Texas ChristianUniversity
NextGen Research Lab
Current Research Projects
Our research lab is focused on addressing key challenges in modern technology, including cybersecurity, education, and next-generation networks. We are exploring how AI, machine learning (ML), and large language models (LLMs) can improve cybersecurity, assist small businesses, and enhance educational outcomes. Additionally, we work on advancing the implementation of key technologies for 5G, beyond 5G (B5G), and 6G networks, as well as optimizing massive MIMO and mmWave systems for efficient and secure communications.
AI and ML for Cybersecurity Offense and Defense
Our work is focused on exploring ML and AI techniques for phishing detection, automated attack and defense strategies, malware detection, intrusion detection, and secure authentication.
- Investigate the effectiveness of ML algorithms and LLMs for phishing email and phishing URL detection.
- Explore ML and LLMs for phishing email and phishing URL detection.
- Explore AI and ML for malware, threat, intrusion detection, network traffic analysis, and secure authentication.
- Assist small businesses in securing their networks using AI, ML, and LLM-based tools.
AI for Education
Our research explores the transformative role of AI and large language models (LLMs) in education, focusing on:
- Enhancing personalized learning experiences through AI-driven educational tools.
- Developing LLM-based systems to assist students with real-time academic support.
- Evaluating the effectiveness of LLMs in improving learning outcomes across diverse educational settings.
- Investigating how AI can bridge learning gaps by providing tailored assistance to underrepresented student populations.
Key Enabling Technologies for 5G, Beyond 5G and 6G Networks
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We are exploring the key enabling technologies for B5G and 6G networks and its implementaion challenges. The goal is to improve data rate, latency, reliability, security, and energy efficiency.
- Explore AI, ML, and quantum communication for next-generation networks.
- Design signal detection, channel estimation, channel modeling, user scheduling algorithms, and frameworks for B5G and 6G networks.
- Explore Ultra-Massive MIMO, millimeter wave, and terahertz-wave bands.
Massive MIMO and mmWave System for Next-Generation Networks
Our work on massive MIMO is focused on overcoming several implementation issues for the massive MIMO technology — improving signal detection, design of robust user scheduling algorithms, mitigation of pilot contamination, and hardware architecture designs.
- Develop low complex and efficient algorithms and their hardware designs to address current challenges on signal detection, precoding, channel estimation, user scheduling, and pilot contamination.
- Investigate the use of Massive MIMO for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. The goal is to allow efficient and faster exchange of data while mitigating interference.
- Explore the use of machine learning and deep learning algorithms for massive MIMO channel estimation to predict statistical channel characteristics for enhancing physical layer security.