AI and NLP Research Group

1. Introduction:

AI and NLP research Group is dedicated in advancing applied research in Artificial Intelligence, Machine Learning, Natural Language Processing, and Generative AI. The research group  explores cutting-edge technologies including  Large Language Models (LLMs), Computer Vision, Data mining and Recommendation Systems to solve real-world problems and drive innovation. Our mission is to conduct impactful research in AI that contribute to technological advancements and societal benefit.

2. Group Members:

3. Projects

	AI based early GDM Prediction lack of region-specific data hampers early prediction and intervention efforts for GDM, impacting maternal and neonatal health for Pakistan. The project aims to bridge this knowledge gap by collaborating with Shifa International Hospital, a major tertiary care facility with expertise in catering to Pakistan’s diverse demographic landscape. The research focuses on developing an AI-based GDM screening and prediction platform. The objective is to improve maternal and neonatal health outcomes by providing accurate, personalized risk assessments and interventions for GDM.
	Domain Specific Large Language Model One-fit-for-All LLMs generally do not meet the requirements of large enterprises dealing with highly domain specific data. The projects developed a complete pipeline to generate instruction data set and then finetune Domain Specific LLM using Parameter Efficient Fine-tuning. The output model is quantized to enable inference on single GPU with 24GB RAM
	Health informatics and Disease Predication Develop Mathematical Model for Predictive analysis of Vector borne infectious disease. Major modules include descriptive dashboard depicting details disease trends and a predictive dashboard to simulate disease forecasting based on machine learning models.
	Data Dialogue A web-based tool that simplifies user-database interactions. It enables users to ask database queries in natural language, translate them into structured SQL commands, and execute them in the backend. Results is presented in natural language and can be visualized
	Anomaly Detection for Surveillance Videos A smart surveillance system with anomaly detection uses computer vision and machine learning to identify unusual activities or events in a monitored environment
	Smart Visual Alert System Edge computing device enable Deaf and Hard of Hearing (DHH) individuals to become aware of their surrounding by generating visual/ sensory/ textual alarms through AI-based sound classification
	VioDet : Violence Detection in Videos VioDet is a modern AI-based video violence detection mechanism that uses deep learning to automatically detect violent content in videos and consequently, flag them as either violent or non-violent.

4. Research Assistants

• Muhammad Rayyan (BSSE 27)
• Muhammad Usman (BSSE 27)
• Ali (BSSE 27)

5. PhD Students

3. Publications

• Ahmed, N. Iltaf, R. Latif, N. S. M. Jamail and Z. Khan, “Dual Modality Reverse Reranking (DM-RR) Based Image Retrieval Framework,” in IEEE Open Journal of the Industrial Electronics Society, vol. 5, pp. 886-897, 2024.
• Mubashir Munaf, Hammad Afzal, Khawir Mahmood, and Naima Iltaf. 2024. Low Resource Summarization using Pre-trained Language Models. ACM Trans. Asian Low-Resour. Lang. Inf. Process, 2024.
• Khan, Z., Gwak, J., Iltaf, N., “RPf-GCNs: reciprocal perspective driven fused GCNs for rumor detection on social media,” Journal of Big Data, 2024.
• Anwar, H. Afzal, N Iltaf, S. Kadry, and J. Kim. “Fuzzy ensemble of fined tuned BERT models for domain-specific sentiment analysis of software engineering dataset.” Plos one 19, 2024.
• Ahmed, Z. Khan, Z. Khan, N. Iltaf, Moongu Jeon, “Advanced Multi-Model Deep Learning Approach for Content-Based Image Retrieval” Proceedings of the Korean Information Science Society, Busan, Korea.
• Anwar, Z., Afzal, H., Ahsan, A., Iltaf, N. & Maqbool, A. (2023). A novel hybrid CNN-LSTM approach for assessing StackOverflow post quality. Journal of Intelligent Systems, 32(1), 20230057.
• Zainab, H. Afzal, T. Al-Shehari, M. Al-Razgan, N. Iltaf M. Zakria, H. Abbas, M. Javed and R. Nawaz,  “Detection and Classification of Temporal Changes for Citrus Canker Growth Rate Using Deep Learning,” in IEEE Access, vol. 11, pp. 127637-127650, 2023
• I khlaq Ahmed, Iltaf, Zafran Khan, Usman Zia, “Deep-view linguistic and inductive learning (DvLIL) based framework for Image Retrieval”, Information Sciences, Sept 2023 (ISI Impact factor 8.233)
• R Khan, Iltaf, R Latif, NSM Jamail  ,“CrossDomain Recommendation based on MetaData using Graph Convolution Networks”, IEEE Access,Aug 2023 (ISI Impact factor: 3.476)
• Ramsha Saeed, Hammad Afzal, Sadaf Abdul Rauf, Iltaf ,“Detection of Offensive Language and ITS Severity for Low Resource Language”, ACM Transactions on Asian and Low-Resource Language Information Processing, 2023. (ISI Impact factor:1.471)
• Saddaf Rubab, Iltaf , “S-RAP: Relevance Aware QoS Prediction in Web Services and User Contexts” Knowledge and Information Systems (IF : 3.205) – 2022
• Ramsha Saeed, Saddaf Rubab, Zaki Murtaza, Haider Abbas, Iltaf, A Framework to Predict Early News Popularity Using Deep Temporal Propagation Patterns ,Expert Systems “With Applications (IF: 5.452) -2022
• Zafran Khan, Muhammad Ishfaq Hussain, Iltaf, Joonmo Kim and Moongu Jeon, CONEXTUAL MATRIX FACTORIZATION FOR HYBRID RECOMMENDER SYSTEM, Applied Soft Computing. (ISI Impact factor: 5.472)
• Ch MM, Riaz MM, Iltaf, Ghafoor A, Nuwayrah JS. Shift Invariant Discrete Wavelet Transform Based Sparse Fusion of Medical Images. Signal, Image and Video Processing. August 2021 (ISI Impact factor: 2.157)
• Sajid Hussain, Hammad Afzal, Ramsha Saeed, Iltaf,and Mir Yasir Umair, Pharmacovigilance with Transformers: A Framework to Detect Adverse Drug Reactions using BERT Fine-Tuned with FARM, Computational and Mathematical Methods in Medicine, vol. 2021, Article ID 5589829, 12 pages, 2021. (ISI Impact factor:2.238)
• Zainub Mumtaz , Mehreen Afzal1 , Waseem Iqbal , Waqas Aman , Iltaf,” Enhanced metamorphic techniques – A case study against Havex malware,” IEEE Access, August 2021(ISI Impact factor:3.367)
• Syed Wasif Abbas Hamdani , Abdul Waheed Khan, Iltaf, Javid Iqbal Bangash, YawwarAbbas Bangash,Asfandyar Khan, “Dynamic Distributed Trust Management Scheme for the Internet of Things”,TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES August 2020 . (ISI Impact factor 0.806)
• Khan, N. Iltaf, H. Afzal, H.Abbass, “Deep Semantic based Topic Driven Hybrid Recommender System “,Computer Communications (April 2020)(ISI Impact factor: 3.167)
• M .Iqbal, M. Riaz, Iltaf, A. Ghafoor, “A Multifocus Image Fusion using High level DWT Components and Guided Filter”, Multimedia Tools and Applications Jan 2020 (ISI Impact factor: 2.757)
• Farooq, M. Riaz, A. Ghafoor, N. Iltaf, “Pulse rate Extraction based on Local area motion Magnification”, Measurement (ISI Impact factor:3.927)
• Khan, N. Iltaf, H. Afzal, H. Abbass, “Enriching Non Negative Matrix Factorization with Contextual Embeddings for Recommender Systems “, Neurocomputing 2019 (ISI Impact factor: 5.719)
• N. Sukhia , A. Ghafoor, M. M. Riaz and N. Iltaf ,” Automated Acute Lymphoblastic Leukemia Detection System using Microscopic Images”, IET Image Processing. 2019 (ISI Impact factor: 1.995).
• N. Sukhia , M. M. Riaz, A. Ghafoor and N. Iltaf ,Content-Based Histopathological Image Retrieval using Multi-Scale and Multichannel Decoder based LTP, Biomedical Signal Processing & Control.2019 (ISI Impact factor: 3.880)
• Javed, H. Afzal, F. Arif, N. Iltaf, H. Abbas, W. Iqbal, ATSWoTS: Context Aware Trustworthy Social Web of Things System, Sensors 2019, vol19, pp3076. (ISI Impact factor: 3.756)
• M .Iqbal, M. Riaz, Iltaf, A. Ghafoor, “Weighted Image Fusion using Cross Bilateral Filter and Non-subsampled Contourlet Transform”, Multidimensional Systems & Signal Process (MULT), pp 1–12.2019 (ISI Impact factor: 2.030)
• Iqbal, M. Riaz, N. Iltaf, A. Ghafoor ,“Magnetic Resonance and Computed Tomography Image Fusion using Saliency Map and Cross Bilateral Filter”, Signal, Image and Video Processing 2019, pp 1–8 (ISI Impact Factor: 2.157)
• Anwar, N. Iltaf, H. Afzal, “A Hybrid Framework to integrate Content Embeddings in Recommender Systems for Cold Start Items”, Journal of Computational Science, Elsevier 2018, vol 29, pp 9-18. (ISI Impact factor:3.976)
• Farooq, M. Riaz, A. Ghafoor, N. Iltaf, “An Efficient Eulerian Video Magnification Technique for Micro-biology Applications”, Radioengineering 2017, vol 26(1), pp 316-322 (ISI Impact factor:0.951 ).
• N. Sukhia , M. M. Riaz, A. Ghafoor and N. Iltaf, “Overlapping White Blood Cells Detection based on Watershed Transform and Circle Fitting”, Radioengineering 2017, vol26(4), pp 1177-1181 (ISI Impact factor:0.951 ).
• Jabeen, M. Riaz, Iltaf, A. Ghafoor, “Image Contrast Enhancement using Weighted Transformation Function”, IEEE Sensors Journal, 2016, vol 16(20), pp 7534 -7536 (ISI Impact factor : 3.301).
• N. Iltaf, A. Ghafoor, U. Zia and M. Hussain, “An Effective Model for Indirect Trust Computation in Pervasive Computing Environment”, Wireless Personal Communications, 2014, Vol 75( 3), pp 1689–1713.(ISI Impact factor :1.671).
• N. Iltaf, A. Ghafoor and U. Zia, “A Mechanism for Detecting Dishonest Recommendation in Indirect Trust Computation ”, EURASIP Journal on Wireless Communication and Networking, 2013, vol 189. (ISI Impact factor :1.408).
• N. Iltaf, A. Ghafoor and M. Hussain, “Modelling Interaction Using Trust and Recommendation in Ubiquitous Computing Environment”, EURASIP Journal on Wireless Communication and Networking, 2012, vol 119 (ISI Impact factor : 1.408).