PhD (IIT Delhi), Senior Member: IEEE, ACM, and CSI

Sr. Associate Professor
Department of Computer Science
South Asian University, New Delhi-21, India
E-mail: abulaish@ieee.org   abulaish@sau.ac.in

  +91-11-24195148 (direct)  

Biography

Muhammad Abulaish is a Sr. Associate Professor at the Department of Computer Science, South Asian University (SAU), New Delhi, India with over 22 years of experience in Academic and Research. Before joining SAU, he has worked as Full Professor and Head of the Department at Jamia Millia Islamia (A Central University with A++ grade by the NAAC), New Delhi, India. He has also worked as the Head of the Internet Surveillance and Forensics research group at the Centre of Excellence in Information Assurance, King Saud University, Riyadh, KSA.

Abulaish received his Ph.D. degree in Computer Science from Indian Institute of Technology Delhi in 2007. His research interests focus on developing novel data analytics and machine learning techniques, especially for applications in text mining, social network analysis, biomedical informatics, data-driven cybersecurity, and digital forensics. He has over 120 research publications in various international journals, books, and conference proceedings, including seven papers in IEEE/ACM Transactions. He is an Associate Editor of the Social Network Analysis and Mining, Springer. He has served several reputed international conferences including SDM, CIKM, IJCAI-ECAIPAKDD, Web Intelligence, and BIOKDD as TPC member. He has also served WI'19 and WI'20 as a publicity co-chair, and ASONAM'20 as a workshop co-chair. He is also an editorial board member and reviewer of various journals of repute. He is a senior member of IEEE, ACM, and CSI. He is also a life member of ISTE, IETE, and ISCA.

Research Publications

  • Muhammad Abulaish, Mohd Fazil, and Muhammed J. Zaki, Domain-Specific Keyword Extraction Using Joint Modeling of Local and Global Contextual Semantics, ACM Transactions on Knowledge Discovery from Data, 2021 (accepted). (URL) (PDF) (BibTex)

  • Mohd Fazil, Amit Kumar Sah, and Muhammad Abulaish, DeepSBD: A Deep Neural Network Model With Attention Mechanism for SocialBot Detection, IEEE Transactions on Information Forensics and Security, Vol. 16, 2021, pp. 4211-4223. (URL) (PDF) (BibTex)

  • Ashraf Kamal and Muhammad Abulaish, CAT-BiGRU: Convolution and Attention with Bi-directional Gated Recurrent Unit for Self-Deprecating Sarcasm Detection, Cognitive Computation, Topical Collection: A Decade on Sentic Computing, Springer, 2021, pp. 1-20. (URL) (PDF) (BibTex)

  • Muhammad Abulaish, Ashraf Kamal, and Mohammed J. Zaki, A Survey of Figurative Language and its Computational Detection in Online Social Networks, ACM Transactions on the Web, Vol. 14, No. 1, pp. 3:1-3:52, 2020. (PDF) (URL) (BibTex)

Books/Tools/Datasets

  • BiSAL: A Bilingual Sentiment Analysis Lexicon to Analyze Dark Web Forums for Cyber Security (dataset)

  • Ontology Engineering for Imprecise Knowledge Management, LAMBERT Academic Publishing, Germany, ISBN: 978-3-8383-0612-4, No. of Pages: 224, 2009. (PDF) (Source)

  • Exploring Database Systems: a systematic approach to develop database design, implementation and querying skills (to appear).

Recent Activities

  • Delivered an Expert Talk on "Socialbots Detection in Online Social Networks using Machine Learning Techniques" at the Faculty Development Program on Enabling Technologies for Artificial Intelligence, Machine Learning and IOT organized by Department of Computer Engineering, AMU Aligarh under the AICTE Training And Learning (ATAL) scheme during June 21-25, 2021.

  • Delivered a Keynote Speech on "Social Network Analytics: Characteristics, Challenges and Research Directions" at the IEEE Computational Intelligence Society (CIS) Summer School on Emerging Research Trends in Computational Intelligence – Theory and Applications organized by Optimization and Machine Learning Lab, IIT Indore during Nov. 26-29, 2020.

  • Presented two research papers entitled “SentiLangN: A Language-Neutral Graph-Based Approach for Sentiment Analysis in Microblogging Data" and “A Graph-Theoretic Embedding-Based Approach for Rumor Detection in Twitter" at the 18th IEEE/WIC/ACM International Conference on Web Intelligence (WI), Thessaloniki, Greece, Oct. 14-17, 2019.