Dr. Tahani Baabdullah

Dr. Tahani Baabdullah is a professor of Computer Science at Capitol Technology University. She is an artificial intelligence (AI) and machine learning (ML) research scientist with expertise in deep learning and cybersecurity, as well as federated learning, blockchain integration, and model tuning. In her role, she has delivered scalable AI solutions for fraud and anomaly detection using Python, TensorFlow, and PyTorch, achieving 99% accuracy and reducing false positives. She is known for translating research into impactful, real-world solutions. Her research interests include neural networks, CNNs, generative AI, large language models, and blockchain integration for secure, ethical, fintech, healthcare, and scalable AI applications. 

When she is not teaching, she enjoys spending time in nature and by the water, working out, cooking, shopping, and having fun with family and friends.

An inspirational quote she follows is: "Always give without remembering and always receive without forgetting." - Brian Tracy

Advice that she offers to your students is: Nothing is impossible, stay passionate, work hard, and be patient, and you can achieve anything!

Areas of Expertise:

• Artificial Intelligence & Machine Learning
• Data Mining  
• Predictive Analytics
• Fraud & Anomaly Detection
• Programming Languages
• Cybersecurity 
• Data Security
• Network Security
• FinTech
• Blockchain, IoTs, and CPSs

Biography:

Education

• Doctor of Philosophy in Computer Science, Howard University (2024)
• Master of Science in Electrical Engineering & Computer Science, The Catholic University of America (2019)
• Master of Science in Computer Science, Colorado State University (2009)
• Bachelor of Science in Computer Science, King Saud University (2004)

Research and Publications

• Tahani Baabdullah, Amani Alzahrani, Danda B. Rawat, Chunmei Liu: Efficiency of Federated Learning and Blockchain in Preserving Privacy and Enhancing the Performance of Credit Card Fraud Detection (CCFD) Systems. Future Internet 16(6): 196 (2024).
• Amani Alzahrani, Danda B. Rawat, Tahani Baabdullah, Aeman Almotairi: Assessing User's Credibility to Enhance Deep Learning-Based Misinformation Detection on Social Media. GLOBECOM 2023: 3197-3202.
• Tahani Baabdullah, Danda B. Rawat, Chunmei Liu, Amani Alzahrani, Aeman Almotairi: Analysis of Cardholder Spending Behavior and Transaction Authentication to Enhance Credit Card Fraud Detection. ICMLA 2023: 1144-1149.
• Amani Alzahrani, Tahani Baabdullah, Aeman Almotairi, Danda B. Rawat: A Hybrid Deep Learning Architecture for Misinformation Detection on Social Media. IRI 2023: 199-204. 
• Gunasekaran Manogaran, Tahani Baabdullah, Danda B. Rawat, P. Mohamed Shakeel: AI-Assisted Service Virtualization and Flow Management Framework for 6G-Enabled Cloud-Software-Defined Network-Based IoT. IEEE Internet Things J. 9(16): 14644-14654 (2022).
• Tahani Baabdullah, Danda B. Rawat, Chunmei Liu, Amani Alzahrani: An Ensemble-Based Machine Learning for Predicting Fraud of Credit Card Transactions. SAI (2) 2022: 214-229. 
• Amani Alzahrani, Tahani Baabdullah, Danda B. Rawat: Attacks and Anomaly Detection in IoT Network Using Machine Learning. HCI (38) 2021: 465-472. 
• Tahani Baabdullah, Amani Alzahrani, Danda B. Rawat: On the Comparative Study of Prediction Accuracy for Credit Card Fraud Detection with Imbalanced Classifications. SpringSim 2020: 1-12.