NetML Lab | University of Central Missouri

Join NetML Lab

NetML Lab welcomes motivated students interested in artificial intelligence for cybersecurity, including machine learning, deep learning, and large language model–based approaches. Our work emphasizes optimization-driven dimensionality reduction, network traffic intelligence, and interpretable AI for security analytics.

Students in the lab engage in hands-on research involving search-based model refinement, security telemetry analysis, and experimental validation across real-world datasets. Active participation in research and publication is expected.

Applicants should have solid programming skills (Python preferred), strong analytical thinking, and a genuine interest in AI-driven cybersecurity research.

Our research has been featured in:
Chameleon Cloud Research Blog
Cybersecurity Guide Podcast

To apply, email your CV and a brief statement of research interests to aksoy {at} ucmo.edu.

Director:

Ahmet Aksoy, Ph.D. Associate Professor aksoy {at} ucmo.edu

Current Students:

		Yaman Shrestha Leveraging Large Language Models for Efficient Incident Classification in Cybersecurity yxs33220 {at} ucmo.edu
		Khursaid Ansari Leveraging Large Language Models for Efficient Incident Classification in Cybersecurity kxa45490 {at} ucmo.edu
		Mayank Dembla AI-Driven User Behavior Fingerprinting for Enhanced Security and Threat Detection mxd08640 {at} ucmo.edu
		Joshua Kiran Yajjala AI-Driven User Behavior Fingerprinting for Enhanced Security and Threat Detection jxy55130 {at} ucmo.edu

Previous Students:

		Sundeep Varma Comparative Analysis of Feature Selection Algorithms for Automated IoT Device Fingerprinting sxv54730 {at} ucmo.edu
		Luis Valle Automated Network Incident Identification through Genetic Algorithm-Driven Feature Selection lev33910 {at} ucmo.edu
		Sachin Rana Automated Fast-flux Detection using Machine Learning and Genetic Algorithms sxr53490 {at} ucmo.edu
		Emiline Stewart Network Traffic Fingerprinting using Artificial Bee Colony Algorithm ers10570 {at} ucmo.edu
		Enya Pan Comparative Analysis of Feature Selection Algorithms for Automated IoT Device Fingerprinting exp99350 {at} ucmo.edu
		Sharwin Reddy Network Traffic Fingerprinting using Ant Colony Algorithm sxp32460 {at} ucmo.edu

Lab: