNIP: 2.895, SJR: 1.043, Impact Factor: 3.892, Percentile in Scopus: 96%)
  11. R Sarwar, AT Rutherford, Saeed-Ul Hassan, T Rakthanmanon, S Nutanong, Native Language Identification of Fluent and Advanced Non-Native Writers, ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), (SNIP: 2.895, SJR: 0.26, Impact Factor: 791, Percentile in Scopus: 59%)
  12. I Safder, Saeed-Ul Hassan, A Visvizi, T Noraset, R Nawaz, S Tuarob, Deep Learning-based Extraction of Algorithmic Metadata in Full-Text Scholarly Documents, Information Processing & Management, in press, 2020. (SNIP: 2.895, SJR: 1.043, Impact Factor: 3.892, Percentile in Scopus: 96%)
  13. L Liu, W Li, NR Aljohani, MD Lytras, Saeed-Ul Hassan, R Nawaz, A Framework to Evaluate Interoperability of Information Systems – Measuring Maturity of Business Process Alignment, International Journal of Information Management, in press, 2020. (SNIP: 3.225, SJR: 1.711, Impact Factor: 5.063, Percentile in Scopus: 99%)
  14. NR Aljohani, A Fayoumi, Saeed-Ul Hassan, Bot Prediction on Social Networks of Twitter in Altmetrics using Deep Graph Convolutional Networks, Soft Computing, in press, Springer, 2020. (SNIP: 1.292, SJR: 0.62, Impact Factor: 2.784, Percentile in Scopus: 98%)
  15. Saeed Ul Hassan, H Waheed, NR Aljohani, M Ali, S Ventura, F Herrera, Virtual Learning Environment to Predict Withdrawal by Leveraging Deep Learning, International Journal of Intelligent Systems, vol 34, issue 8, 1935-1952, 2019. (SNIP: 2.027, SJR: 1.3, Impact Factor: 7.229, Percentile in Scopus: 94%)
  16. Noor Arshad, Abu Bakar, Saira Hanif Soroya, Iqra Safder, Sajjad Haider, Saeed-Ul Hassan, Naif Aljohani, Salem Alelyani, Raheel Nawaz, Extracting Scientific Trends by Mining Topics from Call for Papers, Library Hi Tech, 2019 (in press) (SNIP: 1.049, SJR: 0.75, Impact Factor: 1.256, Percentile in Scopus: 82%)
  17. Awais, A. Ahmed, Saeed Ul Hassan, Leveraging Big Data for Politics: Predicting General Election of Pakistan using a Novel Rigged Model, Journal of Ambient Intelligence and Humanized Computing, in press, 2019. (SNIP: 1.128, SJR: 0.35, Impact Factor: 1.910, Percentile in Scopus: 81%)
  18. Saeed Ul Hassan; Bowman, T.; Shabbir M.; Akhter, A.; Imran, M., Aljohani. N., “Influential Tweeters in Relation to Highly Cited Articles in Altmetric Big Data”, Scientometrics, vol. 119, issue 1, 281- 493; Springer, 2019. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  19. NR Aljohani, A Fayoumi, Saeed-Ul Hassan, Predicting At-risk students using clickstream data in the Virtual Learning Environment, Sustainability, in press, Springer, 2020. (SNIP: 1.169, SJR: 0.549, Impact Factor: 2.592, Percentile in Scopus: 98%)
  20. Suppawong Tuarob, Sung Woo Kang, Poom Wettayakorn, Chanatip Pornprasit, Tanakitti Sachati, Saeed-Ul Hassan, Peter Haddawy, Automatic Classification of Algorithm Citation Functions in Scientific Literature, IEEE Transactions Knowledge and Data Engineering, in press, 2019. (SNIP: 2.954, SJR: 1.14, Impact Factor: 3.857, Percentile in Scopus: 95%)
  21. A Said, TD Bowman, RA Abbasi, NR Aljohani, Saeed Ul Hassan, R Nawaz, Peter Haddawy, Mining Network-Level Properties of Twitter Altmetrics Data, Scientometrics, In press, 2019. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  22. Saeed-Ul Hassan; Anna V; H. Waheed. The ‘who’ and the ‘what’ in international migration research: data-driven analysis of Scopus-indexed scientific literature, Behavior & Information Technology, in press, 2019. (SNIP: 0.675, SJR: 0.56, Impact Factor: 1.429, Percentile in Scopus: 86%)
  23. I Safder, Saeed-Ul Hassan, Bibliometric-enhanced Information Retrieval: A Novel Deep Feature Engineering Approach for Algorithm Searching from Full-text Publications, Scientometrics, vol. 119, issue 1, 257 – 277; Springer, 2019. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  24. W Iqbal, J Qadir, G Tyson, AN Mian, Saeed-Ul Hassan, J Crowcroft, A Bibliometric Analysis of Publications in Computer Networking Research, Scientometrics, in press; Springer, 2019. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  25. Fouad, Ahmed Mahany, Naif Aljohani, Rabeeh Ayaz, Saeed-Ul Hassan, ArWordVec: efficient word embedding models for Arabic tweets, Soft Computing, in press, Springer, 2019. (SNIP: 1.292, SJR: 0.62, Impact Factor: 2.784, Percentile in Scopus: 98%)
  26. Saeed-Ul Hassan, M Imran, S Iqbal, NR Aljohani, R Nawaz, Deep Context of Citations Using Machine-Learning Models in Scholarly Full-text Articles, Scientometrics, vol. 117, issue, 3, 1645-1662 Springer, 2018. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  27. Waheed, Saeed-Ul Hassan, N. R. Aljohani, M Wasif, A Bibliometric Perspective of Learning Analytics Research Landscape, Behavior & Information Technology, vol. 37, issue 10-11, 941-957; 2018. (SNIP: 0.675, SJR: 0.56, Impact Factor: 1.429, Percentile in Scopus: 86%)
  28. F Sabah, Saeed-Ul Hassan, A Muzzam, S Iqbal, S Soroya, R Sarwar, Scientific Collaboration Networks in Pakistan and their Impact on Institutional Research Performance: A Case Study Based on Scopus Publications, Library Hi Tech, Vol. 37 No. 1, pp. 19-29, 2018. (SNIP: 1.049, SJR: 0.75, Impact Factor: 1.256, Percentile in Scopus: 82%)
  29. Saeed-Ul Hassan, I Safder, A Akram, Kamiran F, A Novel Machine-Learning Approach to Measuring Scientific Knowledge Flows Using Citation Context Analysis, Scientometrics, vol. 116, issue 2, 973–996, Springer, 2018. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  30. Rabeeh Abbasi, Naif Radi Aljohani, F Bawakid, F Saleem, Z Ullah, Aali Daud, Muhammad Aslam, J Alowibdi, Saeed-Ul Hassan, Web Observatory Insights: Past, Current, and Future, International Journal on Semantic Web and Information Systems, In press. (Impact Factor: 1.833)
  31. Saeed-Ul Hassan, M Imran, U Gillani, NR Aljohani, TD Bowman, “Measuring Social Media Activity of Scientific Literature: An Exhaustive Comparison of Scopus and Novel Altmetrics Big Data”, Scientometrics, vol. 113, issue 2, 1037-1057; Springer, 2017. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  32. Haddawy, P., Saeed-Ul Hassan, Lee, IB, Craig, A., “Uncovering Fine-Grained Research Excellence: The Global Research Benchmarking System”, Journal of Informetrics, 11, issue 2, 389-406, Elsevier, 2017. (SNIP: 1.815, SJR: 1.952, Impact Factor: 3.879, Percentile in Scopus: 92%)
  33. Bonaccorsi, A., Cicero, T., Haddawy, P., Saeed-Ul Hassan, “The solitude of stars. An analysis of the distributed excellence model of European universities”, Journal of Informetrics, 11, issue 2, 435-454, Elsevier, 2017. (SNIP: 1.815, SJR: 1.952, Impact Factor: 3.879, Percentile in Scopus: 92%)
  34. Bonaccorsi, A., Cicero, T., Haddawy, P., Saeed-Ul Hassan, “Explaining the transatlantic gap in research excellence”, Scientometrics, vol. 110, issue 1, 217-241; Springer, 2017. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  35. M Qasim, Saeed-Ul Hassan, NR Aljohani, M Lytras, “Human Behavior Analysis in the Production and Consumption of Scientific Knowledge across the Regions: A case study based on publications and citations data indexed in Scopus”, Library Hi Tech, vol. 35 Issue: 4, pp.577-587, Emerald, 2017. (SNIP: 1.049, SJR: 0.75, Impact Factor: 1.256, Percentile in Scopus: 82%)
  36. Haddawy, P., Saeed-Ul Hassan, Asghar, A., Amin, S., “A Comprehensive Examination of the Relation of Three Citation-Based Journal Metrics to Expert Judgment of Journal Quality”, Journal of Informetrics: vol. 10, issue 1, 162-173, Elsevier, 2016. (SNIP: 1.815, SJR: 1.952, Impact Factor: 3.879, Percentile in Scopus: 92%)
  37. Saeed-Ul Hassan, R. Sarwar “Tapping into Intra and Int’l Collaborations of OIC States across Science and Technology (S&T) Disciplines”, Science and Public Policy: vol. 43, issue 5, 690-701; Oxford Journals, 2015. (SNIP: 0.753, SJR: 0.7, Impact Factor: 1.575, Percentile in Scopus: 73%)
  38. Sarwar, Saeed-Ul Hassan, “A bibliometric assessment of scientific productivity and international collaboration of the Islamic World in science and technology (S&T) areas”, Scientometrics: vol. 105, issue 2, 1059–1077; Springer, 2015. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  39. Saeed-Ul Hassan, and P. Haddawy, “Analyzing Knowledge Flows of Scientific Literature through Semantic Links: A Case Study in the Field of Energy”, Scientometrics: vol. 103, issue 1, 33-46; Springer, 2015. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  40. Ibrar Hussain, Ling Chen, Hamid Turab Mirza, Gencai Chen, Saeed-Ul Hassan, “Right mix of speech and non-speech: hybrid auditory feedback in mobility assistance of the visually impaired”, Universal Access in the Information Society: vol. 14, issue 4, 527–536; Springer, 2015. (SNIP: 1.380, SJR: 0.35, Impact Factor: 0.92, Percentile in Scopus: 63%)
  41. J Zhu, Saeed-Ul Hassan, HT Mirza, Q Xie, “Measuring Recent Research Performance for Chinese Universities Using Bibliometric Methods”, Scientometrics, vol. 101, issue 1, 429–443; Springer, 2014. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  42. Saeed-Ul Hassan, P. Haddawy, J. Zhu, “A Bibliometric Study of the World’s Research Activity in Sustainable Development and its Sub-areas using Scientific Literature”, Scientometrics, vol. 99, issue 1, 549–579; Springer, 2014. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  43. Jia Zhu, Yi Yang, Qing Xie, Liwei Wang, Saeed-Ul Hassan, “Robust hybrid name disambiguation framework for large databases”, Scientometrics, vol. 98, issue 3, 2255-2274; Springer, 2014. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  44. Saeed-Ul Hassan, and P. Haddawy, “Measuring International Knowledge Flows and Scholarly Impact of Scientific Research”, Scientometrics: vol. 94, issue 1, 163–179; Springer, 2013. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  45. Zhu, Saeed-Ul Hassan, P. Haddawy, “Small-World Phenomenon of Keywords Based on Complex Network”, Scientometrics, vol. 97, issue 2, 435–442; Springer, 2013. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)
  46. Saeed-Ul Hassan, P. Haddawy, P. Kuinkel, A. Degelsegger, and C. Blasy, “A Bibliometric study of research activity in ASEAN related to the EU in FP7 priority areas”, Scientometrics, vol. 91, issue 3, 1035–1051; Springer, 2012. (SNIP: 1.439, SJR: 1.95, Impact Factor: 2.770, Percentile in Scopus: 94%)

 

 Conference Papers

  1. Saeed-Ul Hassan, S Iqbal, M Imran, NR Aljohani, R Nawaz “Mining the Context of Citations in Scientific Publications”, 20th International Conference on Asia-Pacific Digital Libraries (ICADL), Hamilton, New Zealand, 2018. (Core A)
  2. Saeed-Ul Hassan, S Iqbal, M Imran, NR Aljohani, R Nawaz, “Quality Classification of Scientific Publications Using Hybrid Summarization Model”, 20th International Conference on Asia-Pacific Digital Libraries (ICADL), Hamilton, New Zealand, 2018. (Core A)
  3. Saeed-Ul Hassan, Akram, A, P. Haddawy, “Identifying Important Citations using Contextual Information from Full Text”, IEEE/ACM Joint Conference on Digital Libraries (JCDL), Toronto, Ontario, Canada, 2017. (Core A*)
  4. Saeed-Ul Hassan, M Imran, T Iftikhar, I Safder, M Shabir, “Deep Stylometry and Lexical & Syntactic Features based Author Attribution on PLOS Digital Repository”, 19th International Conference on Asia-Pacific Digital Libraries (ICADL), Bangkok, Thailand, 2017. (Core A)
  5. I Safer, J Sarfraz, Saeed-Ul Hassan, M Ali, S Tuarob, “Detecting Target Text related to Algorithmic Efficiency for Scholarly Big Data using Recurrent Convolutional Neural Network Model”, 19th International Conference on Asia-Pacific Digital Libraries (ICADL), Bangkok, Thailand, 2017. (Core A)

 

Short papers, Workshops, and Poster Proceedings

  1. D Henriksen, S Malik, Saeed-Ul Hassan, Altmetrics Study of Economics”, 17th International Conference on Scientometrics & Informetrics (ISSI), Rome, Italy, 2019.
  2. I Safder, Saeed-Ul Hassan “DS4A: Deep Search System for Algorithms from Fulltext Scholarly Big Data”, International Conference on Data Mining Workshops (ICDMW), Singapore, 2018
  3. Saeed-Ul Hassan, Safder, I. Naif, R “AI cognition to Search for Relevant Knowledge from Scholarly Big Data using Multilayer Perceptron and RCNN Model”, The World Wide Web (WWW) in Cognitive Computing Track, Lyon, France, 2018.
  4. Saeed-Ul Hassan, M Imran, A Zuccala, “Alt-Index: A proposed Index for measuring the Social Activity of Scientific Research”, 23rd International Conference on Science and Technology Indicators (STI), Leiden, The Netherlands, 2018.
  5. M Imran, A Akhtar, A Said, I Safder, Saeed-Ul Hassan, N. R Aljohani, “Exploiting Social Networks of Twitter in Altmetrics Big Data”, 23rd International Conference on Science and Technology Indicators (STI), Leiden, The Netherlands, 2018.
  6. I Safder, H Batool, Saeed-Ul Hassan “Deep Feature Engineering using Full-text Scholarly Big Data: An Improved Information Retrieval Model”, 20th International Conference on Asia-Pacific Digital Libraries (ICADL), Hamilton, New Zealand, 2018.
  7. A Bakar, Iqra Safder, Saeed-Ul Hassan, “Mining Algorithmic Complexity in Full Text Scholarly Documents”, 20th International Conference on Asia-Pacific Digital Libraries (ICADL), Hamilton, New Zealand, 2018.
  8. A Bakar, N Arshad, Iqra Safder, Saeed-Ul Hassan, “Mining Scientific Trends Based on Topics in Conference Call for Papers”, 20th International Conference on Asia Pacific Digital Libraries (ICADL), Hamilton, New Zealand, 2018.
  9. Saeed-Ul Hassan, Akram, A., Asghar, A., Naif, A. ” Measuring Scientific Knowledge Flows by Deploying Citation Context Analysis using Machine Learning Approach on PLoS ONE Full Text”, 16th International Conference on Scientometrics & Informetrics (ISSI), Wuhan, China, 2017.
  10. Saeed-Ul Hassan, P. Haddawy “Tapping into Scientific Knowledge via Semantic Links”, 15th International Conference on Scientometrics & Informetrics (ISSI), Istanbul, Turkey, 2015.
  11. Saeed-Ul Hassan, P. Haddawy “Semantic Analysis of Knowledge Flows using Scientific Literature”, 19th International Conference on Science and Technology Indicators (STI), Leiden, The Netherlands, 2014.
  12. Haddawy, Saeed-Ul Hassan, “A Comparison of Three Prominent Journal Metrics with Expert Judgement of Journal Quality”, 19th International Conference on Science and Technology Indicators (STI), Leiden, The Netherlands, 2014.
  13. Saeed-Ul Hassan, P. Haddawy, P. Kuinkel, and S. Sedhai., “A Bibliometric Study of Research Activity in Sustainable Development”, 13th Conference of the International Society for Scientometrics and Informetrics (ISSI), Durban, South Africa, pp. 996-998, 2011.
  14. Saeed-Ul Hassan, and R. Ichise, “Discovering Research Domains Using Distance Matrix and Co-Authorship Network”, SIAM International Conference on Data Mining (SDA), vol. 3, Sparks, Nevada, United States, pp. 1252-1257, 2009.

 

Technical Reports

  1. Saeed-Ul Hassan, “Research Landscape of Pakistan”, MIT Technology Review Pakistan”, vol. 2, 2016.
  2. Saeed-Ul Hassan, P. Haddawy, P. Kuinkel, A. Degelsegger, and C. Blasy, “Technical Report: Analysing ASEAN-EU research collaboration”, vol. 2012, no. 22-05-2012: UNU, pp. Science, Technology and Society, 2012.
  3. Saeed-Ul Hassan, and R. Ichise, “Discovering Research Themes of Institutes’ Research Work”, Information Processing Society in Japan Special Interest Group Technical Report, vol. 2012-ICS-165, issue 1, 2012.
  4. Haddawy, Saeed-Ul Hassan, P. Kuinkel and S. Sedhai. “Technical Report: Analyses of Research strengths of SEA countries for SEA-EU-NET under Task 4.9 Bibliometric Analysis of S&T strengths in Southeast Asia in Transport, Social Sciences, Security and Space”, European Commission: Science & Innovation Section, Project SEA-EU-NET, United Kingdom, 2012.
  5. Haddawy, Saeed-Ul Hassan, P. Kuinkel and S. Sedhai. “Technical Report: Analyses of Research strengths of SEA countries for SEA-EU-NET under Task 4.9 Bibliometric Analysis of S&T strengths in Southeast Asia in Health, ‘Food, Agriculture and Biotechnology’, Environment, ICT, Energy, Nanotechnology and Industrial Technologies”, European Commission: Science & Innovation Section SEA-EU-NET, 2011.

 

Book Chapters

  1. Izza Afrab, Saeed-Ul Hassan, Syeda Amna Hassan, Waqas Rana, “Pakistan’s Role in the New Silk Route: Belt and Road Initiative”, The New Silk Road leads through the Arab Peninsula: Mastering Global Business and Innovation, Emerald Publishing, 2018
  2. Saeed-Ul Hassan, P. Haddawy, L. Inn Beng, “Higher Education in Asia: Expanding Out, Expanding Up”, Looking for Research Excellence in the Right Places, David W. Chapman and Chiao-Ling Chien (Eds.), UNESCO Institute for Statistics, Montreal, Canada, 2014.
  3. Haddawy, Saeed-Ul Hassan, P. Kuinkel, and S. Sedhai., “Research strengths of ASEAN countries”, Spotlight on: Science and Technology Cooperation Between Southeast Asia and Europe, A. Degelsegger, and C. Blasy (Eds.): Centre for Social Innovation (ZSI), Linke Wienzeile, Vienna, Austria, 2011.

Fundings

  1. Big Data and Cloud Computing Lab; Funding agency: Planning Commission of Pakistan, $530,000 – (Role: Co-PI), 2018 – 2021.
  2. Catching data-driven cheating: Machine learning detection of falsified immunisation e-records, Gates Foundation, Grand Challenges Explorations Round 21, $100,000 – (Role: PI from Pakistan side), 2020 – 2021.
  3. Beyond Data Collection: Bringing Actionable Insights to Immunisation Supervisors, Gates Foundation, Grand Challenges Explorations Round 21, $100,000 – (Role: PI from Pakistan side), 2020 – 2021.
  4. An AI Based Automatic Urdu Plagiarism Detection Tool for Academia Using Deep Learning and Big Data. Funding agency: NRPU (HEC), $50,000 – (Role: Co-PI). 2019 – 2021.
  5. Automated Citation Analyzer (ACA): a tool to identify meaningful citations among scholarly big data by developing new generation sentiment analyses and machine learning techniques. Funding agency: NRPU (HEC), $25,000 – (Role: PI). 2018- 2020.
  6. Advocacy and Community Empowerment Campaign: “Building partnerships for Hemophilia awareness and treatment provision”; Funding agency: Novo Nordisk Hemophilia Foundation, Switzerland, $50,000 – (Role: PI), 2017- 2019
  7. ITU Quality Research Rankings: ITU’s funded project to produce University Rating System to compare research performance of Pakistani universities across 250 niche disciplines, Data provider: Web of Science, Funded by ITU seed fund, $25,000 – (Role: PI), 2015- present. URL: http://rankings.itu.edu.pk
  8. Dragon – Sustaining Technology and Research (EU-China Collaboration): This project aims to assess the current ranking of the People’s Republic of China in a set of research fields and identifying areas of common interest, UNU-IIST – (Role: Technical Lead), 2013–2015.
  9. UNESCO UIS – Higher Education, Science and Technology in East and South Asia: This project aims to closely investigate the development of higher education in a group of middle-income countries in East and South Asia that can provide valuable lessons to other countries, UNESCO – (Role: Technical Lead), 2012– 2013.
  10. Global Research Benchmarking System (GRBS): A United Nations backed project which provides objective data and analytics to help universities to benchmark their research activities in traditional subject areas and in Sustainable Development for the purpose of strengthening the quality and increasing the impact of research, UNU-IIST, (Role: Technical Lead), 2011.
  11. Alternative University Appraisal (AUA): An initiative of Hokkaido University Japan to create a learning community among universities in Asia-Pacific region engaged in Education for Sustainable Development, Hokkaido University, Japan, (Role: Technical Lead), 2010 – 2012.

Contact