Cybersecurity and Networks
Generating Reliable, Safe Systems
Our research expertise spans applications and frameworks, using numerical methods, algorithm refinement, and analytics to keep large-scale networks effective and safe for users. We employ cutting-edge machine learning and deep learning models to counter adversarial attacks and malware, simulating real-world attacks, and showcasing effectiveness against attacks on authentic user data. Below is a rotating selection of our standout investigators in these fields.
○ Recent News and Highlights
○ Research Strength: Ethical Technology
Featured Faculty
Shih-Yu Chang
Assistant Professor of Applied Data Sciences
Tensor Data Processing, Wireless Networking, Physical Layer Security, Random Tensors
ORCID: 0000-0002-3576-0021
Mohammad Masum
Assistant Professor of Applied Data Science
Machine Learning, Deep Learning, AI, Tiny Machine Learning, Ethics in AI, Health Informatics,
Cybersecurity, Natural Language Processing, Large Language Processing
ORCID: 0000-0001-9974-6950
Melody Moh
Professor of Computer Science
Cloud Computing, Mobile Networks, Security and Privacy in Cloud and Networks, Machine
Learning Applications in Cloud and Networks
ORCID: 0000-0002-8313-6645
Robert Morelos-Zaragoza
Professor of Electrical Engineering
Error Correcting Codes, Wireless Communication, Software Radio, Belief Propagation,
Decoding Algorithms
ORCID: 0000-0002-2425-1694
Younghee Park
Associate Professor of Computer Engineering
Network Security, Self-driving security, IoT Security, Blockchain Security
ORCID: 0000-0003-0651-2384
Benjamin Reed
Assistant Professor of Computer Engineering
Operating Systems, Networking, Distributed Systems, and Internet Services for Disconnnected
Regions
ORCID: 0000-0002-8620-0331
Xiao Su
Professor of Computer Engineering
Computer Networking, Multimedia Communications, Network Security, and Machine Learning
Mark Stamp
Professor of Computer Science
Information Security, Cybersecurity, Malware, Machine Learning, Deep Learning, Artificial
Intelligence
ORCID: 0000-0002-3803-8368
Potential collaborators and members of the media may contact us at officeofresearch@bianlifan.com.