The LDSA is a central hub of applied data-intensive interdisciplinary analytical research at South Asian University, New Delhi, India. Housed at the Department of Computer Science, LDSA engages affiliated faculty from both Indian and foreign universities to execute cutting edge research to address current challenges and opportunities related to Data Science and Analytics. To advance research, LDSA employs postdoctoral fellows, PhD students in Data Science and Analytics, as well as masters students from affiliated programs in relevant disciplines. The LDSA offers a range of options for both organizations and individuals to get involved, including students mentoring programs, faculty development programs, summer training/workshops, networking events, and more.
The research team at LDSA focuses on applying Data Mining, Machine Learning, and Network Analysis to real-world problems in society and industry. We work on developing novel Data Analytics and Machine Learning techniques, especially for applications in text mining, social network analysis, figurative language detection, sentiment analysis & emotion detection, health informatics, and data-driven cybersecurity. A common pattern in our research is to curate and analyze large-scale data using data mining and machine learning techniques to glean actionable patterns for enabling business intelligence, data-driven economy, and open source intelligence.
LDSA aims to contribute to a number of open-source, open-science, and open-data-resource communities in support of academic research. If you are interested in learning and working on Applied Machine Learning and Complex Networks Analysis, then consider joining our group. Industry, government, and organizations can partner with us to find solutions to their data-centric problems.
Domain-Specific Keyword Extraction Using Joint Modeling of Local and Global Contextual SemanticsMuhammad Abulaish, Mohd Fazil, and Muhammed J. Zaki, ACM Transactions on Knowledge Discovery from Data, Article No.: 70, 2022, pp, 1-30.
DeepSBD: A Deep Neural Network Model With Attention Mechanism for SocialBot DetectionMohd Fazil, Amit Kumar Sah, and Muhammad Abulaish, IEEE Transactions on Information Forensics and Security, Vol. 16, 2021, pp. 4211-4223.
CAT-BiGRU: Convolution and Attention with Bi-directional Gated Recurrent Unit for Self-Deprecating Sarcasm DetectionAshraf Kamal and Muhammad Abulaish, Cognitive Computation, Topical Collection: A Decade on Sentic Computing, Vol. 14, Springer, 2021, pp. 91-109.
A Survey of Figurative Language and its Computational Detection in Online Social NetworksMuhammad Abulaish, Ashraf Kamal, and Mohammed J. Zaki, ACM Transactions on the Web, Volume 14, Issue 1, 2020, pp. 3:1-3:52.
A Hybrid Approach for Detecting Automated Spammers in TwitterMohd Fazil and Muhammad Abulaish, IEEE Transactions on Information Forensics and Security, Volume 13, Issue 11, 2018, pp. 2707-2719.
Dr. M. Abulaish joined the Senior Program Committee (SPC) for CIKM-2022, which is expected to be held in a hybrid format during Oct...
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Dr. M. Abulaish delivered an Expert Talk on "Socialbots Detection in Online Social Networks using Machine Learning Techniques" at th...
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Delivered a Keynote Speech on "Social Network Analytics: Characteristics, Challenges and Research Directions" at the IEEE Computatio...
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Organized by LDSA, Department of Computer Science, South Asian University. It will mainly cover emerging deep learning techniques fo...
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In this training, we will be going over the basics of regression and deep learning. We will start with linear regression, and then c...
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Organized by LDSA, Department of Computer Science, South Asian University in collaboration with Tribhuvan University, Kathmandu, Nepal.
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