• Prediction of Tumor-Homing Peptide by Fusing Deep Learning with Protein Language Models 

  Waqas Ghafoor, 01-243232-011 (Computer Science, 2026)

  Tumor-homing peptides (THPs) are short amino acid sequences that minimize off-target toxicity while selectively binding to molecular markers on tumor cells to enable targeted drug delivery and diagnostic imaging. The ...
• Prediction of Epigenetic Protein using Deep Learning and Protein Large Language Models 

  Kaleem Ullah, 01-243241-010 (Computer Science, 2026)

  Epigenetic proteins (EPs) are essential in regulating gene activity without altering the DNA sequence. Their role in numerous diseases, including cancer, neurodegenerative, and autoimmune disorders, has rendered them ...
• Data Driven Earthquake Prediction using Intelligent Techniques 

  Muhammad Ibrahim Lodhi, 01-249241-007 (Computer Science, 2026)

  Earthquakes represent one of the most devastating natural hazards, claiming thousands of lives and causing trillions in economic damage annually, particularly in seismically active regions like the Himalayan arc and Pacific ...
• A Deep Learning Based Computational Model for Accurate Prediction of Antigenic Protein 

  Muhammad Iqbal, 01-243231-014 (Computer Sciences, 2025)

  Precise prediction of antigenic proteins (APs) is crucial for accelerating vaccine development, antibody engineering, and immunotherapeutic research. This study presents a novel and effective deep learning framework the ...
• Intrusion Detection of Adaptive Attacks using Federated Learning 

  Laiba Gul, 01-243232-002 (Computer Sciences, 2025)

  The rapid expansion of the Internet of Things (IoT) has significantly increased the cyber-attack surface, exposing infrastructures to adaptive and stealthy threats. Traditional Intrusion Detection Systems (IDS), whether ...
• A Framework for Detection of Fileless and Cryptojacking Malware 

  Muhammad Ahmed Raza, 01-247232-011 (Computer Sciences, 2025)

  The rise of stealthy and evasive mal ware particularly fileless mal ware and cryptojacking poses a significant challenge to traditional security mechanisms that rely on file-based signatures and static analysis. This thesis ...
• Enhancing Pharmacological Interaction Prediction in Otolaryngology Using Computational Methods 

  Muhammad Junaid, 01-243232-004 (Computer Sciences, 2025)

  Drug-Drug Interactions (DDIs) cause major clinical challenges leading to adverse drug reactions, lower the therapeutic value of drugs, and increase the overall healthcare burden, especially in the otolaryngology domain ...
• Anomalies Detection in Smart Building 

  Bushra Khadim, 01-249231-004 (Computer Sciences, 2025)

  Anomaly detection involves identifying data points or patterns that significantly diverge from expected behavior within a system, often due to external disruptions, faults, or uncertainties during operation. In smart ...
• Classification of Functional and Non-functional Software Requirements from User App Reviews 

  Aleena Zainab, 01-243231-001 (Computer Sciences, 2025)

  This research explores the important difference between Functional Software Requirements (FRs) and Non-Functional Software Requirements (NFRs). FRs describe what a software system should do, such as user authentication and ...
• Precision Agriculture: Harnessing ML/DL for Rice Leaf Disease Diagnosis 

  Muhammad Hashim, 01-243222-006 (Computer Sciences, 2025)

  Machine Learning (ML) and Deep Learning (DL), more advanced techniques, are being studied in this particular paper as a method for early recognition and classification of leaf diseases on rice plants only for four common ...
• AI-Driven Insights: Enhancing HR Strategies with Job Change Predictions 

  Umer Ikhlas Sheikh, 01-243222-012 (Computer Sciences, 2025)

  Employee attrition is a significant problem that impacts organizational stability, productivity, and financial performance. High employee turnover generates various far-reaching costs, such as recruitment expenses, training ...
• Intelligent Resource Management Framework Using Context Aware Statistics for B5G Network 

  Muhammad Idrees, 01-243222-007 (Computer Sciences, 2025)

  With the rapid evolution of mobile communication from 1G to 6G, efficient resource management has become essential to meet increasing demands of the networks. Traditional static allocation methods struggle to handle dynamic ...
• AI-Driven for Smart Concrete Bridge Inspection and Maintenance 

  Hafiz Muhammad Ahmad, 01-243222-003 (Computer Sciences, 2025)

  Concrete bridges require timely and accurate defect detection in order to maintain their structural safety, time-consuming, expensive processes often suffer from human errors. Meta-learning is applied to enhance convolutional ...
• Exploring Evolutionary Algorithms for Optimal Features Selection to Detect Anomaly Based Intrusion In IoT 

  Ali Arshad, 01-243231-002 (Computer Sciences, 2025)

  In light of the fast-evolving scenario of the IoT, network security constantly bears immense challenges due to the increasing number of cyber threats and vulnerabilities. Traditional intrusion detection systems use predefined ...
• A Hybrid Model for Sentiment and Emotion Analysis Using GRU-Based RNN And SVM 

  Aqsa Amin, 01-243221-002 (Computer Sciences, 2024)

  The study of understanding emotions and sentiments present in textual data is the focus of the developing area of emotion and sentiment analysis. The inability of modern technology to precisely recognize and comprehend ...
• An Efficient IOMT Based Disease Prediction Model 

  Zarqa Abid, 01-243222-013 (Computer Sciences, 2024)

  Chronic disease is one of the most common causes of death worldwide. Lack of awareness and inability to access medical help lead to complications in such patients. In IoMT (Internet of Medical Things), different sensors ...
• Ordinance Categorization of Cybercrime in Pakistan, Analysis and Detection of Phishing Attacks 

  Asfand Yar, 01-243212-003 (Computer Sciences, 2024)

  This research work is based on the detection of phishing attacks and the analysis of different classifiers. We have proposed a framework that describes different aspects of website content and architecture, such as the ...
• Image Based PE File Detection and Classification 

  Muhammad Mutahhar Abbas, 01-243212-013 (Computer Sciences, 2024)

  The rapid evolution of malware and its increasing complexity necessitate innovative detection and classification methods to ensure robust cybersecurity. Traditional methods, which largely rely on signature-based and heuristic ...
• Sentiment-Based Hybrid Approach for Mental Health Identification from Social Media Posts 

  Sumbal Bano, 01-243221-013 (Computer Sciences, 2024)

  Sentiment analysis and mental health identification are critical areas in natural language processing (NLP) with significant implications for understanding human emotions and psychological states through text. Sentiment ...
• AI-Driven Acne Diagnosis and Dermatologist Referral 

  Ume-I-Habiba, 01-243222-011 (Computer Sciences, 2024)

  Facial Acne is a prevalent skin condition, can have significant economic and psychological effects on those affected, making accurate grading essential for effective treatment. In this study, we introduced a new grading ...

View more